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Unequally protected multistage vector quantization for time-varying CDMA channels

IEEE TRANSACTIONS ON COMMUNICATIONS 2001年第6期49卷 1045-1054页

作者： Gadkari, S Rose, K Conexant Syst Inc Newport Beach CA 92658 USA Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

We present a source-channel coding system for operation over code-division multiple-access channels with time-varying conditions. The proposed system consists of a multistage vector quantizer (MSVQ) in conjunction with unequal protection against channel errors. The receiver estimates the channel conditions and decodes as many stages of the quantizer as can be reliably decoded, The approach to system design and optimization is first derived and evaluated for a system that employs hard decoding of stage indices. The approach is then extended to the more general case of weighted decoding. Simulation results are given for transmission of Gauss-Markov sources over broadcast and slow fading channels. Consistent and substantial improvement is achieved over the standard MSVQ with equal error protection, and the gains, in terms of source signal-to-noise ratio, are in the range of 3-5 dB.

关键词： code-division multiple access joint source-channel coding time-varying channels unequal error protection vector quantization

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Transmission of nonuniform memoryless sources via nonsystematic turbo codes

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IEEE TRANSACTIONS ON COMMUNICATIONS 2004年第8期52卷 1344-1354页

作者： Zhu, GC Alajaji, F Bajcsy, J Mitran, P Queens Univ Dept Math & Stat Kingston ON K7L 3N6 Canada McGill Univ Dept Elect & Comp Engn Montreal PQ H3A 2A7 Canada Harvard Univ Div Engn & Appl Sci Cambridge MA 02138 USA

We investigate the joint source-channel coding problem of transmitting nonuniform memoryless sources over binary phase-shift keying-modulated additive white Gaussian noise and Rayleigh fading channels via turbo codes. In contrast to previous work, recursive nonsystematic convolutional encoders are proposed as the constituent encoders for heavily biased sources. We prove that under certain conditions, and when the length of the input source sequence tends to infinity, the encoder state distribution and the marginal output distribution of each constituent recursive convolutional encoder become asymptotically uniform, regardless of the degree of source nonuniformity. We also give a conjecture (which is empirically validated) on the condition for the higher order distribution of the encoder output to be asymptotically uniform, irrespective of the source distribution. Consequently, these conditions serve as design criteria for the choice of good encoder structures. As a result, the outputs of our selected nonsystematic turbo codes are suitably matched to the channel input, since a uniformly distributed input maximizes the channel mutual information, and hence, achieves capacity. Simulation results show substantial gains by the nonsystematic codes over previously designed systematic turbo codes;furthermore, their performance is within 0.74-1.17 dB from the Shannon limit. Finally, we compare our joint source-channel coding system with two tandem schemes which employ a fourth-order Huffman code (performing near-optimal data compression) and a turbo code that either gives excellent waterfall bit-error rate (BER) performance or good error-floor performance. At the same overall transmission rate, our system offers robust and superior performance at low BERs (less than or equal to 10(-4)), while its complexity is lower.

关键词： additive white Gaussian noise (AWGN) and Rayleigh fading channels joint source-channel coding nonsystematic turbo codes nonuniform independent and identically distributed (i.i.d.) sources Shannon limit

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Robust Information Bottleneck for Task-Oriented Communication With Digital Modulation

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2023年第8期41卷 2577-2591页

作者： Xie, Songjie Ma, Shuai Ding, Ming Shi, Yuanming Tang, Mingjian Wu, Youlong ShanghaiTech Univ Sch Informat Sci & Technol Shanghai 201210 Peoples R China Peng Cheng Lab Shenzhen 518055 Peoples R China CSIRO Data61 Sydney NSW 2015 Australia Atlassian Sydney NSW 2000 Australia

Task-oriented communications, mostly using learning-based joint source-channel coding (JSCC), aim to design a communication-efficient edge inference system by transmitting task-relevant information to the receiver. However, only transmitting task-relevant information without introducing any redundancy may cause robustness issues in learning due to the channel variations, and the JSCC which directly maps the source data into continuous channel input symbols poses compatibility issues on existing digital communication systems. In this paper, we address these two issues by first investigating the inherent tradeoff between the informativeness of the encoded representations and the robustness to information distortion in the received representations, and then propose a task-oriented communication scheme with digital modulation, named discrete task-oriented JSCC (DT-JSCC), where the transmitter encodes the features into a discrete representation and transmits it to the receiver with the digital modulation scheme. In the DT-JSCC scheme, we develop a robust encoding framework, named robust information bottleneck (RIB), to improve the communication robustness to the channel variations, and derive a tractable variational upper bound of the RIB objective function using the variational approximation to overcome the computational intractability of mutual information. The experimental results demonstrate that the proposed DT-JSCC achieves better inference performance than the baseline methods with low communication latency, and exhibits robustness to channel variations due to the applied RIB framework.

