WO1994021065A1 - Method and apparatus for coherent communication in a spread-spectrum communication system - Google Patents

Method and apparatus for coherent communication in a spread-spectrum communication system Download PDF

Info

Publication number
WO1994021065A1
WO1994021065A1 PCT/US1994/001746 US9401746W WO9421065A1 WO 1994021065 A1 WO1994021065 A1 WO 1994021065A1 US 9401746 W US9401746 W US 9401746W WO 9421065 A1 WO9421065 A1 WO 9421065A1
Authority
WO
WIPO (PCT)
Prior art keywords
stream
channel
samples
estimated
symbols
Prior art date
Application number
PCT/US1994/001746
Other languages
French (fr)
Inventor
Fuyun Ling
Original Assignee
Motorola Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Family has litigation
First worldwide family litigation filed litigation Critical https://patents.darts-ip.com/?family=21858459&utm_source=google_patent&utm_medium=platform_link&utm_campaign=public_patent_search&patent=WO1994021065(A1) "Global patent litigation dataset” by Darts-ip is licensed under a Creative Commons Attribution 4.0 International License.
Application filed by Motorola Inc. filed Critical Motorola Inc.
Priority to BR9404420A priority Critical patent/BR9404420A/en
Priority to CA002134230A priority patent/CA2134230C/en
Priority to PL94306002A priority patent/PL174713B1/en
Priority to EP94913263A priority patent/EP0643889B1/en
Priority to DE69430720T priority patent/DE69430720T2/en
Priority to JP52000694A priority patent/JP3464002B2/en
Publication of WO1994021065A1 publication Critical patent/WO1994021065A1/en
Priority to SE9403860A priority patent/SE520542C2/en
Priority to FI945336A priority patent/FI112010B/en

Links

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842Weighted combining
    • H04B7/0845Weighted combining per branch equalization, e.g. by an FIR-filter or RAKE receiver per antenna branch
    • HELECTRICITY
    • H03ELECTRONIC CIRCUITRY
    • H03MCODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M13/00Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B1/00Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/69Spread spectrum techniques
    • H04B1/707Spread spectrum techniques using direct sequence modulation
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/005Control of transmission; Equalising
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04KSECRET COMMUNICATION; JAMMING OF COMMUNICATION
    • H04K1/00Secret communication
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00Baseband systems
    • H04L25/02Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202Channel estimation
    • H04L25/0224Channel estimation using sounding signals
    • H04L25/0228Channel estimation using sounding signals with direct estimation from sounding signals

