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作者： Shahrbaf Motlagh, Meysam University of Waterloo

学位级别：master

In this work, we study the problem of lossy joint source-channel coding in an energy harvesting single-user communication systemwith causal energy arrivals, where the energy storage unit may have leakage. In particular, we investigate the achievable distortion in the transmission of a single source with arbitraryalphabets via an energy harvesting transmitter over a point-to-point channel. We first establish a lower bound on the achievable distortion. Then, to minimize the distortion we consider an adaptive joint source-channel coding scheme, where the length of channel codewords varies adaptively based on the available battery charge in each communication block. For this scheme, we obtain two coupled equations that determine the mismatch ratio between channel symbols and input symbols as well as the transmission power, both as functionsof battery charge. As examples of continuous and discrete sources, we consider Gaussian and binary sources. In particular, for the Gaussian case, we obtain a closed form expression for the mismatch factor in terms of the $Lambert W$ function, and show that an increasing transmission power results in a decreasing mismatch factor and vice versa. We also numerically show that when the mismatch factor adaptively changes based on the available charge in the battery, the communication system achieves a smaller distortion compared to that of a constant mismatch factor

关键词： joint source-channel coding Energy Harvesting Distortion Resource Allocation

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A NOVEL ERROR RESILIENT joint source-channel coding SCHEME FOR IMAGE TRANSMISSION OVER ERROR PRONE channelS

A NOVEL ERROR RESILIENT JOINT SOURCE-CHANNEL CODING SCHEME F...

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2nd IEEE International Conference on Broadband Network and Multimedia Technology

作者： Xue Guodong Hao Chenxi Zhang Wenbo Zou Jun Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing 100088 Peoples R China Beijing Univ Posts & Telecommun Sch Comp Sci & Technol Beijing 100088 Peoples R China IBM Corp China Software Dev Lab CDL Beijing Peoples R China

ISBN: (纸本)9781424450053

In this paper, we proposed a double-level error resilient joint source-channel coding scheme for image transmission. Characteristically, we inserted one coordinative component named error resilient entropy coding (EREC) between source coding and channel coding to achieve additional error resilient capability. Based on the novel architecture, we proved that, in the aspects of computational complexity, coding redundancy and furthermore the decoding performance of image transmission, our scheme outperformed either separate source and channel coding scheme or joint source-channel coding scheme with synchronization words.

关键词： double-level error resilient capability joint source-channel coding image transmission error prone channels

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channel-Blind joint source-channel coding for Wireless Image Transmission

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SENSORS 2024年第12期24卷 4005页

作者： Yuan, Hongjie Xu, Weizhang Wang, Yuhuan Wang, Xingxing Commun Univ China State Key Lab Media Convergence & Commun Beijing 100024 Peoples R China

joint source-channel coding (JSCC) based on deep learning has shown significant advancements in image transmission tasks. However, previous channel-adaptive JSCC methods often rely on the signal-to-noise ratio (SNR) of the current channel for encoding, which overlooks the neural network's self-adaptive capability across varying SNRs. This paper investigates the self-adaptive capability of deep learning-based JSCC models to dynamically changing channels and introduces a novel method named channel-Blind JSCC (CBJSCC). CBJSCC leverages the intrinsic learning capability of neural networks to self-adapt to dynamic channels and diverse SNRs without relying on external SNR information. This approach is advantageous, as it is not affected by channel estimation errors and can be applied to one-to-many wireless communication scenarios. To enhance the performance of JSCC tasks, the CBJSCC model employs a specially designed encoder-decoder. Experimental results show that CBJSCC outperforms existing channel-adaptive JSCC methods that depend on SNR estimation and feedback, both in additive white Gaussian noise environments and under slow Rayleigh fading channel conditions. Through a comprehensive analysis of the model's performance, we further validate the robustness and adaptability of this strategy across different application scenarios, with the experimental results providing strong evidence to support this claim.