关键词： Task-oriented communication joint source-channel coding variational inference discrete representation learning

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A Theory of Semantic Communication

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2024年第12期23卷 12211-12228页

作者： Shao, Yulin Cao, Qi Gunduz, Deniz Univ Macau Dept Elect & Comp Engn State Key Lab Internet Things Smart City Macau 999078 Peoples R China Xidian Univ Xidian Guangzhou Res Inst Xian 710126 Peoples R China Imperial Coll London Dept Elect & Elect Engn London SW7 2AZ England

Semantic communication is an emerging research area that has gained a wide range of attention recently. Despite this growing interest, there remains a notable absence of a comprehensive and widely-accepted framework for characterizing semantic communication. This paper introduces a new conceptualization of semantic communication and formulates two fundamental problems, which we term language exploitation and language design. Our contention is that the challenge of language design can be effectively situated within the broader framework of joint source-channel coding theory, underpinned by a comprehensive end-to-end distortion metric. To tackle the language exploitation problem, we put forth three approaches: semantic encoding, semantic decoding, and a synergistic combination of both in the form of combined semantic encoding and decoding. Furthermore, we establish the semantic distortion-cost region as a critical framework for assessing the language exploitation problem. For each of the three proposed approaches, the achievable distortion-cost region is characterized. Overall, this paper aims to shed light on the intricate dynamics of semantic communication, paving the way for a deeper understanding of this evolving field.

关键词： Semantics Receivers Transmitters Decoding Symbols channel coding Distortion joint source-channel coding large language model semantic communication semantic decoding semantic encoding

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Machine Learning in the Air

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2019年第10期37卷 2184-2199页

作者： Gunduz, Deniz de Kerret, Paul Sidiropoulos, Nicholas D. Gesbert, David Murthy, Chandra R. van der Schaar, Mihaela Imperial Coll London Dept Elect & Elect Engn Informat Proc & Commun Lab London SW7 2BT England EURECOM Commun Syst Dept F-501930690 Sophia Antipolis France Univ Virginia Dept Elect & Comp Engn Charlottesville VA 22904 USA Indian Inst Sci Dept Elect & Comp Engn Bengaluru 560012 India Univ Calif Los Angeles Dept Elect & Comp Engn Los Angeles CA 90095 USA

Thanks to the recent advances in processing speed, data acquisition and storage, machine learning (ML) is penetrating every facet of our lives, and transforming research in many areas in a fundamental manner. Wireless communications is another success story - ubiquitous in our lives, from handheld devices to wearables, smart homes, and automobiles. While recent years have seen a flurry of research activity in exploiting ML tools for various wireless communication problems, the impact of these techniques in practical communication systems and standards is yet to be seen. In this paper, we review some of the major promises and challenges of ML in wireless communication systems, focusing mainly on the physical layer. We present some of the most striking recent accomplishments that ML techniques have achieved with respect to classical approaches, and point to promising research directions where ML is likely to make the biggest impact in the near future. We also highlight the complementary problem of designing physical layer techniques to enable distributed ML at the wireless network edge, which further emphasizes the need to understand and connect ML with fundamental concepts in wireless communications.

关键词： Autoencoders channel coding channel estimation data-driven methods distributed learning distributed resource allocation deep learning federated edge learning joint source-channel coding machine learning stochastic approximation wireless communications

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Communicating Correlated sources Over MAC and Interference channels I: Separation-Based Schemes

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IEEE TRANSACTIONS ON INFORMATION THEORY 2020年第7期66卷 4104-4128页

作者： Padakandla, Arun Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN 37996 USA

We consider the two scenarios of communicating a pair S-1, S-2 of distributed correlated sources over 2-user multiple access (MAC) and interference channels (IC), respectively. While in the MAC problem, the receiver needs to reconstruct both sources, in the IC problem, receiver j needs to reconstruct S-j. We undertake a Shannon theoretic study and focus on characterizing sufficient conditions. Building on Dueck's findings (1981), we propose a coding scheme based on fixed block-length (B-L) codes. We characterize its information theoretic performance and characterize a new set of sufficient conditions. We identify examples of the MAC and IC problems for which the latter conditions are proven to be strictly weaker than the current known tightest.