Definitions

  • the present invention relates to communication systems which employ spread-spectrum signals and, more particularly, to a method and apparatus for coherent communication in a spread-spectrum communication system.
  • a communication system generally consists of three basic components: transmitter, channel, and receiver.
  • the transmitter has the function of processing the message signal into a form suitable for transmission over the channel. This processing of the message signal is referred to as modulation.
  • the function of the channel is to provide a physical connection between the transmitter output and the receiver input.
  • the function of the receiver is to process the received signal so as to produce an estimate of the original message signal. This processing of the received signal is referred to as demodulation.
  • One type of communication system is a multiple access spread- spectrum system.
  • a modulation technique is utilized in which a transmitted signal is spread over a wide frequency band within the communication channel.
  • the frequency band is much wider than the minimum bandwidth required to transmit the information being sent.
  • a voice signal for example, can be sent with amplitude modulation (AM) in a bandwidth only twice that of the information itself.
  • AM amplitude modulation
  • FM low deviation frequency modulation
  • single sideband AM also permit information to be transmitted in a bandwidth comparable to the bandwidth of the information itself.
  • the modulation of a signal to be transmitted often includes taking a baseband signal (e.g., a voice channel) with a bandwidth of only a few kilohertz, and distributing the signal to be transmitted over a frequency band that may be many megahertz wide. This is accomplished by modulating the signal to be transmitted with the information to be sent and with a wideband encoding signal.
  • a baseband signal e.g., a voice channel
  • distributing the signal to be transmitted over a frequency band that may be many megahertz wide This is accomplished by modulating the signal to be transmitted with the information to be sent and with a wideband encoding signal.
  • direct sequence modulation a carrier signal is modulated by a digital code sequence whose bit rate is much higher than the information signal bandwidth.
  • Information i.e. the message signal consisting of voice and/or data
  • the direct sequence spread-spectrum signal can be embedded in the direct sequence spread-spectrum signal by several methods.
  • One method is to add the information to the spreading code before it is used for spreading modulation. It will be noted that the information being sent must be in a digital form prior to adding it to the spreading code, because the combination of the spreading code and the information typically a binary code involves modulo-2 addition. Alternatively, the information or message signal may be used to modulate a carrier before spreading it.
  • These direct sequence spread-spectrum communication systems can readily be designed as multiple access communication systems.
  • a spread-spectrum system may be designed as a direct sequence code division multiple access (DS-CDMA) system, in a DS- CDMA system, communication between two communication units is accomplished by spreading each transmitted signal over the frequency band of the communication channel with a unique user spreading code.
  • transmitted signals are in the same frequency band of the communication channel and are separated only by unique user spreading codes.
  • unique user spreading codes preferably are orthogonal to one another such that the cross-correlation between the spreading codes is approximately zero.
  • Particular transmitted signals can be retrieved from the communication channel by despreading a signal representative of the sum of signals in the communication channel with a user spreading code related to the particular transmitted signal which is to be retrieved from the communication channel.
  • the received signal can be correlated with a particular user spreading code such that only the desired user signal related to the particular spreading code is enhanced while the other signals for all of the other users are not enhanced.
  • spreading codes include but are not limited to pseudonoise (PN) codes and Walsh codes.
  • PN pseudonoise
  • a Walsh code corresponds to a single row or column of the Hadamard matrix. Further it will be appreciated by those skilled in the art that spreading codes can be used to channel code data signals.
  • the data signals are channel coded to improve performance of the communication system by enabling transmitted signals to better withstand the effects of various channel impairments, such as noise, fading, and jamming.
  • channel coding reduces the probability of bit error, and/or reduces the required signal to noise ratio usually expressed as error bits per noise density (i.e., E /No which is defined as the ratio of energy per information-bit to noise-spectral density) , to recover the signal at the cost of expending more bandwidth than would otherwise be necessary to transmit the data signal.
  • E /No error bits per noise density
  • Walsh codes can be used to channel code a data signal prior to modulation of the data signal for subsequent transmission.
  • PN spreading codes can be used to channel code a data signal.
  • channel coding alone may not provide the required signal to noise ratio for some communication system designs which require the system to be able to handle a particular number of simultaneous communications (all having a minimum signal to noise ratio).
  • This design constraint may be satisfied, in some instances, by designing the communication system to coherently detect transmitted signals rather than using non-coherent reception techniques.
  • a coherent receiver requires less signal to noise ratio (in Eb N 0 ) than that required by a non-coherent receiver having the same bit error rate (i.e., a particular design constraint denoting an acceptable interference level).
  • dB deciBel
  • One such method for facilitating coherent detection of transmitted signals is to use a pilot signal.
  • the forward channel, or down-link (i.e., from base station to mobile unit) may be coherently detected, if the base station transmits a pilot signal. Subsequently, all the mobile units use the pilot channel signal to estimate the channel phase and magnitude parameters.
  • the reverse channel, or up-link (i.e., from mobile to base station)
  • using such a common pilot signal is not feasible.
  • those of ordinary skill in the art often assume that only non-coherent detection techniques are suitable for up-link communication.
  • CDMA Code Division Multiple Access
  • the Y. J. Liu article describes a more sophisticated detection technique in which the performance of the up-link DS-CDMA communication system with Walsh coding and bit-level interleaving can be improved with a 4-port diversity combining without changing the interleaving method.
  • a method and apparatus is provided for encoding and decoding to facilitate coherent communication.
  • reference symbols are inserted into a stream of input data symbols to form a reference coded stream of input data symbols.
  • the reference coded stream of input data symbols are prepared for transmission over a communication channel by spreading the reference coded stream of input data symbols with a spreading code prior to transmission over the communication channel.
  • decoding a received communication signal is despread with a spreading code to derive a stream of reference samples and a stream of data samples.
  • the channel response is estimated by utilizing the stream of reference samples.
  • an estimated data symbol is detected from the stream of data samples by utilizing the estimated channel response.
  • FIG. 1 is a block diagram showing a preferred embodiment communication system in accordance with the present invention.
  • FIG. 2 is a block diagram showing a preferred embodiment communication channel frame structure for use in the preferred embodiment communication system shown in FIG. 1.
  • FIG. 3 is a block diagram showing a preferred embodiment channel estimator for use in the preferred embodiment communication system shown in FIG. 1.
  • Data-based channel estimation may be implemented as decision-directed or non-decision-directed.
  • the channel estimator must operate at low signal-to-noise ratios and the fading is relatively fast. As a result, the decision-directed approach is not appropriate due to the high decision error rate.
  • a non-decision-directed method such as the one described in the article by A. J. Viterbi and A. M. Viterbi, "Nonlinear Estimation of PSK- Modulated Carrier Phase with Application to Burst Digital Transmission," IEEE Trans, on Info. Theory, Vol.
  • phase ambiguity e.g., 180° ambiguity for binary phase shift keying (BPSK) or 90° ambiguity for quadrature phase shift keying (QPSK)
  • BPSK binary phase shift keying
  • QPSK quadrature phase shift keying
  • Reference- symbol-based channel estimation is described as follows. Reference symbols known to the receiver are inserted into a sequence of information bearing data symbols, which may be coded symbols. At the receiver, the received signal samples corresponding to the reference symbols are used to generate a channel estimate. Because the reference symbols are known to the receiver, there are no decision errors and the resulting channel estimate does not have a phase ambiguity. As a result, a robust communication system with non- differentially coded signaling is provided.
  • the inserted reference symbols can be organized in blocks or uniformly distributed. For a flat fading channel, it is desirable to insert reference symbols periodically and uniformly in the data stream. For a DS-CDMA up-link with a RAKE receiver for front end processing, we can treat the output of each RAKE "finger" as being a flat faded signal. Thus, the preferred embodiment communication system will uniformly insert one reference symbol for every M coded data symbols.
  • the basic operation of RAKE receivers are described in an article by R. Price and P.E. Green, Jr., "A Communication Technique for Multipath Channels," Proceedings of the IRE, March 1958, pages 555- 570. Briefly, a RAKE receiver performs a continuous, detailed measurement of the multipath characteristic of a received signal.
  • traffic channel data bits 102 are input to an encoder 104 at a particular bit rate (e.g., 9.6 kilobit/second).
  • the input traffic channel data bits can include either voice converted to data by a vocoder, pure data, or a combination of the two types of data.
  • Encoder 104 encodes the input data bits 102 into data symbols at a fixed encoding rate (1/r) with an encoding algorithm which facilitates subsequent maximum likelihood decoding of the data symbols into data bits (e.g. convolutional or block coding algorithms).
  • encoder 104 encodes input data bits 102 (e.g., 192 input data bits that were received at a rate of 9.6 kilobits/second) at a fixed encoding rate of one data bit to three data symbols (i.e., 1/3) such that the encoder 102 outputs data symbols 106 (e.g., 576 data symbols output at a 28.8 kilosymbols/second rate).
  • input data bits 102 e.g., 192 input data bits that were received at a rate of 9.6 kilobits/second
  • data symbols 106 e.g., 576 data symbols output at a 28.8 kilosymbols/second rate
  • the data symbols 106 are then input into an interleaver 108.
  • Interleaver 108 organizes the data symbols 106 into blocks (i.e., frames) and block interleaves the input data symbols 106 at the symbol level.
  • the data symbols are individually input into a matrix which defines a predetermined size block of data symbols.
  • the data symbols are input into locations within the matrix so that the matrix is filled in a column by column manner.
  • the data symbols afe individually output from locations within the matrix so that the matrix is emptied in a row by row manner.
  • the matrix is a square matrix having a number of rows equal to the number of columns; however, other matrix forms can be chosen to increase the output interleaving distance between the consecutively input non-interleaved data symbols.
  • the interleaved data symbols 110 are output by the interleaver 108 at the same data symbol rate that they were input (e.g., 28.8 kilosymbols/second).
  • the predetermined size of the block of data symbols defined by the matrix is derived from the maximum number of data symbols which can be transmitted at a coded bit rate within a predetermined length transmission block.
  • the predetermined size of the block of data symbols is 28.8 kilosymbols/second times 20 milliseconds which equals 576 data symbols which defines a 18 by 32 matrix.
  • reference bit inserter 112 outputs 672 reference-coded bits 114 for each block (i.e., frame) such that a reference bit is inserted between each group of six data symbols.
  • An example of a transmitted block (i.e., frame) of reference-coded data symbols 114 consisting of 42 bits is shown in FIG. 2 (where each d represents a data symbol and each r represents a reference bit).
  • the reference-coded data symbols 114 is output from encoding portion 100 of the communication system and input to a transmitting portion 116 of the communication system.
  • the data symbols 114 are prepared for transmission over a communication channel by " a modulator 117. Subsequently, the modulated signal is provided to an antenna 118 for transmission over the communication channel 120.
  • the modulator 117 preferably prepares the data symbols 114 for direct sequence code divided spread-spectrum transmission by deriving a sequence of fixed length codes from the reference-coded data symbols 114 in a spreading process. For example, each of the data symbols within the stream of reference-coded data symbols 114 may be spread to a unique nine bit length code such that a group of six data symbols is represented by a single 54 bit length code. In addition, each reference bit within the stream of reference-coded data symbols 114 may select a ten bit length code. The codes representing the group of six data symbols and an associated reference bit preferably are combined to form a single 64 bit length code.
  • the modulator 117 which received the reference- coded data symbols 114 at a fixed rate (e.g., 28.8 kilosymbols/second) now has a spread sequence of 64 bit length codes having a higher fixed symbol rate (e.g., 307.2 kilosymbols/second).
  • a fixed rate e.g. 28.8 kilosymbols/second
  • the reference bits and data symbols within the stream of reference-coded data symbols 114 may be spread according to numerous other algorithms into a sequence of larger length codes without departing from the scope and spirit of the present invention.
  • the spread sequence is further prepared for direct sequence code divided spread-spectrum transmission by further spreading the spread sequence with a long spreading code (e.g. PN code).
  • the spreading code is a user specific sequence of symbols or unique user code which is output at a fixed chip rate (e.g., 1.228 Megachips/second).
  • the unique user code enhances the security of the communication in the communication channel by scrambling the encoded traffic channel data bits 102.
  • the user code spread encoded data bits i.e. data symbols
  • the sinusoid output signal is bandpass filtered, translated to an RF frequency, amplified, filtered and radiated by an antenna 118 to complete transmission of the traffic channel data bits 102 in a communication channel 120 with BPSK modulation.
  • a receiving portion 122 of the communication system receives the transmitted spread-spectrum signal from over the communication channel 120 through antenna 124.
  • the received signal is sampled into data samples by despreader and sampler 126. Subsequently, the data samples 142 are output to the decoding portion 154 of the communication system.
  • the despreader and sampler 126 preferably BPSK samples the received spread-spectrum signal by filtering, demodulating, translating from the RF frequencies, and sampling at a predetermined rate (e.g., 1.2288 Megasamples/second). Subsequently, the BPSK sampled signal is despread by correlating the received sampled signals with the long spreading code. The resulting despread sampled signal 128 is sampled at a predetermined rate and output to a reference bit extractor 130 (e.g., 307.2 kilosamples/second so that a sequence of four samples of the received spread-spectrum signal is despread and/or represented by a single data sample).
  • a reference bit extractor 130 e.g., 307.2 kilosamples/second so that a sequence of four samples of the received spread-spectrum signal is despread and/or represented by a single data sample.
  • the reference bit extractor 130 preferably extracts the reference bits 132 from the despread sampled signal 128 and outputs the reference bits 132 to a channel estimator 134.
  • the remaining data samples 138 from the despread sampled signal 128 are output to a coherent detector 140 for later coherent detection of data samples 142.
  • the channel estimator 134 correlates the extracted reference bits 132 with a known reference sequence of data samples to obtain unbiased, but noisy, channel estimates. In order to obtained a better channel estimate 136, these noisy estimates may be passed through a low-pass filter, which may be fixed or adaptive, to remove the high frequency noise components.
  • the resulting channel estimates 136 are relatively noise-free and can be used for coherent detection.
  • M the number of data symbols between each reference bit inserted by reference bit inserter 112
  • T the time interval of each data sample.
  • power control may also be used to enhance overall system performance.
  • the power control algorithms may be very similar to the algorithms used in non-coherent communication systems.
  • the preferred embodiment power control algorithm preferably includes estimating received power every 1.25 ms (i.e., each block or frame), or every 12 information bits, i.e., every 36 encoded bits or 42 total received signal samples.
  • the power estimate may be calculated with several different techniques. One technique is to compute a channel estimate with a power estimator 146 by using simply the six reference signal samples (i.e., reference bits 144 from reference bit extractor 130)in a 42 bit length block. The square of the magnitude of the channel estimate is then output by the power estimator 146 as the power estimate 148. After channel estimates 136 are generated, the rest of the receiver is conventional.
  • the coherent detector 140 multiplies the remaining data samples 138 from the despread sampled signal 128 by the conjugate of the channel estimates 136 to generate coherently detected samples 142.
  • the Nth receiver portion would operate in substantially the same manner to retrieve data samples from the received spread-spectrum signal in communication channel 120 as the above described receiving portion 122.
  • the outputs 142 through 152 of the N receiving portions preferably are input to a multiplier 150 which diversity combines the input data samples into a composite stream of coherently detected data samples 160.
  • the individual data samples 160 which form soft decision data are then input into a decoding portion 154 including a deinterleaver 162 which deinterleaves the input soft decision data 160 at the individual data level.
  • the soft decision data 160 are individually input into a matrix which defines a predetermined size block of soft decision data.
  • the soft decision data are input into locations within the matrix so that the matrix is filled in a row by row manner.
  • the deinterieaved soft decision data 164 are individually output from locations within the matrix so that the matrix is emptied in a column by column manner.
  • the deinterieaved soft decision data 164 are output by the deinterleaver 162 at the same rate that they were input (e.g., 28.8Diacs/second).
  • the predetermined size of the block of soft decision data defined by the matrix is derived from the maximum rate of sampling data samples from the spread-spectrum signal received within the predetermined length transmission block.
  • the deinterieaved soft decision data 164 are input to a decoder 166 which uses maximum likelihood decoding techniques to generate estimated traffic channel data bits 168.
  • the maximum likelihood decoding techniques may be augmented by using an algorithm which is substantially similar to a Viterbi decoding algorithm.
  • the decoder 166 uses a group of the individual soft decision data 164 to form a set of soft decision transition metrics for use at each particular time state of the maximum likelihood sequence estimation decoder 166.
  • the number of soft decision data 164 in the group used to form each set of soft decision transition metrics corresponds to the number of data symbols 106 at the output of the convolutional encoder 104 generated from each input data bit 102.
  • the number of soft decision transition metrics in each set is equal to two raised to the power of the number of soft decision data 164 in each group. For example, when a 1/3 convolutional encoder is used in the transmitter, three data symbols 106 are generated from each input data bit 102. Thus, decoder 166 uses groups of three individual soft decision data 164 to form eight soft decision transition metrics for use at each time state in the maximum likelihood sequence estimation decoder 166.
  • the estimated data bits 168 are generated at a rate related to the rate that the soft decision data 164 are input to the decoder 166 and the fixed rate used to originally encode the input data bits 102 (e.g., if the soft decision data are input at 28.8Diacs/second and the original encoding rate was 1/3 then estimated data bits 168 are output at a rate of 9600 bits/second).
  • the communication system includes a first portion ' which encodes input data bits into data symbols, interleaves the data symbols in a symbol by symbol manner, inserts reference bits into the interleaved symbols, modulates and transmits the reference-coded data symbols over a communication channel.
  • the communication system further includes a second portion which receives and demodulates a signal from over the communication channel, estimates parameters of the communication channel, coherently demodulates data samples within received signal, deinterleaves the coherently detected data samples which are used as soft decision data within each received transmission block, subsequently generates soft decision transition metrics from the deinterieaved individual soft decision data, and subsequently generates estimated data bits from the soft decision metrics by using maximum likelihood decoding techniques.
  • a fading channel can be modeled as a complex valued function of time t, denoted by h(t).
  • the time interval of the convolutionally encoded- reference bits is denoted by T.
  • N 3 may be chosen. By doing so, an estimate is obtained for every reference bit interval T r using 7 of the noisy estimates.
  • h(kT) -[(7-i)x h(7nT) + ixh(7nT+7T)] (eq- 3)-
  • the optimal filter would have a frequency response, i.e. the Fourier transform of w ⁇ denoted as:
  • FIR finite impulse response
  • FIG. 3 illustrates how (eq. 5) may be implemented to generate a channel estimate using weighed average of noise channel estimated based on the reference signal.
  • the loss is mainly caused by two factors. First, because of the insertion of non-information bearing reference bits, the energy per information bit (Eb) is effectively reduced (i.e., the data rate is reduced), when the total transmitted power remains the same. Second, in the presence of noise, there are errors in the channel estimates. The total loss is the combined result of these two factors.
  • the loss in E b due to reference insertion, denoted by ⁇ j, can be simply expressed as:
  • a DS-CDMA up-link can be viewed as multiple flat fading channels.
  • the received signal after despreading can be expressed as:
  • r(k) is the received sample at kT
  • a(k) is the corresponding transmitted data or reference symbol
  • h(k) is a low-pass random complex variable characterizing the fading channel
  • z(k) is the additive noise or interference, which is approximately white and Gaussian.
  • the average signal to noise ratio is equal to
  • 2 is the noise variance.
  • h(k) is unbiased and Gaussian distributed.
  • Its power spectrum, called Doppler spectrum is given by:
  • f d is the Doppler frequency, which is a function of the carrier frequency and the mobile communication unit speed. It can be further assumed that BPSK signaling is used. It will be appreciated by those skilled in the art that the following assumptions also are applicable to quadrature phase shift keying signaling. Given that
  • 1 , then it may be assumed that the reference symbols are inserted at (M+1 )kT, so that a((M + 1)k) and r((M+1)k) are the reference symbols and the corresponding received samples, respectively. By multiplying r((M + 1)k) with the conjugate of the reference symbol a ' ((M + 1)k), the resulting channel estimate is:
  • h((M+1)k) is a low-pass random variable and the second term is the channel estimation error.
  • the channel estimate at (M+1)kT can be further improved, i.e., the variance of the channel estimation error can be reduced.
  • Wiener filtering theory the optimal unbiased channel estimate, in the sense of maximizing the ratio of signal energy to the variance of estimation error, can be obtained by passing h((M+1)k) through a linear-phase filter whose magnitude response is equal to the square-root of the quotient of H(f) divided by the noise spectrum.
  • the optimal channel estimator based on the inserted reference symbols is indeed a linear phase matched filter, which is matched to the channel Doppler spectrum divided by the noise spectrum. Practically, it is difficult to implement such an optimal estimator, because the Doppler and noise spectra are usually not known and will change with time.
  • a sub-optimum and realistic solution is to use a fixed, linear-phase, low-pass filter, whose cut-off frequency is greater than or equal to the maximum possible Doppler frequency.
  • h((M + 1)k) h((M+1)k) + z((M+1)k) (eq. 10).
  • the channel estimates at kT, for k ⁇ (M+1 )k can be generated according to (eq. 3). From (eq. 7) and (eq. 10) the coherently detected samples can be written as:
  • the system performance may be optimized by selecting a proper M to minimize ⁇ to tai-
  • the allowable maximum Doppler frequency should be less than the effective bandwidth of the filter.
  • a filter may be designed which has a transition band from 200 Hertz to 400 Hertz.
  • the resulting filter will have a delay less than five millisecond while keeping the effective bandwidth equal to 300 Hertz.
  • the mobile communication unit speed is less than 220 kilometers per hour.
  • the data and reference symbols are transmitted continuously.
  • the reference signals are available every T r time interval and these reference signals can be used for channel estimation by means of low- pass filtering.
  • the referenced symbols are also transmitted discontinuously and the low pass filtering method described above should be modified to be applicable as described below.
  • the channel response h(kT) may be expressed as:
  • ⁇ and ⁇ are two complex constants to be estimated. These two constants may be determined by using the received reference samples through linear best-fitting based on the least squares (LS) principle. The details of such estimation methods are illustrated by the following example. If a transmitted data block (i.e., frame) is assumed to consists of 36 data symbols and with 6 inserted reference symbols (see FIG. 2). As a result, 42 symbols are transmitted per data block. This data block may be separated by time intervals in which no data are transmitted. Thus, when such a short block is received, we only have 6 reference samples during the time interval of interest.
  • LS least squares
  • the channel estimation is performed by using only the received reference samples.
  • a(k) is the kth transmitted symbol, which can be either a data symbol (not known to the receiver) or a reference symbol (known to the receiver), and z(k) is the additive noise at k.
  • LS estimates of ⁇ and ⁇ may satisfy the following:
  • the modulator, antennas and demodulator portions of the preferred embodiment communication system as described were directed to CDMA spread-spectrum signals transmitted over a radio communication channel.
  • the encoding and decoding techniques described and claimed herein can also be adapted for use in other types of transmission systems like those based on time division multiple access (TDMA) and frequency division multiple access (FDMA).
  • the communication channel could alternatively be an electronic data bus, wireline, optical fiber link, satellite link, or any other type of communication channel.

