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Attention-based neural joint source-channel coding of text for point to point and broadcast channel

ARTIFICIAL INTELLIGENCE REVIEW 2022年第3期55卷 2379-2407页

作者： Liu, Ting Chen, Xuechen Cent South Univ Sch Comp Sci & Engn Changsha Peoples R China Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou Peoples R China

In this work, we consider the transmissions of structured data such as text over a noisy channel and correlated texts over a broadcast channel. As the separate source-channel coding principle no longer holds in such scenarios, we propose a joint source-channel coding scheme which is based on deep learning architecture. In order to enhance the convergence speed, we adopt the bidirectional gated recurrent unit at the encoder. For the decoder, to improve the recovery quality, we propose the following two types of strategies: (1) After a unidirectional neural network based decoder is used, a generative adversarial network is applied to train the whole joint source-channel coding framework and pointwise mutual information is added to the objective function of beam search process;(2) Rather than using a unidirectional neural network-based decoder, we develop a bidirectional neural network based and bidirectional attention mechanism integrated decoder to utilize past and future information. Experiments under different types of channels show that our schemes are superior to the existing deep learning joint source-channel coding method and in the case of low bit budget, long sentence length and small channel signal to noise ratio, our models are significantly superior to those of separate source-channel coding. In addition, we extend the proposed unidirectional and bidirectional decoders to the broadcast channel. Additionally, to improve the performance of unidirectional decoding, we utilize not only the correlation between adjacent words in the same text but also the correlation between words in different languages with the same meaning in the beam search process.

关键词： Deep learning Bidirectional attention Generative adversarial networks joint source-channel coding Point to point channel Broadcast channel

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A Lower Bound on the Expected Distortion of joint source-channel coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2020年第8期66卷 4722-4741页

作者： Kochman, Yuval Ordentlich, Or Polyanskiy, Yury Hebrew Univ Jerusalem Rachel & Selim Benin Sch Comp Sci & Engn IL-91904 Jerusalem Israel MIT 77 Massachusetts Ave Cambridge MA 02139 USA

We consider the classic joint source-channel coding problem of transmitting a memoryless source over a memoryless channel. The focus of this work is on the long-standing open problem of finding the rate of convergence of the smallest attainable expected distortion to its asymptotic value, as a function of the blocklength n. Our main result is that in general the convergence rate is not faster than n(-1/2). In particular, we show that for the problem of transmitting i.i.d uniform bits over a binary symmetric channels with Hamming distortion, the smallest attainable distortion (bit error rate) is at least Omega(n(-1/2)) above the asymptotic value, if the "bandwidth expansion ratio" is above 1.

关键词： joint source-channel coding finite blocklength binary symmetric channel (BSC) broadcast channel

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Low-Delay Analog joint source-channel coding With Deep Learning

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IEEE TRANSACTIONS ON COMMUNICATIONS 2023年第1期71卷 40-51页

作者： Xuan, Ziwei Narayanan, Krishna Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77840 USA

We consider the design of low-delay joint source-channel coding (JSCC) schemes for the transmission of discrete-time analog sources over noisy channels based on deep neural networks. The design problem is addressed as optimization of an autoencoder model, and several scenarios are discussed. For point-to-point communication of independent and identically distributed (i.i.d) Gaussian sources and Gauss-Markov sources over additive-white Gaussian noise (AWGN) channels, the encoder and decoder are constructed using recurrent neural networks (RNNs). With minimum prior knowledge used for design, the performance of these RNNs-based models is optimized using fine tuning techniques during training. Sinusoidal representation networks (SIRENs)-based models are proposed and optimized for three JSCC problems namely, transmitting multivariate Gaussian sources over AWGN channels, transmitting i.i.d Gaussian sources with side information at the decoder, and for communicating correlated sources over orthogonal Gaussian channels. We show that these deep learning-based JSCC schemes perform comparably or better than state-of-the-art (SOTA) traditional schemes. The proposed scheme can extend flexibly to different pairs of source and channel dimensions. Moreover, the spontaneously learned encoder mappings exhibit structured patterns that are interpretable.

关键词： Decoding AWGN channels Receivers Noise measurement Training Distortion Recurrent neural networks joint source-channel coding deep learning RNNs SIRENs distributed source-channel coding

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Rematch-and-Forward: joint source-channel coding for Parallel Relaying With Spectral Mismatch

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IEEE TRANSACTIONS ON INFORMATION THEORY 2014年第1期60卷 605-622页

作者： Kochman, Yuval Khina, Anatoly Erez, Uri Zamir, Ram Hebrew Univ Jerusalem Sch Comp Sci & Engn IL-91904 Jerusalem Israel Tel Aviv Univ Dept Elect Engn IL-61392 Tel Aviv Israel

The Gaussian parallel relay network, introduced by Schein and Gallager, consists of a concatenation of a Gaussian additive broadcast channel from a single encoder to a layer of relays followed by a Gaussian multiple-access channel from the relays to the final destination (decoder), where all noises are independent. This setup exhibits an inherent conflict between digital and analog relaying;while analog relaying [known as amplify-and-forward (A&F)] suffers from noise accumulation, digital relaying (known as decode-and-forward) looses the potential coherence gain in combining the relay noises at the decoder. For a large number of relays, the coherence gain is large, and thus analog relaying has better performance;however, it is limited to white channels of equal bandwidth. In this paper, we present a generalization of the analog approach to the case of bandwidth mismatch. Our strategy, coined rematch and forward (R&F), is based upon applying joint source-channel coding techniques that belong to a certain class of maximally analog schemes. Using such techniques, R&F converts the bandwidth of the broadcast section to that of the multiple-access section, creating an equivalent matched-bandwidth network over which A&F is applied. It is shown that this strategy exploits the full bandwidth of the individual channels, without sacrificing the coherence gain offered by A&F. Specifically, for given individual-link capacities, R&F remains within a constant gap from the network capacity for any number of relays and any bandwidth ratio between the sections. Finally, the approach is extended to the case of colored channels.

关键词： Parallel relay network network capacity amplify-and-forward joint source-channel coding hybrid digital-analog transmission modulo-lattice modulation broadcast channel multiple access channel coherence gain bandwidth mismatch ISI channel

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Duality theorems for joint source-channel coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2000年第4期46卷 1263-1275页

作者： Mittal, U Phamdo, N SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA

We consider joint source-channel coding for a memoryless Gaussian source and an additive white Gaussian noise (AWGN) channel. For a given code defined by an encoder-decoder pair (alpha, beta), its dual code is obtained by interchanging the encoder and decoder: (beta, alpha). It is shown that if a code (alpha, beta) is optimal at rate rho channel uses per source sample and if it satisfies a certain uniform continuity condition, then its dual code (beta, alpha) is optimal for rate 1/rho channel uses per source sample, Further, it is demonstrated that there is a code which is optimal but its dual code is not optimal, Finally, using random coding, we show that there is an optimal code which has an optimal dual, The duality concept is also presented for the cases of i) binary memoryless equiprobable source and binary-symmetric channel (BSC), and ii) colored Gaussian source and additive colored Gaussian noise (ACGN) channel.

关键词： AWGN channel blowing-up lemma duality joint source-channel coding memoryless Gaussian source

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Robust Packet Video Transport Over Wireless Fading channels Using a joint source-channel coding Approach

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WIRELESS PERSONAL COMMUNICATIONS 2009年第3期48卷 425-439页

作者： Pei, Yong Modestino, James W. Wright State Univ Dept Comp Sci & Engn Dayton OH 45435 USA Univ Miami Dept Elect & Comp Engn Coral Gables FL 33124 USA

In this paper, we address the problem of robust video transmission over wireless networks. Specifically, we consider packet video transmission over wireless IP networks based on the RTP/UDP/IP protocol stack. Digital video delivered over wireless networks is expected to suffer quality degradation from both packet loss and bit errors in the payload. In this paper, both packet loss and bit errors in the payload are considered and the performance of a joint source-channel coding (JSCC) approach employing forward error-correction (FEC) coding schemes for H.263 + video transmission is studied. Results indicate that with an appropriate JSCC approach, FEC-based error-control techniques can significantly improve the packetization efficiency for a given end-to-end quality requirement and lead to more acceptable video delivery quality over time-varying wireless networks. Another important observation is that with a JSCC approach the fading effects of wireless links upon end-to-end video quality are substantially decreased compared to a system without using channel coding, resulting in attractive robust performance characteristics.

关键词： Video transmission RTP UDP/IP Error-control coding RCPC codes joint source-channel coding Rician fading H.263+

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Turbo compression/joint source-channel coding of correlated binary sources with hidden Markov correlation

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SIGNAL PROCESSING 2006年第11期86卷 3115-3122页

作者： Zhao, Ying Garcia-Frias, Javier Univ Delaware Dept Elect & Comp Engn Newark DE 19716 USA

We propose a system to perform compression and joint source-channel coding of correlated binary sources when the correlation between the sources is defined by a hidden Markov model. In the case of source coding, punctured turbo codes are used as source encoders, with the objective of compressing the information at rates close to the Slepian-Wolf theoretical limit. The same system structure can be utilized for the transmission of the correlated sources through noisy channels (joint source-channel coding), so that the desired information rates are achieved by puncturing. In both cases, no a priori knowledge about the correlation statistics is required in the encoding process. The source decoder utilizes iterative schemes and does not present significant performance degradation when the correlation parameters are not known in the decoder, since they can be estimated jointly with the iterative decoding process. (c) 2006 Elsevier B.V. All rights reserved.

关键词： turbo codes iterative decoding correlated sources AWGN channels joint source-channel coding hidden Markov models

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Two-way successively refined joint source-channel coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2006年第4期52卷 1483-1494页

作者： Maor, A Merhav, N Technion Israel Inst Technol Dept Elect Engn IL-32000 Haifa Israel

Consider a source, {X-i, Y-i}(i=1)(infinity) producing independent copies of a pair of jointly distributed random variables (RVs). The {X-i} part of the process is observed at some location, say A, and is supposed to be reproduced at a different location, say B, where the {Y-i} part of the process is observed. Similarly, {Y-i} should be reproduced at location A. The communication between the two locations is carried out across two memoryless channels in K iterative bi-directional rounds. In each round, the source components are reconstructed at the other locations based on the information exchanged in all previous rounds and the source component known at that location, and it is desired to find the amount of information that should be exchanged between the two locations in each round, so that the distortions incurred (in each round) will not exceed given thresholds. Our setting extends the results of Steinberg and Merhav as well as Kaspi, combining the notion of successive refinement with this of two-way interactive communication. We first derive a single-letter characterization of achievable rates for a pure source-coding problem with successive refinement. Then, for a joint source-channel coding setting, we prove a separation theorem, asserting that in the limit of long blocks, no optimality is lost by first applying lossy (two-way) successive-refinement source coding, regardless of the channels, and then applying good channel codes to each one of the resulting bitstreams, regardless of the source.

关键词： channel capacity joint source-channel coding source coding successive refinement two-way communication

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Concatenated Spatially Coupled LDPC Codes With Sliding Window Decoding for joint source-channel coding

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IEEE TRANSACTIONS ON COMMUNICATIONS 2022年第2期70卷 851-864页

作者： Golmohammadi, Ahmad Mitchell, David G. M. New Mexico State Univ Klipsch Sch Elect & Comp Engn Las Cruces NM 88003 USA Bose Corp Framingham MA 01701 USA

In this paper, a method for joint source-channel coding (JSCC) based on concatenated spatially coupled low-density parity-check (SC-LDPC) codes is investigated. A construction consisting of two SC-LDPC codes is proposed: one for source coding and the other for channel coding, with a joint belief propagation-based decoder. Also, a novel windowed decoding (WD) scheme is presented with significantly reduced latency and complexity requirements. The asymptotic behavior for various graph node degrees is analyzed using a protograph-based Extrinsic Information Transfer (EXIT) chart analysis for both LDPC block codes with block decoding and for SC-LDPC codes with the WD scheme, showing robust performance for concatenated SC-LDPC codes. Simulation results show a notable performance improvement compared to existing state-of-the-art JSCC schemes based on LDPC codes with comparable latency and complexity constraints.

关键词： Codes Parity check codes Decoding source coding Convolutional codes Generators Sparse matrices Low-density parity-check (LDPC) codes spatially coupled codes joint source-channel coding window decoding

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LDGM codes for channel coding and joint source-channel coding of correlated sources

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EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING 2005年第6期2005卷 942-953页

作者： Zhong, W Garcia-Frias, J Univ Delaware Dept Elect & Comp Engn Newark DE 19716 USA

We propose a coding scheme based on the use of systematic linear codes with low-density generator matrix (LDGM codes) for channel coding and joint source-channel coding of multiterminal correlated binary sources. In both cases, the structures of the LDGM encoder and decoder are shown, and a concatenated scheme aimed at reducing the error floor is proposed. Several decoding possibilities are investigated, compared, and evaluated. For different types of noisy channels and correlation models, the resulting performance is very close to the theoretical limits.

关键词： channel coding LDPC codes LDGM codes iterative decoding correlated sources joint source-channel coding

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