关键词： wireless image transmission joint source-channel coding attention mechanism broadcasting

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Transmission of Still Images Using Low-Complexity Analog joint source-channel coding

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SENSORS 2019年第13期19卷 2932.-2932.页

作者： Balsa, Jose Dominguez-Bolano, Tomas Fresnedo, Oscar Garcia-Naya, Jose A. Castedo, Luis Univ A Coruna CITIC Res Ctr Dept Comp Engn La Coruna 15071 Spain

An analog joint source-channel coding (JSCC) system designed for the transmission of still images is proposed and its performance is compared to that of two digital alternatives which differ in the source encoding operation: joint Photographic Experts Group (JPEG) and JPEG without entropy coding (JPEGw/oEC), respectively, both relying on an optimized channel encoder-modulator tandem. Apart from a visual comparison, the figures of merit considered in the assessment are the structural similarity (SSIM) index and the time required to transmit an image through additive white Gaussian noise (AWGN) and Rayleigh channels. This work shows that the proposed analog system exhibits a performance similar to that of the digital scheme based on JPEG compression with a noticeable better visual degradation to the human eye, a lower computational complexity, and a negligible delay. These results confirm the suitability of analog JSCC for the transmission of still images in scenarios with severe constraints on power consumption, computational capabilities, and for real-time applications. For these reasons the proposed system is a good candidate for surveillance systems, low-constrained devices, Internet of things (IoT) applications, etc.

关键词： image coding joint source-channel coding performance evaluation

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joint source and channel coding for MIMO systems: Is it better to be robust or quick?

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IEEE TRANSACTIONS ON INFORMATION THEORY 2008年第4期54卷 1393-1405页

作者： Holliday, Tim Goldsmith, Andrea J. Poor, H. Vincent Goldman Sachs New York NY 10004 USA Stanford Univ Dept Elect Engn Stanford CA 94305 USA Princeton Univ Sch Engn & Appl Sci Princeton NJ 08544 USA

A framework is developed for optimizing the tradeoff between diversity, multiplexing, and delay in multiple-input multiple-output (MIMO) systems to minimize end-to-end distortion. The goal is to find the optimal balance between the increased data rate provided by antenna multiplexing, the reduction in transmission errors provided by antenna diversity and automatic repeat request (ARQ), and the delay introduced by ARQ. First, closed-form analytical results are developed to minimize end-to-end distortion of a vector quantizer concatenated with a space-time MIMO channel code in the high SNR regime. The minimizati(in determines the optimal point on the diversity-multiplexing tradeoff curve. For large but finite SNR this optimal point is found via convex optimization, which is illustrated with an example of a practical joint source-channel code design. It is then shown that for MIMO systems with ARQ retransmission, sources without a delay constraint have distortion minimized by maximizing the ARQ window size. This results in a new multiplexing-diversity tradeoff region enhanced by ARQ. However, under a source delay constraint the problem formulation changes to account for delay distortion associated with random message arrival and random ARQ completion times. In this case, the simplifications associated with a high SNR assumption break down, and a dynamic programming formulation is required to capture the channel diversity-multiplexing tradeoff as well as the random arrival and retransmission dynamics. Results based on this formulation show that a delay-sensitive system obtains significant performance gains by adapting its operating point on the diversity-multiplexing-delay region to system dynamics.

关键词： automatic repeat request (ARQ) diversity-multiplexing-delay tradeoff joint source-channel coding multiple-input multiple-output (MIMO) channels

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Impact of training models on deep joint source-channel coding applicable to 5G systems

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IEICE COMMUNICATIONS EXPRESS 2024年第12期13卷 466-469页

作者： Yamamoto, Ryunosuke Matsumoto, Keigo Inoue, Yoshiaki Hara, Yuko Maruta, Kazuki Nakayama, Yu Hisano, Daisuke Osaka Univ Grad Sch Engn 2-1 Yamadaoka Suita Osaka 5650871 Japan Tokyo Inst Technol Sch Engn 2-12-1 OhokayamaMeguro Ku Tokyo 1528550 Japan Tokyo Univ Sci Fac Engn 6-3-1 NiijukuKatsushika Ku Tokyo 1258585 Japan Tokyo Univ Agr & Technol Inst Engn 2-24-16 Naka Cho Koganei Tokyo 1848588 Japan