关键词： channel coding Integrated circuits Correlation source coding Interference channels Receivers Shannon theory joint source-channel coding inner bound achievability sufficient conditions correlated sources constant composition codes single-letter coding scheme

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Generalized joint Shuffled Scheduling Decoding Algorithm for the JSCC System Based on Protograph-LDPC Codes

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IEEE ACCESS 2021年 9卷 128372-128380页

作者： Xu, Zhiping Wang, Lin Hong, Shaohua Chen, Guanrong Xiamen Univ Dept Commun Engn Xiamen 361005 Peoples R China Xiamen Univ Natl Inst Data Sci Hlth & Med Xiamen 361005 Peoples R China Shenzhen Res Inst Xiamen Univ Shenzhen 518057 Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China

The joint shuffied scheduling decoding (JSSD) algorithm can reduce the decoding complexity of the joint source-channel coding system (JSCC) based on double protograph low-density parity-check (P-LDPC) codes. However, the JSSD algorithm will not work when the linking matrix between check nodes (CNs) of the source P-LDPC and variable nodes (VNs) of the channel P-LDPC is adopted in such a system, and this linking matrix has a significant influence on the system performance. In this paper, a generalized joint shuffied scheduling decoding (GJSSD) algorithm is designed to work for the system, and the JSSD algorithm can be regarded as a special case of this algorithm. Simulations show that the proposed GJSSD algorithm can reduce the decoding complexity with performance improvement when compared with the joint belief-propagation (JBP) algorithm.

关键词： joint source-channel coding P-LDPC code shuffied decoding

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joint source-channel Decoding Over MIMO channels Based on Partial Marginalization

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2012年第12期60卷 6734-6739页

作者： Persson, Daniel Larsson, Erik G. Skoglund, Mikael Linkoping Univ Dept Elect Engn SE-58183 Linkoping Sweden Royal Inst Technol Sch Elect Engn SE-10044 Stockholm Sweden

We investigate fast joint source-channel decoding employed for communication over frequency-flat and frequency-selective block-fading multiple-input multiple-output channels. Our setting has applications for communication with short codes under low-latency constraints. The case of no transmitter channel state information is considered. We propose a partial marginalization decoder that allows performance to be traded for computational complexity, by adjusting a user parameter. By tuning this parameter to its maximum value, the minimum mean square error (MMSE) decoder is obtained. In the conducted simulations, the proposed scheme almost achieves the MMSE performance for a wide range of the channel signal-to-noise ratios, with significant reductions in computational complexity.

关键词： Fast decoding joint source-channel coding low latency multiple-input multiple-output (MIMO) short codes

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Analogue Transmission over a Two-Hop Gaussian Cascade Network

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IEEE COMMUNICATIONS LETTERS 2010年第2期14卷 175-177页

作者： Kim, Anna N. Kansanen, Kimmo Norwegian Univ Sci & Technol Inst Elect & Telecommun NO-7491 Trondheim Norway

We investigate lossy transmission of two intercorrelated sources over a two-hop cascade network. A low delay analogue based joint source-channel coding scheme is proposed for the case of jointly Gaussian sources over channels with additive white Gaussian noise (AWGN), subject to a quadratic distortion constraint. For the first hop, uncoded transmission is used, with an optimal minimum mean-squared error (mmse) decoder at the relay node that utilizes the other source as side information. For the second hop, we first perform decorrelation using Karhunen-Loeve Transform, followed by dimension reduction mappings. Simulation results show that relative to the optimal performance theoretically attainable (OPTA), uncoded transmission with the optimal mmse joint decoder for the first hop is able perform close to OPTA when the inter-correlation is relatively weak. For the second hop, result of the proposed scheme is able to come within 1.5dB from OPTA.

关键词： Cascade network joint source-channel coding uncoded transmission Shannon-Kotel'nikov mapping dimension reduction

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joint design of channel-optimized multistage vector quantizer

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IEEE SIGNAL PROCESSING LETTERS 2004年第1期11卷 5-7页

作者： Krishnan, V Anderson, DV Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

In this letter, a novel channel-optimized multistage vector quantization (COMSVQ), codec is presented in which the stage codebooks are jointly designed. The proposed codec uses a signal source and channel-dependent distortion measure to encode line spectral frequencies derived from segments of a speech signal. Simulation results are provided to demonstrate the consistent reduction in the spectral distortion obtained using the proposed codec as compared to the conventional sequentially designed channel-matched multistage vector quantizer.

关键词： joint source-channel coding speech coding vector quantization

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