CA2201460C - Joint detector for multiple coded digital signals - Google Patents
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- CA2201460C CA2201460C CA002201460A CA2201460A CA2201460C CA 2201460 C CA2201460 C CA 2201460C CA 002201460 A CA002201460 A CA 002201460A CA 2201460 A CA2201460 A CA 2201460A CA 2201460 C CA2201460 C CA 2201460C
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M13/00—Coding, 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
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/22—Arrangements for detecting or preventing errors in the information received using redundant apparatus to increase reliability
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L5/00—Arrangements affording multiple use of the transmission path
- H04L5/02—Channels characterised by the type of signal
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Abstract
A method for the joint detection of multiple coded digital signals that share the same transmission medium in a manner that causes mutual interference. The method is comprised of two steps that are applied to preliminary estimates of each digital signal, one or more times. The first step is to obtain reliability estimates for each data element of each digital signal by combining the preliminary estimates, a statistical model for the interference, and any a priori information regarding the data elements. The second step is to revise these reliability estimates for each digital signal based on the forward error correction code used for that digital signal. When the steps are repeated, the revised reliability estimates from the second step are used as a priori information for the first step.
Description
Joint Detector for Multiple Coded Digital Signals Field of Invention This invention relates to the joint detection of a multiple digital signals that are forward error correction coded and share the same transmission medium in a manner that causes mutual interference, More specifically, the present invention relates to a novel method for detection that allows the permissible interference to be increased and bandwidth to be conserved.
Background of the Invention In order to maximize the number of signals that can share a transmission medium, the frequency spectrum is re-used in a variety of ways. The traditional approach is to physically isolate communications signals of the same frequency in order to reduce their mutual interference to acceptable levels. Less traditional approaches use spread spectrum techniques to average the effects of interference over a bandwidth significantly greater than the information bandwidth. In both of these cases, interference will exist to some extent and, in some cases, can significantly reduce the system capacity, i.e., the informationlunit time/unit bandwidth.
To increase the capacity, joint detection schemes have been proposed that take into account the effect of the interference between the different signals and perform interference cancellation. Examples of such schemes are found in S.Verdu, "Minimum probability of error for asynchronous Gaussian multiple-access channels," IEEE Trans. Inf.~ Th., vol. 32, No. 1, pp.85-96, January 1986.
R.Lupas and S.Verdu, "Linear multiuser detectors for synchronous code-division multiple-access channels," IEEE Trans. Inf. Th., vol. 35, No.l, pp.123-136, January 1989;
Doc. No. 18-9CA
';~
R.Lupas and S.Verdu, "Near-far resistance of multiuser detectors in asynchronous channels," IEEE Trans. Comm. , vol. 38, No.4, pp.496-508, April 1990;
M.K.Varanasi and B.Aazhang, "Multistage detection in asynchronous code-division multiple access communications," IEEE Trans. Comm. , vol. 38, No.4, pp.509-519, Apri11990;
D.L.Ayerst et al, U.S. Patent No.: 5323418, 1994;
D.L.Schilling et al, U.S.Patent No.: 5553062, 1996;
and include techniques such as applying linear transformations to the received samples to decorrelate the interference, and techniques such as estimating the strongest user 1o first, subtracting it from the received signal and repeating it for the next strongest signal, etc. These techniques work well if the interference does not overwhelm the desired signal at any stage in the processing. Because of the latter constraint, these techniques have generally only been considered for spread spectrum signals.
The aforementioned joint detection schemes do not take into account any forward error IS correction coding of the signals.
To achieve the theoretically optimum capacity when multiple signals share the same transmission medium requires the use of forward error correction coding as is described by T.M.Cover and J.A.Thomas, in Elements of Information Theory, New 2o York: Wiley, 1991. Pedagogical techniques for achieving the theoretical capacity suggest applying a different code to each user at the transmitter and, at the receiver, estimating the digital signal with the largest signal to noise ratio (or the strongest code), subtracting its effect, and then repeating for the next digital signal; very similar to the techniques which have been proposed for uncoded systems. These techniques require 25 powerful codes that do not lead to a practical implementation. Such a technique, that is "almost practical", has been presented in the literature, for example by A.J.Viterbi, in a paper entitled " Very low rate convolutional codes for maximum theoretical performance of spread-spectrum multiple-access channels" , IEEE J. Sel. Areas Comm. , Doc. No. 18-9CA
vol. 8, no.4, pp.641-649, May 1990, but it has the drawback that it treats the digital signals asymmetrically and requires some co-ordination between transmitters.
An alternative approach to joint detection of multiple coded digital signals that is known to be optimum in a maximum likelihood sense for certain types of forward error s correction codes, is described by T.R.Giallorenzi and S.G.Wilson, in a paper entitled "Multiuser ML sequence estimator for convolutional coded asynchronous DS-CDMA
systems," IEEE Trans. Comm. , vol. 44, No. 8, pp.997-1008, August 1996.
This latter technique is a Viterbi-like algorithm that has a complexity, which is exponential in both the code memory and the number of digital signals, making it to impractical for implementation. There are other approaches to the joint detection of multiple coded signals that are obvious to those practicing the art. These include approaches such as cascading a joint detector for multiple uncoded signals with standard decoding algorithm. These approaches however, are fundamentally limited by the performance of the joint detector for multiple uncoded signals.
Examples of schemes related to and for obtaining reliability estimates from the preliminary estimates are found in H.L.van Trees, Detection, Estimation and Modulation Theory: Part I, New York: Wiley, 1968.
Examples of schemes related to soft-output decoding are found in 2o L.R.Bahl et al, "Optimal decoding of linear codes for minimizing symbol error rate,"
IEEE Trans. Inf. Th. , vo1.20, pp284-287, March 1974;
G.Battail, "Coding for the Gaussian channel: the promise of weighted output decoding," Int.J.Sat.Comm., vol.7, pp.183-192, 1989.