With the development of 5G technology and the proliferation of IoT devices, Deep joint source-channel coding (DeepJSCC) has attracted attention for efficiently transmitting video and image data. DeepJSCC can maintain a good peak signal-to-noise ratio (PSNR) of images even at a meager signal-to-noise ratio (SNR). In cellular communication systems, the compression ratio must adapt to channel fluctuations, requiring multiple training models at the base station. However, the optimal SNR and compression ratio combination during training has yet to be reported. This paper investigates the necessary number of training models by stepwise varying SNR and compression ratio during training.

关键词： 5G joint source-channel coding deep learning semantic com- munication image transmission

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ANALOG joint source-channel coding IN RAYLEIGH FADING channelS

ANALOG JOINT SOURCE-CHANNEL CODING IN RAYLEIGH FADING CHANNE...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Glauber Gomes de Oliveira Brante Richard Demo Souza Javier Garcia-Frias CPGEI Federal University of Technology-Parana (UTFPR) Curitiba Brazil Dept. of ECE University of Delaware DE USA

ISBN: (纸本)9781457705380

We consider discrete-time all-analog-processing joint source-channel coding, using non-linear spiral-like curves. We assume a Rayleigh channel, where the receiver may employ or not multiple antennas. Maximum Likelihood (ML) and Minimum Mean Square Error (MMSE) detection are considered. Our results show that MMSE performs much better than ML in high CSNR in single-antenna wireless systems, while diversity combining is able to significantly reduce such performance gap, therefore making the low complexity ML decoding very attractive in the case of multiple receive antennas.

关键词： joint source-channel coding wireless channel receive diversity analog coding

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Rate-Distortion Optimized joint source/channel coding of WWAN Multicast Video for A Cooperative Peer-to-Peer Collective

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2011年第1期21卷 39-52页

作者： Liu, Leo X. Cheung, Gene Chuah, Chen-Nee Cisco Syst San Jose CA 95134 USA Natl Inst Informat Tokyo 1018430 Japan Univ Calif Davis Dept Elect & Comp Engn Davis CA 95616 USA

Because of unavoidable wireless packet losses and inapplicability of retransmission-based schemes due to the well-known negative acknowledgment implosion problem, providing high quality video multicast over wireless wide area networks (WWAN) remains difficult. Traditional joint source/channel coding (JSCC) schemes for video multicast target a chosen nth-percentile WWAN user. Users with poorer reception than nthpercentile user (poor users) suffer substantial channel losses, while users with better reception (rich users) have more channel coding than necessary, resulting in sub-optimal video quality. In this paper, we recast the WWAN JSCC problem in a new setting called cooperative peer-to-peer repair (CPR), where users have both WWAN and wireless local area network (WLAN) interfaces and use the latter to exchange received WWAN packets locally. Given CPR can mitigate some WWAN losses via cooperative peer exchanges, a CPR-aware JSCC scheme can now allocate more bits to source coding to minimize source quantization noise without suffering more packet losses, leading to smaller overall visual distortion. Through CPR, this quality improvement is in fact reaped by all peers in the collective, not just a targeted nth-percentile user. To efficiently implement both WWAN forward error correction and WLAN CPR repairs, we propose to use network coding for this dual purpose to reduce decoding complexity and maximize packet recovery at the peers. We show that a CPR-aware JSCC scheme dramatically improves video quality: by up to 8.7 dB in peak signal-to-noise ratio for the entire peer group over JSCC scheme without CPR, and by up to 6.0 dB over a CPR-ignorant JSCC scheme with CPR.

关键词： Cooperative peer-to-peer repair joint source-channel coding network coding

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A low-complexity rate allocation algorithm for joint source-channel video coding

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2009年第5期24卷 368-383页

作者： Milani, