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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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Robust decoding of variable-length encoded Markov sources using a three-dimensional trellis

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IEEE COMMUNICATIONS LETTERS 2003年第7期7卷 320-322页

作者： Thobaben, R Kliewer, J Univ Kiel Fac Engn Inst Circuits & Syst Theory D-24143 Kiel Germany

In this letter, we present an improved index-based a-posteriori probability (APP) decoding approach for the error-resilient transmission of packetized variable-length encoded Markov sources. The proposed algorithm is based on a novel two-dimensional (2-D) state representation which leads to a three-dimensional trellis with unique state transitions. APP decoding on this trellis is realized by employing a 2-D version of the BCJR algorithm where all available source statistics can be fully exploited in the source decoder. For an additional use of channel codes the proposed approach leads to an increased error-correction performance compared to a one-dimensional state representation.

关键词： iterative decoding joint source-channel coding residual source redundancy variable-length codes (VLCs)

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Utilization of multi-dimensional source correlation in multi-dimensional single parity check codes

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TELECOMMUNICATION SYSTEMS 2016年第4期62卷 735-745页

作者： Izhar, Mohd Azri Mohd Zhou, Xiaobo Matsumoto, Tad Univ Teknol Malaysia Wireless Commun Ctr Skudai 81310 Johor Malaysia Tianjin Univ Sch Comp Sci & Technol Weijin Rd 92 Tianjin 300072 Peoples R China Japan Adv Inst Sci & Technol 1-1 Asahidai Nomi Ishikawa 9231292 Japan

This paper proposes a joint source-channel coding (JSCC) technique that well utilizes multi-dimensional (MD) source correlation using MD single parity check codes (MD-SPCCs). The source is assumed to be described by the coupling of multiple first-order binary Markov processes. The knowledge about the source correlation is utilized in the channel decoding process where each component decoder utilizes a single dimension correlation of the MD source. To enhance performance and reduce the error floor, a rate-1 recursive systematic convolutional code is serially concatenated to the MD-SPCC via a random interleaver. Two decoding techniques are proposed for each component decoder, and the selection of the decoding technique depends on the strength of the source correlation, which may further enhance the performance of the proposed JSCC technique. Simulation results reveal that a significant performance gain can be achieved by exploiting the MD source correlation with the proposed JSCC technique compared with the case in which the source correlation is not utilized;more significant gains can be achieved with stronger source correlation, and with a larger dimensionality source correlation as well.

关键词： joint source-channel coding Single parity check codes Multi-dimensional source correlation Turbo coding

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Tree-structured oversampled filterbanks as joint source-channel codes: Application to image transmission over erasure channels

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2004年第9期52卷 2584-2599页

作者： Motwani, R Guillemot, C Data Storage Inst Singapore Singapore Natl Univ Singapore Singapore 117548 Singapore INRIA IRISA F-35042 Rennes France

This paper studies oversampled filterbanks for robust transmission of multimedia signals over erasure channels. Oversampled filterbanks implement frame expansions of signals in l(2)(Z). The dependencies between the expansion coefficients introduced by the oversampled filterbank are first characterized both in the z-domain and in the time-domain. Conditions for recovery of some typical erasure patterns like bursty erasure patterns are derived. The analysis leads to the design of two erasure recovery algorithms that are first studied without quantization noise. The reconstruction algorithm derived from the time-domain analysis exploits the fact that an oversampled filterbank represents signals with more than one set of basis functions. The erased samples are first reconstructed from the received ones, and then, signal space projection is applied. The effect of quantization noise on the reconstructed signal is studied for both algorithms. Using image signals, the theoretical results are validated for a number of erasure patterns, considering unequal error protection enabled tree-structured decompositions.

关键词： erasure resilient coding frames joint source-channel coding multiple description coding oversampled filterbanks

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