J.Hagenauer and P.Hoeher, "A Viterbi algorithm with soft decision outputs and its applications," Proc. IEEE Globecom, pp.47.1.1-47.1.7, November 1989;
P.Robertson et al, "A comparison of optimal and suboptimal MAP decoding algorithms operating in the log domain," Proc. ICC, pp.1009-1013, Seattle, June 1995.
Background of the Invention In order to maximize the number of signals that can share a transmission medium, the frequency spectrum is re-used in a variety of ways. The traditional approach is to physically isolate communications signals of the same frequency in order to reduce their mutual interference to acceptable levels. Less traditional approaches use spread spectrum techniques to average the effects of interference over a bandwidth significantly greater than the information bandwidth. In both of these cases, interference will exist to some extent and, in some cases, can significantly reduce the system capacity, i.e., the informationlunit time/unit bandwidth.
To increase the capacity, joint detection schemes have been proposed that take into account the effect of the interference between the different signals and perform interference cancellation. Examples of such schemes are found in S.Verdu, "Minimum probability of error for asynchronous Gaussian multiple-access channels," IEEE Trans. Inf.~ Th., vol. 32, No. 1, pp.85-96, January 1986.
R.Lupas and S.Verdu, "Linear multiuser detectors for synchronous code-division multiple-access channels," IEEE Trans. Inf. Th., vol. 35, No.l, pp.123-136, January 1989;
Doc. No. 18-9CA
';~
R.Lupas and S.Verdu, "Near-far resistance of multiuser detectors in asynchronous channels," IEEE Trans. Comm. , vol. 38, No.4, pp.496-508, April 1990;
M.K.Varanasi and B.Aazhang, "Multistage detection in asynchronous code-division multiple access communications," IEEE Trans. Comm. , vol. 38, No.4, pp.509-519, Apri11990;
D.L.Ayerst et al, U.S. Patent No.: 5323418, 1994;
D.L.Schilling et al, U.S.Patent No.: 5553062, 1996;
and include techniques such as applying linear transformations to the received samples to decorrelate the interference, and techniques such as estimating the strongest user 1o first, subtracting it from the received signal and repeating it for the next strongest signal, etc. These techniques work well if the interference does not overwhelm the desired signal at any stage in the processing. Because of the latter constraint, these techniques have generally only been considered for spread spectrum signals.
The aforementioned joint detection schemes do not take into account any forward error IS correction coding of the signals.
To achieve the theoretically optimum capacity when multiple signals share the same transmission medium requires the use of forward error correction coding as is described by T.M.Cover and J.A.Thomas, in Elements of Information Theory, New 2o York: Wiley, 1991. Pedagogical techniques for achieving the theoretical capacity suggest applying a different code to each user at the transmitter and, at the receiver, estimating the digital signal with the largest signal to noise ratio (or the strongest code), subtracting its effect, and then repeating for the next digital signal; very similar to the techniques which have been proposed for uncoded systems. These techniques require 25 powerful codes that do not lead to a practical implementation. Such a technique, that is "almost practical", has been presented in the literature, for example by A.J.Viterbi, in a paper entitled " Very low rate convolutional codes for maximum theoretical performance of spread-spectrum multiple-access channels" , IEEE J. Sel. Areas Comm. , Doc. No. 18-9CA
vol. 8, no.4, pp.641-649, May 1990, but it has the drawback that it treats the digital signals asymmetrically and requires some co-ordination between transmitters.
An alternative approach to joint detection of multiple coded digital signals that is known to be optimum in a maximum likelihood sense for certain types of forward error s correction codes, is described by T.R.Giallorenzi and S.G.Wilson, in a paper entitled "Multiuser ML sequence estimator for convolutional coded asynchronous DS-CDMA
systems," IEEE Trans. Comm. , vol. 44, No. 8, pp.997-1008, August 1996.
This latter technique is a Viterbi-like algorithm that has a complexity, which is exponential in both the code memory and the number of digital signals, making it to impractical for implementation. There are other approaches to the joint detection of multiple coded signals that are obvious to those practicing the art. These include approaches such as cascading a joint detector for multiple uncoded signals with standard decoding algorithm. These approaches however, are fundamentally limited by the performance of the joint detector for multiple uncoded signals.
Examples of schemes related to and for obtaining reliability estimates from the preliminary estimates are found in H.L.van Trees, Detection, Estimation and Modulation Theory: Part I, New York: Wiley, 1968.
Examples of schemes related to soft-output decoding are found in 2o L.R.Bahl et al, "Optimal decoding of linear codes for minimizing symbol error rate,"
IEEE Trans. Inf. Th. , vo1.20, pp284-287, March 1974;
G.Battail, "Coding for the Gaussian channel: the promise of weighted output decoding," Int.J.Sat.Comm., vol.7, pp.183-192, 1989.
J.Hagenauer and P.Hoeher, "A Viterbi algorithm with soft decision outputs and its applications," Proc. IEEE Globecom, pp.47.1.1-47.1.7, November 1989;
P.Robertson et al, "A comparison of optimal and suboptimal MAP decoding algorithms operating in the log domain," Proc. ICC, pp.1009-1013, Seattle, June 1995.
Doc. No. 18-9CA
Summary of the Invention It is an object of this invention is to reduce the effects of the interference between a s multiplicity of coded digital signals sharing the same transmission medium so as to permit greater interference and conserve bandwidth.
It is a further object to provide a method that does not require asymmetrical treatment of the digital signals.
to It is a further object of the invention to provide a method that has a practical implementation.
The present invention provides an iterative method for reliably estimating multiple 15 coded digital signals that share the same medium causing mutual interference. The digital signals, in general, come from different sources but they need not.
The method is comprised of two steps that are applied to preliminary estimates of each digital signal, one or more times. There are various known methods of obtaining these preliminary estimates. In many cases, the best approach is to detect each digital signal 2o as if it were the only digital signal present in the transmission medium.
The performance of the present invention will depend upon the quality of these preliminary estimates. With regard to the approach taken to obtain these preliminary estimates, the present invention relies only on a statistical model of the interference between these preliminary estimates.
The first step of the method is to provide reliability estimates for each data element of each digital signal using the preliminary estimates, a statistical model for the interference, and any a priori information regarding the data elements. This interference model corresponds to the statistical distribution of the preliminary Doc. No. 18-9CA
estimates assuming the transmitted data is known. The reliability estimate is defined as the conditional probability of the data elements given the interference model, the preliminary estimates, and the a priori information. On the first iteration there is often no a priori information and the reliability estimates are based on the preliminary s estimate and the interference model. For binary data elements, the resulting reliability estimate is often expressed as the probability that the data element is a "0"
or a " 1" .
Properties of the forward error correction coding are not used in this step.
The second step of the method is to revise these reliability estimates for each digital 1o signal based on the forward error correction code used for that digital signal. In the literature, decoders that revise the symbol reliabilities are often called soft-output decoders. The revised probability estimates are the conditional probabilities of the data elements given the reliabilities of all the data elements for that digital signal, and the relationships between them, as defined by the forward error correction code.
In this 15 step, the digital signals are independently decoded. This results in a significant computational saving over joint decoding.
The subsequent iterations use the revised reliability estimates for each data element of each digital signal obtained from the second step as a priori information for the first 2o step. This improves the performance of the latter, which in turn can be used to improve the performance of the second step. On the last iteration, the decoders of the second step are configured to produce reliability estimates or hard decisions corresponding to the information elements of those digital signals of interest. The information elements may or may not be explicitly contained in the data elements of each digital signal, but 2s they may be always be estimated through the knowledge of the forward error correction code.
Doc. No. 18-9CA
In accordance with the invention, a method is provided of detecting a plurality of digital signals that are forward error correction encoded and mutually interfere. The method comprises the steps of:
a) obtaining preliminary estimates of the plurality of digital signals;
s b) calculating a reliability estimate for each data element of each digital signal from preliminary estimates of those data elements, a statistical model of the interference, and a priori information, if any, concerning those data elements;
c) calculating a revised reliability estimate for each data element based on the reliability estimates from the first step and the properties of the forward error correction code for to the corresponding digital signal; and d) repeating the previous two steps, one or more times, using the revised reliability estimates provided by step (c) as a priori information for step (b).
In accordance to another aspect of the invention, a system is provided of detecting a 15 plurality of digital signals that are forward error correction encoded and mutually interfere, given preliminary estimates of those signals, comprising:
means for calculating a reliability estimate for each data element of each digital signal in dependence upon the preliminary estimates of those data elements, a statistical model of the interference, and a priori information, if any, concerning those data elements;
2o and, for calculating a revised reliability estimate for each data element based on the reliability estimates calculated and the properties of the forward error correction code for the corresponding digital signal.
The present invention can be applied to digital signals in any shared transmission 25 medium, or in distinct transmission media where there is crosstalk between the media.
Doc. No. 18-9CA
Brief Description of the Drawings Exemplary embodiments of the invention will now be described in conjunction with the drawings, in which:
s Fig. 1 is schematic block diagram of a communication system to which the present invention can be applied;
Fig. 2 is a schematic block diagram of an iterative joint detector for multiple decoded signals;
Fig. 3 is flow chart of the steps required for obtaining reliability estimates;
1o Fig. 4 is a graph illustrating performance of present invention in a synchronous Gaussian channel for the case of five digital signals with a pairwise correlation of 0.75;
Fig. 5 is a block diagram illustrating a serial implementation of this invention;
Fig. 6 is a block diagram illustrating an alternative serial implementation to that shown in Fig 5;
is Fig. 7 is a block diagram illustrating the use of multiple preliminary estimates, in accordance with this invention; and, Fig. 8 is a block diagram illustrating a feedback arrangement for implementing each iteration of the method.
2o Detailed Description The present invention is a method of processing the received signal samples obtained when multiple coded signals share the same transmission medium. An example of a communications system to which this invention can be applied is illustrated in Fig. 1.
2s In this example, each of the K independent data sequences {bk(i): k=1..K, i=1,...} are modulated with a signaling waveform to produce a digital signal. These signaling waveforms may include filtering, frequency translations, spreading codes, etc.
The signaling waveforms need not be unique. These signals then enter the transmission medium and may suffer corresponding delays and attenuation, and be degraded by Doc. No. 18-9CA
noise. In this example, the communications receiver has K parallel subreceivers, one for each digital signal. These subreceivers provide preliminary estimates of the data elements of each digital signal. These preliminary estimates are often called soft decisions in the technical literature. In many cases, the best subreceiver is one that is s matched to the signaling waveform for the corresponding digital signal, ignoring the presence of the other digital signals. This matching refers not only to the transmitted signaling waveform but also any delay, frequency translation, or phase rotation that may have been incidentally applied to the signal after transmission. The present invention also applies to non-optimum subreceivers. The output of these matched detectors is then sampled, once per data element period, to produce a soft decision for each data element in the corresponding digital signal.
The present invention is a method of processing the preliminary estimates provided by these K subreceivers to reduce the effects of interference. An exemplary arrangement for the processing performed in the present invention is shown in Fig 2. In the simplest embodiment for this invention, the digital signals have the same signaling rate and are synchronous. Let b(i) be the vector of K symbols, one from each digital signal, with a common symbol time i, and let y(i) be the corresponding vector of K
preliminary 2o estimates from the K subreceivers. The statistical model for the interference, in this case, is the conditional distribution of y(i) given the transmitted data b(i).
If the noise is Gaussian then, in this case, the conditional distribution of y(i) given b(i) is multivariate Gaussian for the symbol time i and independent from one symbol time to the next.