Abstract

A method and apparatus is provided for encoding and decoding to facilitate coherent communication. In encoding, reference symbols are inserted into a stream of input data symbols (110) to form a reference coded stream of input data symbols (114). Subsequently, the reference coded stream of input data symbols are prepared for transmission over a communication channel by spreading the reference coded stream of input data symbols with a spreading code prior to transmission over the communication channel. In decoding, a received communication signal (120) is despread with a spreading code to derive a stream of reference samples (132) and a stream of data samples (138). The channel response is estimated by utilizing the stream of reference samples (132). Finally, an estimated data symbol is detected from the stream of data samples (138) by utilizing the estimated channel response.

Description

METHOD AND APPARATUS FOR COHERENT
COMMUNICATION IN A SPREAD-SPECTRUM
COMMUNICATION SYSTEM
Field of the Invention
The present invention relates to communication systems which employ spread-spectrum signals and, more particularly, to a method and apparatus for coherent communication in a spread-spectrum communication system.
Background of the Invention
Communication systems take many forms. In general, the purpose of a communication system is to transmit information-bearing signals from a source, located at one point, to a user destination, located at another point some distance away. A communication system generally consists of three basic components: transmitter, channel, and receiver. The transmitter has the function of processing the message signal into a form suitable for transmission over the channel. This processing of the message signal is referred to as modulation. The function of the channel is to provide a physical connection between the transmitter output and the receiver input. The function of the receiver is to process the received signal so as to produce an estimate of the original message signal. This processing of the received signal is referred to as demodulation.
One type of communication system is a multiple access spread- spectrum system. In a spread-spectrum system, a modulation technique is utilized in which a transmitted signal is spread over a wide frequency band within the communication channel. The frequency band is much wider than the minimum bandwidth required to transmit the information being sent. A voice signal, for example, can be sent with amplitude modulation (AM) in a bandwidth only twice that of the information itself. Other forms of modulation, such as low deviation frequency modulation (FM ) or single sideband AM , also permit information to be transmitted in a bandwidth comparable to the bandwidth of the information itself. However, in a spread-spectrum system, the modulation of a signal to be transmitted often includes taking a baseband signal (e.g., a voice channel) with a bandwidth of only a few kilohertz, and distributing the signal to be transmitted over a frequency band that may be many megahertz wide. This is accomplished by modulating the signal to be transmitted with the information to be sent and with a wideband encoding signal. Three general types of spread-spectrum communication techniques exist, including direct sequence modulation, frequency and/or time hopping modulation, and chirp modulation. In direct sequence modulation, a carrier signal is modulated by a digital code sequence whose bit rate is much higher than the information signal bandwidth.
Information (i.e. the message signal consisting of voice and/or data) can be embedded in the direct sequence spread-spectrum signal by several methods. One method is to add the information to the spreading code before it is used for spreading modulation. It will be noted that the information being sent must be in a digital form prior to adding it to the spreading code, because the combination of the spreading code and the information typically a binary code involves modulo-2 addition. Alternatively, the information or message signal may be used to modulate a carrier before spreading it. These direct sequence spread-spectrum communication systems can readily be designed as multiple access communication systems. For example, a spread-spectrum system may be designed as a direct sequence code division multiple access (DS-CDMA) system, in a DS- CDMA system, communication between two communication units is accomplished by spreading each transmitted signal over the frequency band of the communication channel with a unique user spreading code. As a result, transmitted signals are in the same frequency band of the communication channel and are separated only by unique user spreading codes. These unique user spreading codes preferably are orthogonal to one another such that the cross-correlation between the spreading codes is approximately zero. Particular transmitted signals can be retrieved from the communication channel by despreading a signal representative of the sum of signals in the communication channel with a user spreading code related to the particular transmitted signal which is to be retrieved from the communication channel. Further, when the user spreading codes are orthogonal to one another, the received signal can be correlated with a particular user spreading code such that only the desired user signal related to the particular spreading code is enhanced while the other signals for all of the other users are not enhanced. It will be appreciated by those skilled in the art that several different spreading codes exist which can be used to separate data signals from one another in a DS-CDMA communication system. These spreading codes include but are not limited to pseudonoise (PN) codes and Walsh codes. A Walsh code corresponds to a single row or column of the Hadamard matrix. Further it will be appreciated by those skilled in the art that spreading codes can be used to channel code data signals. The data signals are channel coded to improve performance of the communication system by enabling transmitted signals to better withstand the effects of various channel impairments, such as noise, fading, and jamming. Typically, channel coding reduces the probability of bit error, and/or reduces the required signal to noise ratio usually expressed as error bits per noise density (i.e., E /No which is defined as the ratio of energy per information-bit to noise-spectral density), to recover the signal at the cost of expending more bandwidth than would otherwise be necessary to transmit the data signal. For example, Walsh codes can be used to channel code a data signal prior to modulation of the data signal for subsequent transmission. Similarly PN spreading codes can be used to channel code a data signal.
However, channel coding alone may not provide the required signal to noise ratio for some communication system designs which require the system to be able to handle a particular number of simultaneous communications (all having a minimum signal to noise ratio). This design constraint may be satisfied, in some instances, by designing the communication system to coherently detect transmitted signals rather than using non-coherent reception techniques. It will be appreciated by those skilled in the art that a coherent receiver requires less signal to noise ratio (in Eb N0) than that required by a non-coherent receiver having the same bit error rate (i.e., a particular design constraint denoting an acceptable interference level). Roughly speaking, there is a three deciBel (dB) difference between them for the Rayleigh fading channel. The advantage of the coherent receiver is more significant when diversity reception is used, because there is no combining loss for an optimal coherent receiver while there is always a combining loss for noncoherent receiver.
One such method for facilitating coherent detection of transmitted signals is to use a pilot signal. For example, in a cellular communication system the forward channel, or down-link, (i.e., from base station to mobile unit) may be coherently detected, if the base station transmits a pilot signal. Subsequently, all the mobile units use the pilot channel signal to estimate the channel phase and magnitude parameters. However, for the reverse channel, or up-link, (i.e., from mobile to base station), using such a common pilot signal is not feasible. As a result, those of ordinary skill in the art often assume that only non-coherent detection techniques are suitable for up-link communication.
As a result, many recent publications have focused on optimizing non-coherent reception in DS-CDMA systems. See for example the following articles.
A. Salmasi and K.S. Gilhousen, "On The System Design Aspects of Code Division Multiple Access (CDMA) Applied to Digital Cellular And Personal Communications
Networks," Proc. of VTC91, pp. 57-62, 1991. F. Ling and D. Falconer, "Orthogonal Convolutional Coding for Reverse Channel CDMA Communication," Proc. of VTC'92, pp. 63-66, May, 1992, Denver, CO.
• L F. Chang and N. R. Sollenberger, "Comparison of Two Interleaving Techniques for CDMA Radio Communication Systems," Proc. of VTC'92, pp. 275-278, May, 1992, Denver, CO.
• Y. J. Liu, "Soft Decision Decoding for a Bit-Interleaved
Convolutionally Encoded Code Division Multiple Access System over Rayleigh Fading Channel," Proc. of PIMRC'92, pp. 128-132, Oct. 1992.
Each of these articles show that a substantial difference in performance exists when different coding, modulation, detection and interleaving techniques are used for up-link communication in cellular communication systems.
In the A. Salmasi and K.S. Gilhousen article, a DS-CDMA communication system is described which uses bit-by-bit interleaving within convolutional and orthogonal coding scheme to optimize non¬ coherent reception in DS-CDMA communication systems.
In the F. Ling and D. Falconer article as well as the L. F. Chang and N. R. Sollenberger article, an up-link DS-CDMA system that employs Walsh coding (i.e., orthogonal coding), non-coherent detection and using orthogonal symbol (i.e., word-by-word) interleaving instead of bit-by-bit interleaving was disclosed. The L F. Chang and N. R. Sollenberger article shows that a word-by-word interleaved convolutional and orthogonal coding scheme requires about 1 to 1.4 dB less Eb N0 than the similar bit-by-bit interleaving scheme described by in the A. Salmasi and K.S. Gilhousen article when the communication system which employs either scheme also utilizes power control of mobile communication unit which move at different speeds (e.g., move at rate ranging from 0 to 100 kilometers per hour). While the word-by- word interleaving convolutional/orthogonal coding scheme has better performance than the bit-by-bit one, it has less implicit diversity than the latter. Moreover, it is still a non-coherent communication system and the combing loss can not be avoided.
Finally, the Y. J. Liu article describes a more sophisticated detection technique in which the performance of the up-link DS-CDMA communication system with Walsh coding and bit-level interleaving can be improved with a 4-port diversity combining without changing the interleaving method.
However, even in view of the above-described improvements for non-coherent communication systems, a need still exists for a communication system which employs coherent detection techniques.
Summary of the Invention
A method and apparatus is provided for encoding and decoding to facilitate coherent communication. In encoding, reference symbols are inserted into a stream of input data symbols to form a reference coded stream of input data symbols. Subsequently, the reference coded stream of input data symbols are prepared for transmission over a communication channel by spreading the reference coded stream of input data symbols with a spreading code prior to transmission over the communication channel. In decoding, a received communication signal is despread with a spreading code to derive a stream of reference samples and a stream of data samples. The channel response is estimated by utilizing the stream of reference samples. Finally, an estimated data symbol is detected from the stream of data samples by utilizing the estimated channel response.
Brief Description of the Drawings
FIG. 1 is a block diagram showing a preferred embodiment communication system in accordance with the present invention. FIG. 2 is a block diagram showing a preferred embodiment communication channel frame structure for use in the preferred embodiment communication system shown in FIG. 1. FIG. 3 is a block diagram showing a preferred embodiment channel estimator for use in the preferred embodiment communication system shown in FIG. 1. Detailed Description
In the course of the following discussion, a new approach for up- link DS-CDMA communication is presented. This new approach employs coherent-detection with reference-symbol based channel estimation. It will be appreciated by those skilled in the art that other types of communication systems (e.g., personal communication systems, trunked systems, satellite communication systems, data networks, and the like) may also be adapted and/or designed to use the principles described herein. It will be shown that a substantial gain in Eb/N0 can be obtained relative to non-coherent detection techniques by applying such a coherent detection method to up-link DS-CDMA communication. In particular, simulation results have shown that the required Eb N0 by using this new scheme is about 2.5 dB lower than non-coherent detection of Walsh coding with bit-by-bit interleaving or 1.3 dB lower than non-coherent detection with Walsh symbol (i.e., word- by-word) interleaving over the entire range of practical mobile communication unit speeds (i.e., speeds of 0 to 100 kilometers per hour). The analysis of this new scheme is given in the frequency- domain. This frequency-domain analysis results in a simple formula that characterizes the performance loss of such a scheme relative to perfect coherent detection.
In order to perform effective coherent detection, it is necessary to obtain an accurate channel estimate. There are basically two types of channel estimation methods: data-based and reference-based. Data- based channel estimation may be implemented as decision-directed or non-decision-directed. For DS-CDMA up-link communication, the channel estimator must operate at low signal-to-noise ratios and the fading is relatively fast. As a result, the decision-directed approach is not appropriate due to the high decision error rate. On the other hand, a non-decision-directed method, such as the one described in the article by A. J. Viterbi and A. M. Viterbi, "Nonlinear Estimation of PSK- Modulated Carrier Phase with Application to Burst Digital Transmission," IEEE Trans, on Info. Theory, Vol. IT-29, No. 4, pp. 543- 551 , Jul. 1983, always has a phase ambiguity, e.g., 180° ambiguity for binary phase shift keying (BPSK) or 90° ambiguity for quadrature phase shift keying (QPSK), in the channel estimate. As a consequence, it is necessary to use differential coding to eliminate its effect. However, as will be appreciated by those skilled in the art, in communication systems having a differential coded signal transmitted over Rayleigh fading channels, even with coherent detection, still need over 3 dB higher Eb No than non-differentially coded phase shift keying (PSK) signaling.
One way to solve the decision error and phase ambiguity problem is to use reference symbols for channel estimation. Reference- symbol-based channel estimation is described as follows. Reference symbols known to the receiver are inserted into a sequence of information bearing data symbols, which may be coded symbols. At the receiver, the received signal samples corresponding to the reference symbols are used to generate a channel estimate. Because the reference symbols are known to the receiver, there are no decision errors and the resulting channel estimate does not have a phase ambiguity. As a result, a robust communication system with non- differentially coded signaling is provided.
The inserted reference symbols can be organized in blocks or uniformly distributed. For a flat fading channel, it is desirable to insert reference symbols periodically and uniformly in the data stream. For a DS-CDMA up-link with a RAKE receiver for front end processing, we can treat the output of each RAKE "finger" as being a flat faded signal. Thus, the preferred embodiment communication system will uniformly insert one reference symbol for every M coded data symbols. The basic operation of RAKE receivers are described in an article by R. Price and P.E. Green, Jr., "A Communication Technique for Multipath Channels," Proceedings of the IRE, March 1958, pages 555- 570. Briefly, a RAKE receiver performs a continuous, detailed measurement of the multipath characteristic of a received signal. This knowledge is then exploited to combat the selective fading by detecting the echo signals individually, using a correlation method, and algebraically combining those echo signals into a single detected signal. The intersymbol interference is attenuated by varying the time delay or phase between the various detected echo signals prior to their algebraic combination.
Referring now to FIG. 1 , a system for coherent communication in a spread-spectrum communication system is shown. In the encoding portion 100 of the communication system, traffic channel data bits 102 are input to an encoder 104 at a particular bit rate (e.g., 9.6 kilobit/second). The input traffic channel data bits can include either voice converted to data by a vocoder, pure data, or a combination of the two types of data. Encoder 104 encodes the input data bits 102 into data symbols at a fixed encoding rate (1/r) with an encoding algorithm which facilitates subsequent maximum likelihood decoding of the data symbols into data bits (e.g. convolutional or block coding algorithms). For example, encoder 104 encodes input data bits 102 (e.g., 192 input data bits that were received at a rate of 9.6 kilobits/second) at a fixed encoding rate of one data bit to three data symbols (i.e., 1/3) such that the encoder 102 outputs data symbols 106 (e.g., 576 data symbols output at a 28.8 kilosymbols/second rate).
The data symbols 106 are then input into an interleaver 108. Interleaver 108 organizes the data symbols 106 into blocks (i.e., frames) and block interleaves the input data symbols 106 at the symbol level. In the interleaver 108, the data symbols are individually input into a matrix which defines a predetermined size block of data symbols. The data symbols are input into locations within the matrix so that the matrix is filled in a column by column manner. The data symbols afe individually output from locations within the matrix so that the matrix is emptied in a row by row manner. Typically, the matrix is a square matrix having a number of rows equal to the number of columns; however, other matrix forms can be chosen to increase the output interleaving distance between the consecutively input non-interleaved data symbols. The interleaved data symbols 110 are output by the interleaver 108 at the same data symbol rate that they were input (e.g., 28.8 kilosymbols/second). The predetermined size of the block of data symbols defined by the matrix is derived from the maximum number of data symbols which can be transmitted at a coded bit rate within a predetermined length transmission block. For example, if data symbols 106 are output from the encoder 104 at a 28.8 kilosymbols/second rate, and if the predetermined length of the transmission block is 20 milliseconds, then the predetermined size of the block of data symbols is 28.8 kilosymbols/second times 20 milliseconds which equals 576 data symbols which defines a 18 by 32 matrix. The interleaved data symbols 110 are then input to a reference bit inserter 112 which inserts L known reference bits for every M interleaved data symbols 110. To simplify the following discussion, it will be assumed that L=1 and M=6. In addition, it will be assumed that each inserted reference bit is a zero bit. However, it will be appreciated by those skilled in the art that L and M could be any other value without departing from the scope and spirit of the present invention. In addition, the reference bits could be any known sequence such as all one bits or several one bits followed by several zero bits without departing from the scope and spirit of the present invention. When L=1 and M=6, reference bit inserter 112 outputs 672 reference-coded bits 114 for each block (i.e., frame) such that a reference bit is inserted between each group of six data symbols. An example of a transmitted block (i.e., frame) of reference-coded data symbols 114 consisting of 42 bits is shown in FIG. 2 (where each d represents a data symbol and each r represents a reference bit).
The reference-coded data symbols 114 is output from encoding portion 100 of the communication system and input to a transmitting portion 116 of the communication system. The data symbols 114 are prepared for transmission over a communication channel by" a modulator 117. Subsequently, the modulated signal is provided to an antenna 118 for transmission over the communication channel 120.
The modulator 117 preferably prepares the data symbols 114 for direct sequence code divided spread-spectrum transmission by deriving a sequence of fixed length codes from the reference-coded data symbols 114 in a spreading process. For example, each of the data symbols within the stream of reference-coded data symbols 114 may be spread to a unique nine bit length code such that a group of six data symbols is represented by a single 54 bit length code. In addition, each reference bit within the stream of reference-coded data symbols 114 may select a ten bit length code. The codes representing the group of six data symbols and an associated reference bit preferably are combined to form a single 64 bit length code. As a result of this spreading process, the modulator 117 which received the reference- coded data symbols 114 at a fixed rate (e.g., 28.8 kilosymbols/second) now has a spread sequence of 64 bit length codes having a higher fixed symbol rate (e.g., 307.2 kilosymbols/second). It will be appreciated by those skilled in the art that the reference bits and data symbols within the stream of reference-coded data symbols 114 may be spread according to numerous other algorithms into a sequence of larger length codes without departing from the scope and spirit of the present invention.
The spread sequence is further prepared for direct sequence code divided spread-spectrum transmission by further spreading the spread sequence with a long spreading code (e.g. PN code). The spreading code is a user specific sequence of symbols or unique user code which is output at a fixed chip rate (e.g., 1.228 Megachips/second). In addition to providing an identification as to which user sent the encoded traffic channel data bits 102 over the communication channel 120, the unique user code enhances the security of the communication in the communication channel by scrambling the encoded traffic channel data bits 102. In addition, the user code spread encoded data bits (i.e. data symbols) are used to bi-phase modulate a sinusoid by driving the power level controls of the sinusoid. The sinusoid output signal is bandpass filtered, translated to an RF frequency, amplified, filtered and radiated by an antenna 118 to complete transmission of the traffic channel data bits 102 in a communication channel 120 with BPSK modulation.
A receiving portion 122 of the communication system receives the transmitted spread-spectrum signal from over the communication channel 120 through antenna 124. The received signal is sampled into data samples by despreader and sampler 126. Subsequently, the data samples 142 are output to the decoding portion 154 of the communication system.
The despreader and sampler 126 preferably BPSK samples the received spread-spectrum signal by filtering, demodulating, translating from the RF frequencies, and sampling at a predetermined rate (e.g., 1.2288 Megasamples/second). Subsequently, the BPSK sampled signal is despread by correlating the received sampled signals with the long spreading code. The resulting despread sampled signal 128 is sampled at a predetermined rate and output to a reference bit extractor 130 (e.g., 307.2 kilosamples/second so that a sequence of four samples of the received spread-spectrum signal is despread and/or represented by a single data sample). The reference bit extractor 130 preferably extracts the reference bits 132 from the despread sampled signal 128 and outputs the reference bits 132 to a channel estimator 134. The remaining data samples 138 from the despread sampled signal 128 are output to a coherent detector 140 for later coherent detection of data samples 142. The channel estimator 134 correlates the extracted reference bits 132 with a known reference sequence of data samples to obtain unbiased, but noisy, channel estimates. In order to obtained a better channel estimate 136, these noisy estimates may be passed through a low-pass filter, which may be fixed or adaptive, to remove the high frequency noise components. The resulting channel estimates 136 are relatively noise-free and can be used for coherent detection. It should be noted that the low pass filtering only gives us a channel estimate for every (M+1)T, where M is the number of data symbols between each reference bit inserted by reference bit inserter 112 (e.g., M=6) and where T is the time interval of each data sample. To perform coherent detection of transmitted data symbols, we need to have a channel estimate for every T. When (M+1)T is short relative to the channel variation time constant, a simple but effective method to get a channel estimate for every T is to perform linear interpolation between two channel estimates separated by (M+1)T. however, as will be appreciated by those skilled in the art more sophisticated interpolation techniques may be used if necessary.
In the preferred embodiment coherent communication system, power control may also be used to enhance overall system performance. The power control algorithms may be very similar to the algorithms used in non-coherent communication systems. The preferred embodiment power control algorithm preferably includes estimating received power every 1.25 ms (i.e., each block or frame), or every 12 information bits, i.e., every 36 encoded bits or 42 total received signal samples. The power estimate may be calculated with several different techniques. One technique is to compute a channel estimate with a power estimator 146 by using simply the six reference signal samples (i.e., reference bits 144 from reference bit extractor 130)in a 42 bit length block. The square of the magnitude of the channel estimate is then output by the power estimator 146 as the power estimate 148. After channel estimates 136 are generated, the rest of the receiver is conventional. The coherent detector 140 multiplies the remaining data samples 138 from the despread sampled signal 128 by the conjugate of the channel estimates 136 to generate coherently detected samples 142.
As will be appreciated by those skilled in the art, multiple receiving portions 122 through 123 and antennae 124 through 125, respectively, to achieve space diversity. The Nth receiver portion would operate in substantially the same manner to retrieve data samples from the received spread-spectrum signal in communication channel 120 as the above described receiving portion 122. The outputs 142 through 152 of the N receiving portions preferably are input to a multiplier 150 which diversity combines the input data samples into a composite stream of coherently detected data samples 160. The individual data samples 160 which form soft decision data are then input into a decoding portion 154 including a deinterleaver 162 which deinterleaves the input soft decision data 160 at the individual data level. In the deinterleaver 162, the soft decision data 160 are individually input into a matrix which defines a predetermined size block of soft decision data. The soft decision data are input into locations within the matrix so that the matrix is filled in a row by row manner. The deinterieaved soft decision data 164 are individually output from locations within the matrix so that the matrix is emptied in a column by column manner. The deinterieaved soft decision data 164 are output by the deinterleaver 162 at the same rate that they were input (e.g., 28.8 kilometrics/second).
The predetermined size of the block of soft decision data defined by the matrix is derived from the maximum rate of sampling data samples from the spread-spectrum signal received within the predetermined length transmission block.
The deinterieaved soft decision data 164, are input to a decoder 166 which uses maximum likelihood decoding techniques to generate estimated traffic channel data bits 168. The maximum likelihood decoding techniques may be augmented by using an algorithm which is substantially similar to a Viterbi decoding algorithm. The decoder 166 uses a group of the individual soft decision data 164 to form a set of soft decision transition metrics for use at each particular time state of the maximum likelihood sequence estimation decoder 166. The number of soft decision data 164 in the group used to form each set of soft decision transition metrics corresponds to the number of data symbols 106 at the output of the convolutional encoder 104 generated from each input data bit 102. The number of soft decision transition metrics in each set is equal to two raised to the power of the number of soft decision data 164 in each group. For example, when a 1/3 convolutional encoder is used in the transmitter, three data symbols 106 are generated from each input data bit 102. Thus, decoder 166 uses groups of three individual soft decision data 164 to form eight soft decision transition metrics for use at each time state in the maximum likelihood sequence estimation decoder 166. The estimated data bits 168 are generated at a rate related to the rate that the soft decision data 164 are input to the decoder 166 and the fixed rate used to originally encode the input data bits 102 (e.g., if the soft decision data are input at 28.8 kilometrics/second and the original encoding rate was 1/3 then estimated data bits 168 are output at a rate of 9600 bits/second).
Thus, a communication system for coherently encoding and decoding has been described above with reference to FIG. 1. In summary, the communication system includes a first portion'which encodes input data bits into data symbols, interleaves the data symbols in a symbol by symbol manner, inserts reference bits into the interleaved symbols, modulates and transmits the reference-coded data symbols over a communication channel. The communication system further includes a second portion which receives and demodulates a signal from over the communication channel, estimates parameters of the communication channel, coherently demodulates data samples within received signal, deinterleaves the coherently detected data samples which are used as soft decision data within each received transmission block, subsequently generates soft decision transition metrics from the deinterieaved individual soft decision data, and subsequently generates estimated data bits from the soft decision metrics by using maximum likelihood decoding techniques.
To more clearly described the reasoning behind this method of using reference bits to coherently detect data samples and the operation of the channel estimator 134 as well as to facilitate further discussion, let us establish the following mathematical model. It will be appreciated by those skilled in the art that a fading channel can be modeled as a complex valued function of time t, denoted by h(t). The time interval of the convolutionally encoded- reference bits is denoted by T. The received signal after demodulation and despreading is then sampled at every T. Assuming that one reference bit is inserted for every 6 encoded bits, the samples corresponding to the reference bit appears at nTr = 7nT, n = .... -1 , 0, 1 , ..., where Tr = 7T is defined. Then, the noisy estimates may be written as:
h(nTr) = h(nTr) + z(nTr) (eq. 1)
where z(nTr) is the sampled additive noise. A better estimate than that shown in (eq. 1 ) can be obtained such that:
Figure imgf000017_0001
(eq- 2)-
For example N = 3 may be chosen. By doing so, an estimate is obtained for every reference bit interval Tr using 7 of the noisy estimates. To obtain the channel estimate at kT for k ≠ 7n which are needed for generating coherent detection information, inteφolation techniques can be used. The easiest inteφolation method is to use linear inteφolation. For example, assuming that k = 7n + i where 1 < i < 6, results in (eq. 2) being rewritten as:
h(kT) = -[(7-i)x h(7nT) + ixh(7nT+7T)] (eq- 3)-
= l{(7-i)x h(nTr) + i xh[(n-M)Tr]}
Other more sophisticated inteφolation techniques can be used to further improve the estimation. However, when the channel fading is slow relative to the sampling rate 1/Tr of the reference signal, the linear inteφolation method described above is sufficient.
It will be appreciated by those skilled in the art that the sampled channel response h(n) ≡ h(nTr) can be modeled as a slowly time- varying random process with a power spectrum Φ(f), and Φ(f) = 0 for f < -f and f>f where f is the Doppler frequency. If fd s not known or may change with time, the best estimate h(n) which can obtained is to pass the noisy estimate h(kTr) through an ideal low-pass linear-phase filter which rejects the noise components with frequency |f | > fd >max . The optimal filter would have a frequency response, i.e. the Fourier transform of wι denoted as:
Figure imgf000018_0001
One such filter is finite impulse response (FIR) filter which has an output which can be written as:
h(n) = h(nTr ) = ∑ wkh(nTr + kTr ) (eq. 5) k=-N
where WK is the FIR filter coefficients, or weights, for generating the estimate. It is easy to see that the (2N+1 ) sample average method described above is a specially case of this weighted sum method, if wk = 1/(2N + 1). By selecting W according to the criterion described above, a better estimate of h(n) can be obtained, although delay will be introduced. FIG. 3 illustrates how (eq. 5) may be implemented to generate a channel estimate using weighed average of noise channel estimated based on the reference signal.
It will be appreciated by those skilled in the art that the performance of an ideal coherent receiver over a Rayleigh fading channel is well known. Therefore, the following discussion will analyze the performance loss of the reference-based channel estimation method relative to the optimal coherent receiver over such a channel.
The loss is mainly caused by two factors. First, because of the insertion of non-information bearing reference bits, the energy per information bit (Eb) is effectively reduced (i.e., the data rate is reduced), when the total transmitted power remains the same. Second, in the presence of noise, there are errors in the channel estimates. The total loss is the combined result of these two factors. The loss in Eb due to reference insertion, denoted by ζj, can be simply expressed as:
ζi = (M+1)/M = 1 + 1/M (eq. 6)
where 1/M is the insertion rate. For example, for M = 6, a loss in E of 10log-ιo(7/6) = 0.67 dB occurs.
In order to analyze the performance loss due to estimation error, a channel and signaling model must first be established for the DS- CDMA up-link. A DS-CDMA up-link can be viewed as multiple flat fading channels. For each of the flat fading channels, the received signal after despreading can be expressed as:
r(k) = h(k)a(k) +z(k) (eq. 7)
where r(k) is the received sample at kT, a(k) is the corresponding transmitted data or reference symbol, h(k) is a low-pass random complex variable characterizing the fading channel, and z(k) is the additive noise or interference, which is approximately white and Gaussian. The average signal to noise ratio is equal to
E[|a(k)|2
Figure imgf000019_0001
is the noise variance. According to Jakes' channel model (as described in W. C. Jakes, Ed., Microwave Mobile Communications, John Wiley, New York, 1974), h(k) is unbiased and Gaussian distributed. Its power spectrum, called Doppler spectrum, is given by:
Figure imgf000019_0002
where fd is the Doppler frequency, which is a function of the carrier frequency and the mobile communication unit speed. It can be further assumed that BPSK signaling is used. It will be appreciated by those skilled in the art that the following assumptions also are applicable to quadrature phase shift keying signaling. Given that |a(k)| = 1 , then it may be assumed that the reference symbols are inserted at (M+1 )kT, so that a((M + 1)k) and r((M+1)k) are the reference symbols and the corresponding received samples, respectively. By multiplying r((M + 1)k) with the conjugate of the reference symbol a'((M + 1)k), the resulting channel estimate is:
h((M+1)k) = h((M+1)k) + a'((M+1)k)z((M+1)k). (eq. 9).
In the channel estimate given by (eq. 9), h((M+1)k), is a low-pass random variable and the second term is the channel estimation error. When 1/(M+1 )T > 2fd, the channel estimate at (M+1)kT can be further improved, i.e., the variance of the channel estimation error can be reduced. It is known from Wiener filtering theory that the optimal unbiased channel estimate, in the sense of maximizing the ratio of signal energy to the variance of estimation error, can be obtained by passing h((M+1)k) through a linear-phase filter whose magnitude response is equal to the square-root of the quotient of H(f) divided by the noise spectrum. The optimal channel estimator based on the inserted reference symbols is indeed a linear phase matched filter, which is matched to the channel Doppler spectrum divided by the noise spectrum. Practically, it is difficult to implement such an optimal estimator, because the Doppler and noise spectra are usually not known and will change with time. A sub-optimum and realistic solution is to use a fixed, linear-phase, low-pass filter, whose cut-off frequency is greater than or equal to the maximum possible Doppler frequency. By filtering h((M+1)k) using an ideal low-pass linear phase filter, whose cut-off frequency is fcut-off. with zero group delay, or equivalents a fixed group delay, and unit magnitude in its passband, the output at the filter can be expressed as:
h((M + 1)k) = h((M+1)k) + z((M+1)k) (eq. 10).
It can be shown that the variance of z((M+1)k) , the residual estimation error, is equal to σ2 x (2fcut_off / fr), where fr = 1/(M+1 )T is the reference symbol insertion frequency. More precisely, after filtering, the variance of the channel estimation error is reduced by a factor of 2fcut-off/fr-
Subsequently, by using linear inteφolation, the channel estimates at kT, for k ≠ (M+1 )k can be generated according to (eq. 3). From (eq. 7) and (eq. 10) the coherently detected samples can be written as:
a(n) = r(k)h-(k)
=|h(k)|2a(k)+z'(k)h(k)a(k)+z(k)h'(k)+z(k)z'(k)
If it is further assumed that z'(k)h(k)a(k) and z(k)h*(k) are independent and the high order error term z(k)z'(k) is negligible, then the total noise variance at the output of the detector is equal to | h(k)|22 + σ2 ). By comparing this result with the optimum coherent receiver for max-ratio combining, which has an noise variance of |h(k)|2 σ2 at the detector output, it may be concluded that the loss due to estimation error is approximately equal to:
ζβst « 1 + σ2z 2 = 1 + (2fCUI_off/fr) (eq. 12).
By combining (eq. 6) and (eq. 12), the total performance loss may be expressed as:
ζtota - [1 + (2f „^,/f r )] x (1 + 1/M) " (eq. 13).
The system performance may be optimized by selecting a proper M to minimize ζtotai-
For an r = 1/3 convolutionally coded system with information bit rate of 9600 bits per second, the coded bit rate is equal to 28800 bits per second. Letting M = 6, then fr = 4800 Hertz (Hz). For an fcut-of = 300 Hz, the total loss is (1+1/8)x(1+1/6) = 63/48 or about 1.14 dB. Since an optimal coherent receiver requires an Eb/N0 over 3 dB less than that required by a non-coherent receiver, a gain of over 2 dB can be expected. When diversity combining of signals from multiple RAKE fingers and/or multiple antennas is used, the difference in performance between the coherent receiver and non-coherent receiver could be even larger because the combining loss in a non-coherent receiver does not exist for a coherent receiver. Although this additional advantage may be partially canceled out due to the fact that, when diversity combining is used, the communication system is likely to be operated at lower signal-to-noise ratios for the individual signals to be combined than without diversity. As a result, the second order term in (eq. 11 ) can not be ignored. In the above analysis, it has been assumed that an ideal low- pass filter is used for channel estimation. Realization of such an ideal filter will require an infinite delay. A practical filter must have a transition band to have a finite delay. Thus, the allowable maximum Doppler frequency should be less than the effective bandwidth of the filter. For example, a filter may be designed which has a transition band from 200 Hertz to 400 Hertz. The resulting filter will have a delay less than five millisecond while keeping the effective bandwidth equal to 300 Hertz. By using such a filter, there is no additional loss if the mobile communication unit speed is less than 220 kilometers per hour. Furthermore in the above analysis, it was assumed that the data and reference symbols are transmitted continuously. As a result, the reference signals are available every Tr time interval and these reference signals can be used for channel estimation by means of low- pass filtering. In some cases, such as when variable rate speech transmission is used, it is desirable to transmit data in short and discontinuous blocks. In such a case, the referenced symbols are also transmitted discontinuously and the low pass filtering method described above should be modified to be applicable as described below.
First, it will be appreciated by those skilled in the art that when the duration of a data block is short relative to the time constant of channel variation, the channel response may be assumed to vary linearly during the time span of a block. Thus, the channel response h(kT) may be expressed as:
h(kT) = α + βk (eq. 14)
where α and β are two complex constants to be estimated. These two constants may be determined by using the received reference samples through linear best-fitting based on the least squares (LS) principle. The details of such estimation methods are illustrated by the following example. If a transmitted data block (i.e., frame) is assumed to consists of 36 data symbols and with 6 inserted reference symbols (see FIG. 2). As a result, 42 symbols are transmitted per data block. This data block may be separated by time intervals in which no data are transmitted. Thus, when such a short block is received, we only have 6 reference samples during the time interval of interest.
In this example, the channel estimation is performed by using only the received reference samples. The received samples may be denoted by r(k), k = 0 41 , which can be written as:
r(k) = h(kT)a(k)+z(k) (eq. 15)
where a(k) is the kth transmitted symbol, which can be either a data symbol (not known to the receiver) or a reference symbol (known to the receiver), and z(k) is the additive noise at k. In this example, for a reference sample r(k), k=7i+3, i = 0, 1 , 2, 3, 4, and 5, since a(k) is known, a noisy channel estimate can be obtained as:
h(kT) = r(k)a'(k) (eq. 16)
where a*(k) represents the complex conjugate of a(k). By minimizing the LS error between h(kT) given by (eq. 14) and h(kT), the LS estimates of α and β may satisfy the following:
αN + β∑k = ∑h(k) (eq- 17) k k α∑k + β∑k2 = ∑kh(k) (eq. 18)
where N is the number of elements in the summation and h(kT) is given by (eq. 16) and the summation index k takes the value k = 3+7i, i = 0, 1 , .... 5. The solution of α and β is given by:
α = kh(k) (eq. 19)
Figure imgf000023_0001
β = d N∑h(k)-∑k x ∑h(k) (eq. 20) where,
d = l/ N∑k2 - ∑k (eq. 21).
/ [ k J J
Thus, the estimates channel responses at time kT, k = 0, 1 41 can be computed according to (eq. 14) using the estimated α and β.
Although the invention has been described and illustrated with a certain degree of particularity, it is understood that the present disclosure of embodiments has been made by way of example only and that numerous changes in the arrangement and combination of parts as well as steps may be resorted to by those skilled in the art without departing from the spirit and scope of the invention as claimed. For example, the modulator, antennas and demodulator portions of the preferred embodiment communication system as described were directed to CDMA spread-spectrum signals transmitted over a radio communication channel. However, as will be understood by those skilled in the art, the encoding and decoding techniques described and claimed herein can also be adapted for use in other types of transmission systems like those based on time division multiple access (TDMA) and frequency division multiple access (FDMA). In addition the communication channel could alternatively be an electronic data bus, wireline, optical fiber link, satellite link, or any other type of communication channel.

Claims

ClaimsWhat is claimed is:
1. A communication unit comprising:
(a) reference means for inserting reference symbols into a stream of input data symbols to form a reference coded stream of input data symbols; and
(b) spreading means, operatively coupled to the reference means, for preparing the reference coded stream of input data symbols for transmission over a communication channel by spreading the reference coded stream of input data symbols with a spreading code prior to transmission over the communication channel.
2. The communication unit of claim 1 wherein the spreading means comprises first spreading means for spreading the reference symbols at a first rate of spreading and second spreading means for spreading the stream of input data symbols at a second rate of spreading.
3. A communication unit comprising:
(a) a demodulator adapted for despreading a received communication signal with a spreading code to derive a stream of reference samples and a stream of data samples;
(b) a channel estimator, operatively coupled to the demodulator, and adapted for estimating the channel response by utilizing the stream of reference samples; and (c) a detector, operatively coupled to the demodulator and the channel estimator, and adapted for generating an estimated data symbol from the stream of data samples by utilizing the estimated channel response.
4. The communication unit of claim 3 wherein the demodulator comprises a first despreader adapted for despreading the received communication signal with one of a first despreading code and a first rate of despreading, respectively, to derive the stream of reference samples, and a second despreader adapted for despreading the received communication signal with one of a second despreading code and a second rate of despreading, respectively, to derive the stream of data samples.
5. The communication unit of claim 3 wherein the channel estimator comprises one of the group consisting of:
(a) means for estimating the channel response by low-pass filtering the stream of reference samples;
(b) means for estimating the channel response as a linear function of sampling time; and
(c) filtering means for generating an estimate of the channel response associated with each reference sample by low- pass filtering the stream of reference samples, and inteφolating means, operatively coupled to the filtering means, for generating an estimated channel response between at least two of the reference sample estimated channel responses.
6. The communication unit of claim 3 wherein the detector comprises one of the group consisting of:
(a) means for generating the estimated data symbol from the stream of data samples by correlating the estimated channel response with the stream of data samples;
(b) means for generating an estimated data bit by utilizing maximum likelihood decoding techniques to derive the estimated data bit from the estimated data symbol.
(c) means for generating an estimated data bit by utilizing a Viterbi maximum likelihood decoding algorithm to derive the estimated data bit from the estimated data symbol.
7. A method of communication comprising:
(a) inserting reference symbols into a stream of input data symbols to form a reference coded stream of input data symbols; (b) preparing the reference coded stream of input data symbols for transmission over a communication channel by spreading the reference coded stream of input data symbols with a spreading code prior to transmission over the communication channel; and (c) transmitting the spread reference coded stream of input data symbols over the communication channel.
8. The method of claim 7 wherein the step of inserting comprises inserting reference symbols into a stream of input data symbols according to an insertion algorithm to form a reference coded stream of input data symbols, the insertion algorithm comprising inserting reference symbols at a rate greater than twice of channel variation frequency of a communication channel over which the spread reference coded stream of input data symbols is to be transmitted.
9. A method of processing a received communication signal comprising:
(a) despreading the received communication signal with a spreading code to derive a stream of reference samples and a stream of data samples;
(b) estimating the channel response by utilizing the stream of reference samples; and
(c) generating an estimated data symbol from the stream of data samples by utilizing the estimated channel response.
10. The method of claim 39 wherein the estimating step comprises: (a) generating an estimate of the channel response associated with each reference sample by low-pass filtering the stream of reference samples; and (b) generating an estimated channel response between at least two of the reference sample estimated channel responses.
PCT/US1994/001746 1993-03-11 1994-02-16 Method and apparatus for coherent communication in a spread-spectrum communication system WO1994021065A1 (en)

Priority Applications (8)

Application Number Priority Date Filing Date Title
BR9404420A BR9404420A (en) 1993-03-11 1994-02-16 Communication process unit and received communication signal processing method
CA002134230A CA2134230C (en) 1993-03-11 1994-02-16 Method and apparatus for coherent communication in a spread-spectrum communication system
PL94306002A PL174713B1 (en) 1993-03-11 1994-02-16 Method of and apparatus for ensuring coherent communication in a spectrumdistibuted communication system
EP94913263A EP0643889B1 (en) 1993-03-11 1994-02-16 Method and apparatus for coherent communication in a spread-spectrum communication system
DE69430720T DE69430720T2 (en) 1993-03-11 1994-02-16 METHOD AND DEVICE FOR COHERENT COMMUNICATION IN A SPREADING SPECTRUM COMMUNICATION SYSTEM
JP52000694A JP3464002B2 (en) 1993-03-11 1994-02-16 Coherent communication method and apparatus in spread spectrum communication system
SE9403860A SE520542C2 (en) 1993-03-11 1994-11-10 Method and apparatus for coherent communication in a spread-spectrum system
FI945336A FI112010B (en) 1993-03-11 1994-11-11 A method and apparatus for performing coherent communication in a spread spectrum communication system

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US08/031,258 1993-03-11
US08/031,258 US5329547A (en) 1993-03-11 1993-03-11 Method and apparatus for coherent communication in a spread-spectrum communication system

Publications (1)

Publication Number Publication Date
WO1994021065A1 true WO1994021065A1 (en) 1994-09-15

Family

ID=21858459

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US1994/001746 WO1994021065A1 (en) 1993-03-11 1994-02-16 Method and apparatus for coherent communication in a spread-spectrum communication system

Country Status (14)

Country Link
US (1) US5329547A (en)
EP (1) EP0643889B1 (en)
JP (1) JP3464002B2 (en)
CN (1) CN1048606C (en)
BR (1) BR9404420A (en)
CA (1) CA2134230C (en)
DE (1) DE69430720T2 (en)
FI (1) FI112010B (en)
MY (1) MY125586A (en)
PL (1) PL174713B1 (en)
SE (1) SE520542C2 (en)
SG (1) SG46295A1 (en)
TW (1) TW295754B (en)
WO (1) WO1994021065A1 (en)

Families Citing this family (106)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5103459B1 (en) * 1990-06-25 1999-07-06 Qualcomm Inc System and method for generating signal waveforms in a cdma cellular telephone system
US6693951B1 (en) * 1990-06-25 2004-02-17 Qualcomm Incorporated System and method for generating signal waveforms in a CDMA cellular telephone system
US5506864A (en) * 1990-12-05 1996-04-09 Interdigital Technology Corporation CDMA communications and geolocation system and method
US7020125B2 (en) * 1990-12-05 2006-03-28 Interdigital Technology Corporation Broadband CDMA overlay system and method
JPH0754991B2 (en) * 1993-01-21 1995-06-07 日本電気株式会社 Digital mobile radio communication system
WO1994028640A1 (en) * 1993-06-02 1994-12-08 Roke Manor Research Limited Rake receiver combining all the useful multipath components of a spread spectrum signal
US5446757A (en) * 1993-06-14 1995-08-29 Chang; Chen-Yi Code-division-multiple-access-system based on M-ary pulse-position modulated direct-sequence
US5412686A (en) * 1993-09-17 1995-05-02 Motorola Inc. Method and apparatus for power estimation in a communication system
GB2282300B (en) * 1993-09-22 1997-10-22 Northern Telecom Ltd Communications system and receiver devices therefor
US5446727A (en) * 1993-11-30 1995-08-29 Motorola Inc. Method and apparatus for time aligning signals for reception in a code-division multiple access communication system
US5418813A (en) * 1993-12-06 1995-05-23 Motorola, Inc. Method and apparatus for creating a composite waveform
US5490148A (en) * 1993-12-15 1996-02-06 Motorola, Inc. Bit error rate estimator
FI94579C (en) * 1994-01-12 1995-09-25 Nokia Mobile Phones Ltd Data Transfer method
US5768684A (en) * 1994-03-04 1998-06-16 Motorola, Inc. Method and apparatus for bi-directional power control in a digital communication system
JP3202125B2 (en) * 1994-03-10 2001-08-27 沖電気工業株式会社 Code division multiple access system
US5497395A (en) * 1994-04-04 1996-03-05 Qualcomm Incorporated Method and apparatus for modulating signal waveforms in a CDMA communication system
CA2145566C (en) * 1994-04-29 1999-12-28 Nambirajan Seshadri Methods of and devices for enhancing communications that use spread spectrum technology
US5544156A (en) * 1994-04-29 1996-08-06 Telefonaktiebolaget Lm Ericsson Direct sequence CDMA coherent uplink detector
US5751739A (en) * 1994-04-29 1998-05-12 Lucent Technologies, Inc. Methods of and devices for enhancing communications that use spread spectrum technology
US5519779A (en) * 1994-08-05 1996-05-21 Motorola, Inc. Method and apparatus for inserting signaling in a communication system
US5559828A (en) * 1994-05-16 1996-09-24 Armstrong; John T. Transmitted reference spread spectrum communication using a single carrier with two mutually orthogonal modulated basis vectors
EP0715440B1 (en) * 1994-06-22 2004-06-16 NTT DoCoMo, Inc. Synchronous detector and synchronizing method for digital communication receiver
CN1065093C (en) * 1994-06-23 2001-04-25 Ntt移动通信网株式会社 CDMA demodulation circuit and demodulating method
US5619524A (en) * 1994-10-04 1997-04-08 Motorola, Inc. Method and apparatus for coherent communication reception in a spread-spectrum communication system
US5659573A (en) * 1994-10-04 1997-08-19 Motorola, Inc. Method and apparatus for coherent reception in a spread-spectrum receiver
US5822359A (en) * 1994-10-17 1998-10-13 Motorola, Inc. Coherent random access channel in a spread-spectrum communication system and method
FI97180C (en) * 1994-11-03 1996-10-25 Nokia Mobile Phones Ltd Method for channel estimation and receiver
US5623485A (en) * 1995-02-21 1997-04-22 Lucent Technologies Inc. Dual mode code division multiple access communication system and method
US5640431A (en) * 1995-03-10 1997-06-17 Motorola, Inc. Method and apparatus for offset frequency estimation for a coherent receiver
US5498512A (en) * 1995-03-10 1996-03-12 Eastman Kodak Company Photographic element having a transparent magnetic recording layer
US7072380B2 (en) 1995-06-30 2006-07-04 Interdigital Technology Corporation Apparatus for initial power control for spread-spectrum communications
US6885652B1 (en) 1995-06-30 2005-04-26 Interdigital Technology Corporation Code division multiple access (CDMA) communication system
US7020111B2 (en) 1996-06-27 2006-03-28 Interdigital Technology Corporation System for using rapid acquisition spreading codes for spread-spectrum communications
ZA965340B (en) 1995-06-30 1997-01-27 Interdigital Tech Corp Code division multiple access (cdma) communication system
US7929498B2 (en) 1995-06-30 2011-04-19 Interdigital Technology Corporation Adaptive forward power control and adaptive reverse power control for spread-spectrum communications
US5677930A (en) * 1995-07-19 1997-10-14 Ericsson Inc. Method and apparatus for spread spectrum channel estimation
US6018651A (en) * 1995-11-29 2000-01-25 Motorola, Inc. Radio subscriber unit having a switched antenna diversity apparatus and method therefor
JP3214860B2 (en) * 1996-03-05 2001-10-02 株式会社エヌ・ティ・ティ・ドコモ Signal transmission method, transmitter, receiver and spread code synchronization method in mobile communication system
JP2934185B2 (en) 1996-03-15 1999-08-16 松下電器産業株式会社 CDMA cellular radio base station apparatus, mobile station apparatus, and transmission method
US5737327A (en) * 1996-03-29 1998-04-07 Motorola, Inc. Method and apparatus for demodulation and power control bit detection in a spread spectrum communication system
FR2747870B1 (en) * 1996-04-19 1998-11-06 Wavecom Sa DIGITAL SIGNAL WITH MULTIPLE REFERENCE BLOCKS FOR CHANNEL ESTIMATION, CHANNEL ESTIMATION METHODS AND CORRESPONDING RECEIVERS
US6396804B2 (en) * 1996-05-28 2002-05-28 Qualcomm Incorporated High data rate CDMA wireless communication system
US5930230A (en) * 1996-05-28 1999-07-27 Qualcomm Incorporated High data rate CDMA wireless communication system
US5926500A (en) * 1996-05-28 1999-07-20 Qualcomm Incorporated Reduced peak-to-average transmit power high data rate CDMA wireless communication system
US6678311B2 (en) 1996-05-28 2004-01-13 Qualcomm Incorporated High data CDMA wireless communication system using variable sized channel codes
US5784366A (en) * 1996-08-27 1998-07-21 Transsky Corp. Wideband code-division-multiple access system and method
US5757846A (en) * 1996-08-30 1998-05-26 Vasudevan; Subramanian CDMA communication system and method with dual-mode receiver
JP3796870B2 (en) * 1997-01-21 2006-07-12 ソニー株式会社 Receiving device, receiving method, and terminal device of mobile phone system
US6360079B2 (en) * 1997-02-12 2002-03-19 Interdigital Technology Corporation Global channel power control to minimize spillover in a wireless communication environment
US7046682B2 (en) 1997-02-12 2006-05-16 Elster Electricity, Llc. Network-enabled, extensible metering system
US6072785A (en) * 1997-03-04 2000-06-06 At&T Corp Differential PSK signalling in CDMA networks
US6094428A (en) * 1997-04-30 2000-07-25 Motorola, Inc. Method and apparatus for transmission and reception of a transmission rate in a CDMA communication system
DE69838133T4 (en) * 1997-05-14 2008-04-17 Qualcomm, Inc., San Diego PARTICIPANT WITH MULTIPLE CONTROL AND INFORMATION DATA FOR CDMA WIRELESS COMMUNICATION SYSTEM
US6021309A (en) * 1997-05-22 2000-02-01 Globalstar L.P. Channel frequency allocation for multiple-satellite communication network
US6088659A (en) * 1997-09-11 2000-07-11 Abb Power T&D Company Inc. Automated meter reading system
US20020051434A1 (en) * 1997-10-23 2002-05-02 Ozluturk Fatih M. Method for using rapid acquisition spreading codes for spread-spectrum communications
US6408019B1 (en) 1997-12-29 2002-06-18 Georgia Tech Research Corporation System and method for communication using noise
US6208632B1 (en) 1998-01-29 2001-03-27 Sharp Laboratories Of America System and method for CDMA channel estimation
US6292912B1 (en) * 1998-02-27 2001-09-18 Western Digital Technologies, Inc. Disk drive having built-in self-test system for characterizing performance of the drive
US6085104A (en) * 1998-03-25 2000-07-04 Sharp Laboratories Of America, Inc. Pilot aided, time-varying finite impulse response, adaptive channel matching receiving system and method
US6091760A (en) * 1998-06-29 2000-07-18 L-3 Communications Corporation Non-recursively generated orthogonal PN codes for variable rate CDMA
US6724741B1 (en) 1998-06-29 2004-04-20 L-3 Communications Corporation PN code selection for synchronous CDMA
DE69824898T2 (en) * 1998-07-21 2005-06-30 Nokia Corp. ESTIMATE THE CHANNEL IMPULSE RESPONSE BY MUTING THE RECEIVED SIGNAL
GB2340352B (en) * 1998-07-31 2003-05-07 Roke Manor Research Sampling means for use with rake receiver
US6643338B1 (en) 1998-10-07 2003-11-04 Texas Instruments Incorporated Space time block coded transmit antenna diversity for WCDMA
US6700902B1 (en) 1998-10-19 2004-03-02 Elster Electricity, Llc Method and system for improving wireless data packet delivery
US6128330A (en) 1998-11-24 2000-10-03 Linex Technology, Inc. Efficient shadow reduction antenna system for spread spectrum
KR100388980B1 (en) 1998-11-26 2003-10-10 엘지정보통신주식회사 Data transferring system and method for cdma mobile communication system
US6526103B1 (en) * 1998-12-23 2003-02-25 Nortel Networks Limited Multi-stage receiver
US6587517B1 (en) * 1998-12-23 2003-07-01 Nortel Networks Limited Multi-stage receiver
US6721349B1 (en) 1999-01-28 2004-04-13 Qualcomm Incorporated Method and apparatus for reducing peak-to-average ratio in a CDMA communication system
US6978015B1 (en) 1999-11-11 2005-12-20 Tokyo Electron Limited Method and apparatus for cooperative diagnosis of impairments and mitigation of disturbers in communication systems
US6970560B1 (en) 1999-11-11 2005-11-29 Tokyo Electron Limited Method and apparatus for impairment diagnosis in communication systems
WO2001035614A1 (en) 1999-11-11 2001-05-17 Voyan Technology Method and apparatus for the prediction and optimization in impaired communication systems
US6970415B1 (en) 1999-11-11 2005-11-29 Tokyo Electron Limited Method and apparatus for characterization of disturbers in communication systems
US6870901B1 (en) 1999-11-11 2005-03-22 Tokyo Electron Limited Design and architecture of an impairment diagnosis system for use in communications systems
US6463279B1 (en) * 1999-11-17 2002-10-08 Globalstar L.P. Channel frequency allocation for multiple-satellite communication network
AR031539A1 (en) 1999-12-01 2003-09-24 Ericsson Telefon Ab L M METHOD AND APPLIANCE TO ESTIMATE THE QUALITY OF LINK IN A RADIOTELECOMMUNICATIONS SYSTEM
US6301291B1 (en) 2000-02-03 2001-10-09 Tantivy Communications, Inc. Pilot symbol assisted modulation and demodulation in wireless communication systems
US6801564B2 (en) * 2000-02-23 2004-10-05 Ipr Licensing, Inc. Reverse link correlation filter in wireless communication systems
US6542559B1 (en) * 2000-05-15 2003-04-01 Qualcomm, Incorporated Decoding method and apparatus
JP3464645B2 (en) * 2000-08-30 2003-11-10 松下電器産業株式会社 Wireless receiver
US6977974B1 (en) 2000-11-20 2005-12-20 At&T Corp. De-modulation of MOK(M-ary orthogonal modulation)
US7580488B2 (en) * 2000-11-29 2009-08-25 The Penn State Research Foundation Broadband modulation/demodulation apparatus and a method thereof
US7697594B2 (en) * 2001-03-30 2010-04-13 Texas Instruments Incorporated Method and apparatus for regenerative based interference cancellation within a communication system
CN1110163C (en) * 2001-04-16 2003-05-28 华为技术有限公司 Estimating method for flat fading channel in CDMA communication system and its device
US7088955B2 (en) * 2001-07-16 2006-08-08 Qualcomm Inc. Method and apparatus for acquiring and tracking pilots in a CDMA communication system
GB0120535D0 (en) * 2001-08-23 2001-10-17 Roke Manor Research Space-time interleaving transmit diversity
US7116957B2 (en) * 2001-10-22 2006-10-03 Qualcomm Incorporated Velocity responsive filtering for pilot signal reception
US6867707B1 (en) 2002-04-24 2005-03-15 Elster Electricity, Llc Automated on-site meter registration confirmation using a portable, wireless computing device
US20040165683A1 (en) * 2002-09-04 2004-08-26 Gupta Alok Kumar Channel estimation for communication systems
US7161973B2 (en) * 2002-12-17 2007-01-09 Sbc Properties, L.P. Pilot aided adaptive minimum mean square interference cancellation and detection
TW200428839A (en) * 2003-02-20 2004-12-16 Matsushita Electric Ind Co Ltd Frame synchronization method
JP4470377B2 (en) * 2003-02-28 2010-06-02 株式会社日立製作所 Propagation path estimation method in mobile communication system
US7742430B2 (en) 2004-09-24 2010-06-22 Elster Electricity, Llc System for automated management of spontaneous node migration in a distributed fixed wireless network
US7702594B2 (en) 2004-09-24 2010-04-20 Elster Electricity, Llc System and method for automated configuration of meters
US7352795B2 (en) * 2005-05-04 2008-04-01 Harris Corporation System and method for communicating data using constant amplitude waveform with hybrid orthogonal and MSK or GMSK modulation
EP1746756B1 (en) * 2005-07-21 2013-01-16 STMicroelectronics Srl A method and system for decoding signals, corresponding receiver and computer program product
US7310391B2 (en) * 2005-08-12 2007-12-18 At&T Corp. De-modulation of MOK(M-ary orthogonal modulation)
US8073384B2 (en) 2006-12-14 2011-12-06 Elster Electricity, Llc Optimization of redundancy and throughput in an automated meter data collection system using a wireless network
US8320302B2 (en) 2007-04-20 2012-11-27 Elster Electricity, Llc Over the air microcontroller flash memory updates
WO2009082761A1 (en) 2007-12-26 2009-07-02 Elster Electricity, Llc. Optimized data collection in a wireless fixed network metering system
US8077770B2 (en) * 2008-05-20 2011-12-13 Panasonic Corporation Methods and apparatus for reducing modulation signal bandwidth in polar modulation transmitters
US8525692B2 (en) 2008-06-13 2013-09-03 Elster Solutions, Llc Techniques for limiting demand from an electricity meter with an installed relay
US8203463B2 (en) 2009-02-13 2012-06-19 Elster Electricity Llc Wakeup and interrogation of meter-reading devices using licensed narrowband and unlicensed wideband radio communication
US9429639B2 (en) 2012-05-01 2016-08-30 Ohio University Terrestrial position and timing system