The first step of the invention requires a means for estimating reliability of the data elements of each of the digital signals. The conventional approach is to use Bayes' rule for conditional probability, one then computes the reliability estimate (conditional s Doc. No. 18-9CA
~Q~ ~~
probability) of each data element of each digital signal that is based only on the vector of preliminary estimates y(i), the statistical model for the interference, and the a priori information regarding those data elements. Mathematically, joint reliability estimates for the K digital signals is given by Pr~b(i)IY(i)~ = pLY(i)Ib(1)l PrLb(z)l h~Y~i)~
The reliability estimates for the individual digital signals are given by the corresponding marginal distributions.This constitutes the first step.
Exemplary steps to for determining these reliability estimators are shown in Fig. 3.
In the second step of the method, each digital signal is considered independent of the others. As shown in Fig. 2, this can be implemented as K parallel decoders.
For each digital signal, the reliability estimates provided by the first step are revised based on the known relationships between data elements. These known relationships are due to the forward error correction encoding. When the data sequences are finite, a preferred means for soft-output decoding is described by L.R.Bahl, J.Cocke, F.Jelinek, and J.Raviv, in a paper entitled"Optimal decoding of linear codes for minimizing symbol error rate," IEEE
Traps. Inf. Th., vol. 20, pp.284-287, March 1974.
In subsequent iterations, the revised reliability estimates provided by the second step are used as a priori probabilities in the first step. In the preferred embodiment, the revised reliability estimates are treated as independent of one another; and in the preferred embodiment, not all of the revised reliability estimates provided by the second step are used in each first step calculation. In particular, the first step reliability estimates for a particular digital signal only use the a priori information for those digital signals other than the one of interest.
Doc. No. 18-9CA
~~, An example of the bit error rate performance obtained with this method for the case of a synchronous Gaussian channel with five independent pseudo-randomly interleaved digital signals, when the cross-correlation between each pair of the signaling waveforms (a measure of the interference) is 0.75, is shown in Fig. 4 for 1, 2, 4, and 8 iterations. Also shown in Fig. 4 is the performance obtained when there is no interference between the users (p=0).
Investigations have shown that performance improves if each of the K digital signals is pseudo-randomly interleaved relative to one another at the transmitter after forward to error correction encoding. In the description of the present invention, the interleaving is considered part of the forward error correction code. However, the approach can be applied with any type of interleaving, or even with no interleaving.
The present invention does not require that the digital signals are synchronous.
1 s However, it is recommended that the interference model for the preliminary estimates include the effects of any asynchronism. The complexity of the present invention depends in part on the complexity of this interference model. There is the possibility of reducing the complexity by appropriate design of the K subreceivers. If the digital signals are not only asynchronous but also have different signaling rates then to 20 optimize performance may require oversampling of the received signal, and constructing a corresponding interference model. Oversampling is defined as sampling at a rate higher than the transmission rate of the data elements.
The present invention does not require that all data sequences use the same forward error 25 correction code. The use of different error correction codes will only affect the second step of the method. If the digital signals are asynchronous or the data sequences have different lengths then the direct implementation of the soft decoding method of L.R.Bahl et al, may not be appropriate. Alternatively, in this case and others where the sequence to Doc. No. 18-9CA
.w..
length is an issue, the soft decoding techniques can be applied to a series of overlapping blocks where the block size is less than the sequence length. In addition to L.R.Bahl et al, there are alternative soft decoding techniques as presented by J.Hagenaur and P.Hoeher, in a paper entitled" A Viterbi algorithm with soft-decision outputs and its applications" , Proc. IEEE Globecom'89, pp.47.1. l-47.1.7, November, 1989.
[and by P.Robertson et al, in a paper entitled "A comparison of optimal and sub-optimal MAP decoding algorithms operating in the log domain," Proc. ICC'95, pp.1009-1013, June 1995, that can also be used in the second step of the method.
1o The digital signals are not required to have the same modulation format.
There are no particular issues associated with different modulation formats except to note that in the exemplary communications shown in Fig. 1, the sampling will correspond to sampling both the in phase and quadrature components of a digital signal with some modulation formats. With a binary modulation format, only the reliability of the data element "1"
is or a "0",but not both, needs to be stored; while with a M-ary modulation formats, at least M-1 or M reliability values should be stored corresponding to the M
possible values for each data element.
The invention also applies when the digital signals have the same, different, or even 2o time-varying power levels. The latter may be due to different propagation losses, fading and mufti-path. For the best performance the available knowledge concerning the power levels and time-variations, whether it be deterministic or statistical, should be included in the interference model.
25 Complexity may often be an issue in either the first or the second step of the method.
Sometimes, in the first step, simplifications are made to the interference model to reduce this complexity. These simplifications often result from a consideration of a subset of the available data in the model. For example, for each digital signal, the Doc. No. 18-9CA
interference model may only consider the interference from the two strongest interferers and ignore the effects of the other signals. Similarly, in addition to the block processing approach mentioned above, in the second step simplifications can often be made to the decoding technique to reduce the complexity. These s simplifications often result from considering only a subset of the available data. For example, some simplified decoding techniques only consider the most probable sequences (paths) at each step and ignore the less probable ones. In practice, there is usually a tradeoff between complexity and performance.
1 o Additional material is found in the appendix that further elaborates and provides additional examples in accordance with the invention.
The parallel implementation shown in Fig. 2 is one implementation of this invention;
however, the invention can also be implemented serially. In particular, one need not is decode all K signals in the second step. It is only necessary to decode a subset of the digital signals, containing at least one signal, in the second step before repeating the first step. This approach may be appropriate when a subset of the signals has significantly greater power, and it is desirable to characterize their effect accurately first. Such an approach affects the convergence time of the algorithm.
Referring now to Fig. 8, the invention does not need to be implemented with distinct hardware or software for each iteration of the method as may be suggested by Fig. 2.
One can also use the same hardware or software in a feedback arrangement, as is more obviously suggested by Fig. 8, for implementing each iteration of the method, wherein the revised reliability estimates are fed back to the initial means for estimating reliability, and the two steps of the algorithm are repeated. This feedback implementation can also be applied to all embodiments of the method. In practice, the Doc. No. 18-9CA
approach illustrated in Fig. 8 may require some buffering of the incoming preliminary estimates .
In Fig. 5, a serial implementation is shown that decodes only one signal at the second step, selecting a different one of the K digital signals for each second step.
According to the invention, any number from one to all of the K digital signals is decoded on execution of the second step. The signals need not be decoded in any particular order, nor do all signals have to be decoded an equal number of times. An alternative serial implementation is shown in Fig. 6. In this case, two decodings are performed with to each second step but the decoded digital signals are not distinct on subsequent decodings. In Figs 2, 5, and 6, the phrase "Means for soft-output decoding k"
indicates a means for soft-output decoding of digital signal k.
Note that any existing interference cancellation method for uncoded signals can be applied, prior to this invention, to provide the preliminary estimates. The only requirement is that the interference model applies to the preliminary estimates after the initial interference cancellation, if any, is done.
The invention is also applicable when there are multiple preliminary estimates of the 2o signal such as may occur when one has a number of distinct receivers. This is known in the literature as diversity reception. There are a number of ways to use the multiple preliminary estimates according to the invention. The simplest approach is using a means of combining the multiple estimates into a single estimate prior to this invention.
This is illustrated in Fig. 6.
There are many methods in the literature for combining a plurality of estimates of the same signal or set of signals. Examples of such combining schemes can be found in Doc. No. 18-9CA
W.C.Jakes (ed.), Microwave Mobile Communications, (1974) reprinted by New York:
IEEE Press , 1993 .As shown in Fig. 7, the method remains unchanged in this application. An alternative to the approach shown in Fig. 7 is to include the multiple preliminary estimates in the interference model. In this case, the method remains the s same although the means for calculating the reliability estimates may change.
Of course, numerous other embodiments other than those described heretofore and those described in the appendix may be envisaged, without departing from the spirit and scope of the invention.
Summary of the Invention It is an object of this invention is to reduce the effects of the interference between a s multiplicity of coded digital signals sharing the same transmission medium so as to permit greater interference and conserve bandwidth.
It is a further object to provide a method that does not require asymmetrical treatment of the digital signals.
to It is a further object of the invention to provide a method that has a practical implementation.
The present invention provides an iterative method for reliably estimating multiple 15 coded digital signals that share the same medium causing mutual interference. The digital signals, in general, come from different sources but they need not.
The method is comprised of two steps that are applied to preliminary estimates of each digital signal, one or more times. There are various known methods of obtaining these preliminary estimates. In many cases, the best approach is to detect each digital signal 2o as if it were the only digital signal present in the transmission medium.
The performance of the present invention will depend upon the quality of these preliminary estimates. With regard to the approach taken to obtain these preliminary estimates, the present invention relies only on a statistical model of the interference between these preliminary estimates.
The first step of the method is to provide reliability estimates for each data element of each digital signal using the preliminary estimates, a statistical model for the interference, and any a priori information regarding the data elements. This interference model corresponds to the statistical distribution of the preliminary Doc. No. 18-9CA
estimates assuming the transmitted data is known. The reliability estimate is defined as the conditional probability of the data elements given the interference model, the preliminary estimates, and the a priori information. On the first iteration there is often no a priori information and the reliability estimates are based on the preliminary s estimate and the interference model. For binary data elements, the resulting reliability estimate is often expressed as the probability that the data element is a "0"
or a " 1" .
Properties of the forward error correction coding are not used in this step.
The second step of the method is to revise these reliability estimates for each digital 1o signal based on the forward error correction code used for that digital signal. In the literature, decoders that revise the symbol reliabilities are often called soft-output decoders. The revised probability estimates are the conditional probabilities of the data elements given the reliabilities of all the data elements for that digital signal, and the relationships between them, as defined by the forward error correction code.
In this 15 step, the digital signals are independently decoded. This results in a significant computational saving over joint decoding.
The subsequent iterations use the revised reliability estimates for each data element of each digital signal obtained from the second step as a priori information for the first 2o step. This improves the performance of the latter, which in turn can be used to improve the performance of the second step. On the last iteration, the decoders of the second step are configured to produce reliability estimates or hard decisions corresponding to the information elements of those digital signals of interest. The information elements may or may not be explicitly contained in the data elements of each digital signal, but 2s they may be always be estimated through the knowledge of the forward error correction code.
Doc. No. 18-9CA
In accordance with the invention, a method is provided of detecting a plurality of digital signals that are forward error correction encoded and mutually interfere. The method comprises the steps of:
a) obtaining preliminary estimates of the plurality of digital signals;
s b) calculating a reliability estimate for each data element of each digital signal from preliminary estimates of those data elements, a statistical model of the interference, and a priori information, if any, concerning those data elements;
c) calculating a revised reliability estimate for each data element based on the reliability estimates from the first step and the properties of the forward error correction code for to the corresponding digital signal; and d) repeating the previous two steps, one or more times, using the revised reliability estimates provided by step (c) as a priori information for step (b).
In accordance to another aspect of the invention, a system is provided of detecting a 15 plurality of digital signals that are forward error correction encoded and mutually interfere, given preliminary estimates of those signals, comprising:
means for calculating a reliability estimate for each data element of each digital signal in dependence upon the preliminary estimates of those data elements, a statistical model of the interference, and a priori information, if any, concerning those data elements;
2o and, for calculating a revised reliability estimate for each data element based on the reliability estimates calculated and the properties of the forward error correction code for the corresponding digital signal.
The present invention can be applied to digital signals in any shared transmission 25 medium, or in distinct transmission media where there is crosstalk between the media.
Doc. No. 18-9CA
Brief Description of the Drawings Exemplary embodiments of the invention will now be described in conjunction with the drawings, in which:
s Fig. 1 is schematic block diagram of a communication system to which the present invention can be applied;
Fig. 2 is a schematic block diagram of an iterative joint detector for multiple decoded signals;
Fig. 3 is flow chart of the steps required for obtaining reliability estimates;
1o Fig. 4 is a graph illustrating performance of present invention in a synchronous Gaussian channel for the case of five digital signals with a pairwise correlation of 0.75;
Fig. 5 is a block diagram illustrating a serial implementation of this invention;
Fig. 6 is a block diagram illustrating an alternative serial implementation to that shown in Fig 5;
is Fig. 7 is a block diagram illustrating the use of multiple preliminary estimates, in accordance with this invention; and, Fig. 8 is a block diagram illustrating a feedback arrangement for implementing each iteration of the method.
2o Detailed Description The present invention is a method of processing the received signal samples obtained when multiple coded signals share the same transmission medium. An example of a communications system to which this invention can be applied is illustrated in Fig. 1.
2s In this example, each of the K independent data sequences {bk(i): k=1..K, i=1,...} are modulated with a signaling waveform to produce a digital signal. These signaling waveforms may include filtering, frequency translations, spreading codes, etc.
The signaling waveforms need not be unique. These signals then enter the transmission medium and may suffer corresponding delays and attenuation, and be degraded by Doc. No. 18-9CA
noise. In this example, the communications receiver has K parallel subreceivers, one for each digital signal. These subreceivers provide preliminary estimates of the data elements of each digital signal. These preliminary estimates are often called soft decisions in the technical literature. In many cases, the best subreceiver is one that is s matched to the signaling waveform for the corresponding digital signal, ignoring the presence of the other digital signals. This matching refers not only to the transmitted signaling waveform but also any delay, frequency translation, or phase rotation that may have been incidentally applied to the signal after transmission. The present invention also applies to non-optimum subreceivers. The output of these matched detectors is then sampled, once per data element period, to produce a soft decision for each data element in the corresponding digital signal.
The present invention is a method of processing the preliminary estimates provided by these K subreceivers to reduce the effects of interference. An exemplary arrangement for the processing performed in the present invention is shown in Fig 2. In the simplest embodiment for this invention, the digital signals have the same signaling rate and are synchronous. Let b(i) be the vector of K symbols, one from each digital signal, with a common symbol time i, and let y(i) be the corresponding vector of K
preliminary 2o estimates from the K subreceivers. The statistical model for the interference, in this case, is the conditional distribution of y(i) given the transmitted data b(i).
If the noise is Gaussian then, in this case, the conditional distribution of y(i) given b(i) is multivariate Gaussian for the symbol time i and independent from one symbol time to the next.
The first step of the invention requires a means for estimating reliability of the data elements of each of the digital signals. The conventional approach is to use Bayes' rule for conditional probability, one then computes the reliability estimate (conditional s Doc. No. 18-9CA
~Q~ ~~
probability) of each data element of each digital signal that is based only on the vector of preliminary estimates y(i), the statistical model for the interference, and the a priori information regarding those data elements. Mathematically, joint reliability estimates for the K digital signals is given by Pr~b(i)IY(i)~ = pLY(i)Ib(1)l PrLb(z)l h~Y~i)~
The reliability estimates for the individual digital signals are given by the corresponding marginal distributions.This constitutes the first step.
Exemplary steps to for determining these reliability estimators are shown in Fig. 3.
In the second step of the method, each digital signal is considered independent of the others. As shown in Fig. 2, this can be implemented as K parallel decoders.
For each digital signal, the reliability estimates provided by the first step are revised based on the known relationships between data elements. These known relationships are due to the forward error correction encoding. When the data sequences are finite, a preferred means for soft-output decoding is described by L.R.Bahl, J.Cocke, F.Jelinek, and J.Raviv, in a paper entitled"Optimal decoding of linear codes for minimizing symbol error rate," IEEE
Traps. Inf. Th., vol. 20, pp.284-287, March 1974.
In subsequent iterations, the revised reliability estimates provided by the second step are used as a priori probabilities in the first step. In the preferred embodiment, the revised reliability estimates are treated as independent of one another; and in the preferred embodiment, not all of the revised reliability estimates provided by the second step are used in each first step calculation. In particular, the first step reliability estimates for a particular digital signal only use the a priori information for those digital signals other than the one of interest.
Doc. No. 18-9CA
~~, An example of the bit error rate performance obtained with this method for the case of a synchronous Gaussian channel with five independent pseudo-randomly interleaved digital signals, when the cross-correlation between each pair of the signaling waveforms (a measure of the interference) is 0.75, is shown in Fig. 4 for 1, 2, 4, and 8 iterations. Also shown in Fig. 4 is the performance obtained when there is no interference between the users (p=0).
Investigations have shown that performance improves if each of the K digital signals is pseudo-randomly interleaved relative to one another at the transmitter after forward to error correction encoding. In the description of the present invention, the interleaving is considered part of the forward error correction code. However, the approach can be applied with any type of interleaving, or even with no interleaving.
The present invention does not require that the digital signals are synchronous.
1 s However, it is recommended that the interference model for the preliminary estimates include the effects of any asynchronism. The complexity of the present invention depends in part on the complexity of this interference model. There is the possibility of reducing the complexity by appropriate design of the K subreceivers. If the digital signals are not only asynchronous but also have different signaling rates then to 20 optimize performance may require oversampling of the received signal, and constructing a corresponding interference model. Oversampling is defined as sampling at a rate higher than the transmission rate of the data elements.
The present invention does not require that all data sequences use the same forward error 25 correction code. The use of different error correction codes will only affect the second step of the method. If the digital signals are asynchronous or the data sequences have different lengths then the direct implementation of the soft decoding method of L.R.Bahl et al, may not be appropriate. Alternatively, in this case and others where the sequence to Doc. No. 18-9CA
.w..
length is an issue, the soft decoding techniques can be applied to a series of overlapping blocks where the block size is less than the sequence length. In addition to L.R.Bahl et al, there are alternative soft decoding techniques as presented by J.Hagenaur and P.Hoeher, in a paper entitled" A Viterbi algorithm with soft-decision outputs and its applications" , Proc. IEEE Globecom'89, pp.47.1. l-47.1.7, November, 1989.
[and by P.Robertson et al, in a paper entitled "A comparison of optimal and sub-optimal MAP decoding algorithms operating in the log domain," Proc. ICC'95, pp.1009-1013, June 1995, that can also be used in the second step of the method.
1o The digital signals are not required to have the same modulation format.
There are no particular issues associated with different modulation formats except to note that in the exemplary communications shown in Fig. 1, the sampling will correspond to sampling both the in phase and quadrature components of a digital signal with some modulation formats. With a binary modulation format, only the reliability of the data element "1"
is or a "0",but not both, needs to be stored; while with a M-ary modulation formats, at least M-1 or M reliability values should be stored corresponding to the M
possible values for each data element.
The invention also applies when the digital signals have the same, different, or even 2o time-varying power levels. The latter may be due to different propagation losses, fading and mufti-path. For the best performance the available knowledge concerning the power levels and time-variations, whether it be deterministic or statistical, should be included in the interference model.
25 Complexity may often be an issue in either the first or the second step of the method.
Sometimes, in the first step, simplifications are made to the interference model to reduce this complexity. These simplifications often result from a consideration of a subset of the available data in the model. For example, for each digital signal, the Doc. No. 18-9CA
interference model may only consider the interference from the two strongest interferers and ignore the effects of the other signals. Similarly, in addition to the block processing approach mentioned above, in the second step simplifications can often be made to the decoding technique to reduce the complexity. These s simplifications often result from considering only a subset of the available data. For example, some simplified decoding techniques only consider the most probable sequences (paths) at each step and ignore the less probable ones. In practice, there is usually a tradeoff between complexity and performance.
1 o Additional material is found in the appendix that further elaborates and provides additional examples in accordance with the invention.
The parallel implementation shown in Fig. 2 is one implementation of this invention;
however, the invention can also be implemented serially. In particular, one need not is decode all K signals in the second step. It is only necessary to decode a subset of the digital signals, containing at least one signal, in the second step before repeating the first step. This approach may be appropriate when a subset of the signals has significantly greater power, and it is desirable to characterize their effect accurately first. Such an approach affects the convergence time of the algorithm.
Referring now to Fig. 8, the invention does not need to be implemented with distinct hardware or software for each iteration of the method as may be suggested by Fig. 2.
One can also use the same hardware or software in a feedback arrangement, as is more obviously suggested by Fig. 8, for implementing each iteration of the method, wherein the revised reliability estimates are fed back to the initial means for estimating reliability, and the two steps of the algorithm are repeated. This feedback implementation can also be applied to all embodiments of the method. In practice, the Doc. No. 18-9CA
approach illustrated in Fig. 8 may require some buffering of the incoming preliminary estimates .
In Fig. 5, a serial implementation is shown that decodes only one signal at the second step, selecting a different one of the K digital signals for each second step.
According to the invention, any number from one to all of the K digital signals is decoded on execution of the second step. The signals need not be decoded in any particular order, nor do all signals have to be decoded an equal number of times. An alternative serial implementation is shown in Fig. 6. In this case, two decodings are performed with to each second step but the decoded digital signals are not distinct on subsequent decodings. In Figs 2, 5, and 6, the phrase "Means for soft-output decoding k"
indicates a means for soft-output decoding of digital signal k.
Note that any existing interference cancellation method for uncoded signals can be applied, prior to this invention, to provide the preliminary estimates. The only requirement is that the interference model applies to the preliminary estimates after the initial interference cancellation, if any, is done.
The invention is also applicable when there are multiple preliminary estimates of the 2o signal such as may occur when one has a number of distinct receivers. This is known in the literature as diversity reception. There are a number of ways to use the multiple preliminary estimates according to the invention. The simplest approach is using a means of combining the multiple estimates into a single estimate prior to this invention.
This is illustrated in Fig. 6.
There are many methods in the literature for combining a plurality of estimates of the same signal or set of signals. Examples of such combining schemes can be found in Doc. No. 18-9CA
W.C.Jakes (ed.), Microwave Mobile Communications, (1974) reprinted by New York:
IEEE Press , 1993 .As shown in Fig. 7, the method remains unchanged in this application. An alternative to the approach shown in Fig. 7 is to include the multiple preliminary estimates in the interference model. In this case, the method remains the s same although the means for calculating the reliability estimates may change.
Of course, numerous other embodiments other than those described heretofore and those described in the appendix may be envisaged, without departing from the spirit and scope of the invention.
Claims (19)
1. A method of detecting a plurality of digital signals that are forward error correction encoded and mutually interfere comprising the steps of:
a) using a detector, detecting the plurality of digital signals and providing detector estimates of a first digital signal and second other digital signal from the plurality of digital signals;
b) using a processor receiving the detector estimates and calculating a reliability estimate for each data element of first digital signal from the plurality of digital signals, the reliability estimate calculated from detector estimates of those data elements, a model of interference, and a priori information determined in previous iterations, if any, concerning those data elements;
c) using a processor, calculating a reliability estimate for each data element of a second other digital signal from the plurality of digital signals, the reliability estimate calculated from detector estimates of those data elements, a model of the interference, and a priori information determined in previous iterations, if any, concerning those data elements;
d) using the processor, calculating a revised reliability estimate for each data element in dependence upon the reliability estimates from the step (b) and the properties of the forward error correction code for the corresponding digital signal; and e) repeating the previous two steps, one or more times, using the revised reliability estimates provided by step (c) as a priori information for the step (b).
a) using a detector, detecting the plurality of digital signals and providing detector estimates of a first digital signal and second other digital signal from the plurality of digital signals;
b) using a processor receiving the detector estimates and calculating a reliability estimate for each data element of first digital signal from the plurality of digital signals, the reliability estimate calculated from detector estimates of those data elements, a model of interference, and a priori information determined in previous iterations, if any, concerning those data elements;
c) using a processor, calculating a reliability estimate for each data element of a second other digital signal from the plurality of digital signals, the reliability estimate calculated from detector estimates of those data elements, a model of the interference, and a priori information determined in previous iterations, if any, concerning those data elements;
d) using the processor, calculating a revised reliability estimate for each data element in dependence upon the reliability estimates from the step (b) and the properties of the forward error correction code for the corresponding digital signal; and e) repeating the previous two steps, one or more times, using the revised reliability estimates provided by step (c) as a priori information for the step (b).
2. A method as defined claim 1 wherein during the first step (a), the processor uses only a subset of data when calculating the reliability estimates.
3. A method as defined in claim 1 wherein during the second step (b), the processor uses only a subset of the data when calculating the revised reliability estimates.
4. The method as defined in claim 1 wherein the first and second steps (a) and (b) provide reliability estimates for a subset of K digital signals.
5. A method as defined in claim 1, wherein either one of step b) or step c) comprises the step of using a soft-output decoder, performing soft-output decoding.
6. A method as defined in claim 5 where the step of soft-output decoding is implemented for a plurality of digital signals using a single soft-output decoder.
7. A method as defined in claim 5 wherein the step of soft-output decoding is applied to a subset of K digital signals.
8. A method as defined in claim 5 where the step of soft-output decoding is implemented in parallel for each of a plurality of digital signals.
9. A method as defined in claim 1 comprising the step of:
receiving a plurality of substantially similar digital signals from a plurality of receivers;
wherein the detector detects data elements within at least two of the received digital signals and provides the preliminary estimates of those signals; and, wherein the steps a), b) and c) are performed in dependence upon the plurality of substantially similar digital signals from a plurality of receivers.
receiving a plurality of substantially similar digital signals from a plurality of receivers;
wherein the detector detects data elements within at least two of the received digital signals and provides the preliminary estimates of those signals; and, wherein the steps a), b) and c) are performed in dependence upon the plurality of substantially similar digital signals from a plurality of receivers.
10. The method as defined in claim 1 including the step of outputting information content of one or more of the digital signals.
11. A method of detecting a plurality of digital signals that are forward error correction encoded and mutually interfere comprising the steps of;
a) providing preliminary estimates of the plurality of detected digital signals to a processor;
b) using the processor, calculating a reliability estimate for each data element of each digital signal from preliminary estimates of those data elements, a model of the interference, and a priori information, if any, concerning those data elements;
c) using the processor, calculating a revised reliability estimate for each data element in dependence upon the reliability estimates from the step (b) and the properties of the forward error correction code for the corresponding digital signal;
and, d) providing corrected estimates of each of the plurality of digital signals, the corrected estimates corrected from the preliminary estimates based on the calculated and revised reliability estimates.
a) providing preliminary estimates of the plurality of detected digital signals to a processor;
b) using the processor, calculating a reliability estimate for each data element of each digital signal from preliminary estimates of those data elements, a model of the interference, and a priori information, if any, concerning those data elements;
c) using the processor, calculating a revised reliability estimate for each data element in dependence upon the reliability estimates from the step (b) and the properties of the forward error correction code for the corresponding digital signal;
and, d) providing corrected estimates of each of the plurality of digital signals, the corrected estimates corrected from the preliminary estimates based on the calculated and revised reliability estimates.
12. A method of detecting as defined in claim 11 comprising the step of repeating steps (b) and (c) one or more times, using the revised reliability estimates provided by the step (c) as a priori information for step (b).
13. A method as defined in claim 12, wherein step (c) comprises the step of soft-output decoding.
14. The method as defined in claim 12 including the step of using a detector, detecting the plurality of digital signals and providing detector estimates of a first digital signal and second other digital signal from the plurality of digital signals.
15. A system for detecting a plurality of digital signals that are forward error correction encoded and mutually interfere, given preliminary estimates of those signals, the system having a detector for detecting a digital signal, and comprising:
a processor having an input and an output, the processor comprising:
means for calculating a reliability estimate for each data element of at least two different digital signals from the plurality of digital signals in dependence upon the preliminary estimates of those data elements, a model of interference, and a priori information, if any, concerning those data elements; and, means for calculating a revised reliability estimate for each data element based on the reliability estimates calculated and the properties of the forward error correction code for the corresponding digital signal; and, means for providing corrected estimates of the data elements of each of the first and second digital signals, the corrected estimates corrected based on the calculated and revised reliability estimates.
a processor having an input and an output, the processor comprising:
means for calculating a reliability estimate for each data element of at least two different digital signals from the plurality of digital signals in dependence upon the preliminary estimates of those data elements, a model of interference, and a priori information, if any, concerning those data elements; and, means for calculating a revised reliability estimate for each data element based on the reliability estimates calculated and the properties of the forward error correction code for the corresponding digital signal; and, means for providing corrected estimates of the data elements of each of the first and second digital signals, the corrected estimates corrected based on the calculated and revised reliability estimates.
16. A system of detecting a plurality of digital signals as defined in claim 15, including a storage medium having executable commands stored thereon for execution on the processor, said processor performing said calculations when executing the commands.
17. A system as defined in claim 16 including feed back means for providing feedback from the output to the input.
18. A system as defined in claim 15 including output means for outputting information content of one or more of the digital signals.
19. A system as defined in claim 15 comprising:
a plurality of transmitters for transmitting data signals via a common communications channel;
a model of mutual interference between signals transmitted from the transmitters from the plurality of transmitters; and, a plurality of detectors for detecting mutually interfering digital data signals and for providing the detector estimates of those signals to the processor.
a plurality of transmitters for transmitting data signals via a common communications channel;
a model of mutual interference between signals transmitted from the transmitters from the plurality of transmitters; and, a plurality of detectors for detecting mutually interfering digital data signals and for providing the detector estimates of those signals to the processor.
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