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4559633A (en) * 1982-10-22 1985-12-17 Hitachi, Ltd. Spread spectrum system
US4730340A (en) * 1980-10-31 1988-03-08 Harris Corp. Programmable time invariant coherent spread symbol correlator
US5029184A (en) * 1990-01-24 1991-07-02 Harris Corporation Low probability of intercept communication system
US5181225A (en) * 1990-11-22 1993-01-19 Ascom Tech. Ag. Receiver for a dsss signal
US5214669A (en) * 1989-10-12 1993-05-25 Agence Spatiale Europeenne Code acquisition process and circuit for a spread-spectrum signal

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US509204A (en) * 1893-11-21 Propeller
US4365338A (en) * 1980-06-27 1982-12-21 Harris Corporation Technique for high rate digital transmission over a dynamic dispersive channel
DE3403715A1 (en) * 1984-02-03 1985-08-08 Licentia Patent-Verwaltungs-Gmbh, 6000 Frankfurt DIGITAL CELL RADIO SYSTEM WITH TIME MULTIPLEX
US4901307A (en) * 1986-10-17 1990-02-13 Qualcomm, Inc. Spread spectrum multiple access communication system using satellite or terrestrial repeaters
US4811357A (en) * 1988-01-04 1989-03-07 Paradyne Corporation Secondary channel for digital modems using spread spectrum subliminal induced modulation
CH676179A5 (en) * 1988-09-29 1990-12-14 Ascom Zelcom Ag
US5101501A (en) * 1989-11-07 1992-03-31 Qualcomm Incorporated Method and system for providing a soft handoff in communications in a cdma cellular telephone system
US5109390A (en) * 1989-11-07 1992-04-28 Qualcomm Incorporated Diversity receiver in a cdma cellular telephone system
US5056109A (en) * 1989-11-07 1991-10-08 Qualcomm, Inc. Method and apparatus for controlling transmission power in a cdma cellular mobile telephone system
US5103459B1 (en) * 1990-06-25 1999-07-06 Qualcomm Inc System and method for generating signal waveforms in a cdma cellular telephone system
US5107225A (en) * 1990-11-30 1992-04-21 Qualcomm Incorporated High dynamic range closed loop automatic gain control circuit

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4730340A (en) * 1980-10-31 1988-03-08 Harris Corp. Programmable time invariant coherent spread symbol correlator
US4559633A (en) * 1982-10-22 1985-12-17 Hitachi, Ltd. Spread spectrum system
US5214669A (en) * 1989-10-12 1993-05-25 Agence Spatiale Europeenne Code acquisition process and circuit for a spread-spectrum signal
US5029184A (en) * 1990-01-24 1991-07-02 Harris Corporation Low probability of intercept communication system
US5181225A (en) * 1990-11-22 1993-01-19 Ascom Tech. Ag. Receiver for a dsss signal

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP0643889A4 *

Also Published As

Publication number Publication date
PL174713B1 (en) 1998-09-30
JPH07506713A (en) 1995-07-20
JP3464002B2 (en) 2003-11-05
SE9403860D0 (en) 1994-11-10
EP0643889A4 (en) 1997-12-10
PL306002A1 (en) 1995-02-20
SE9403860L (en) 1994-12-27
US5329547A (en) 1994-07-12
FI945336A (en) 1994-11-11
DE69430720T2 (en) 2002-12-05
CA2134230A1 (en) 1994-09-15
FI112010B (en) 2003-10-15
BR9404420A (en) 1999-06-15
MY125586A (en) 2006-08-30
EP0643889B1 (en) 2002-06-05
TW295754B (en) 1997-01-11
EP0643889A1 (en) 1995-03-22
SE520542C2 (en) 2003-07-22
CN1105510A (en) 1995-07-19
DE69430720D1 (en) 2002-07-11
CA2134230C (en) 1999-09-21
FI945336A0 (en) 1994-11-11
CN1048606C (en) 2000-01-19
SG46295A1 (en) 1998-02-20

Similar Documents

Publication Publication Date Title
EP0643889B1 (en) Method and apparatus for coherent communication in a spread-spectrum communication system
Ling Coherent detection with reference-symbol based channel estimation for direct sequence CDMA uplink communications
EP0732022B1 (en) Method and apparatus for coherent communication reception in a spread-spectrum communication system
US5659573A (en) Method and apparatus for coherent reception in a spread-spectrum receiver
AU676973B2 (en) Decoder for a non-coherently demodulated signal
Fazel et al. A flexible and high performance cellular mobile communications system based on orthogonal multi-carrier SSMA
US5412686A (en) Method and apparatus for power estimation in a communication system
US7035316B2 (en) Method and apparatus for adaptive linear equalization for Walsh covered modulation
US5822359A (en) Coherent random access channel in a spread-spectrum communication system and method
US7042929B2 (en) Scaling using gain factors for use in data detection for wireless code division multiple access communication systems
EP0944977B1 (en) Method and apparatus for digital symbol detection using transmission medium response estimates
US6868112B2 (en) Apparatus and method for detecting signals of space-time coding based on transmission diversity
MXPA98000853A (en) Des-extendedor adapta
EP1378067A2 (en) Adaptive chip equalizers for synchronous ds-cdma system with pilot sequences
US7817709B2 (en) Non-coherent phase differential and multiple orthogonal signal reception
Arslan et al. Iterative co-channel interference cancellation in narrowband mobile radio systems
Fazel Performance of convolutionally coded CDMA/OFDM in a frequency-time selective fading channel and its near-far resistance
Pu et al. Transmission and reception of TDD multicarrier CDMA signals in mobile communications system
BRIEF Rayleigh Fading Channels in Mobile igital Co

Legal Events

Date Code Title Description
AK Designated states

Kind code of ref document: A1

Designated state(s): BR CA CN FI JP KR PL SE

AL Designated countries for regional patents

Kind code of ref document: A1

Designated state(s): AT BE CH DE DK ES FR GB GR IE IT LU MC NL PT SE

WWE Wipo information: entry into national phase

Ref document number: 2134230

Country of ref document: CA

WWE Wipo information: entry into national phase

Ref document number: 94038601

Country of ref document: SE

WWE Wipo information: entry into national phase

Ref document number: 945336

Country of ref document: FI

WWE Wipo information: entry into national phase

Ref document number: 1994913263

Country of ref document: EP

121 Ep: the epo has been informed by wipo that ep was designated in this application
WWP Wipo information: published in national office

Ref document number: 94038601

Country of ref document: SE

WWP Wipo information: published in national office

Ref document number: 1994913263

Country of ref document: EP

EX32 Extension under rule 32 effected after completion of technical preparation for international publication

Free format text: GE

WWG Wipo information: grant in national office

Ref document number: 1994913263

Country of ref document: EP

WWG Wipo information: grant in national office

Ref document number: 945336

Country of ref document: FI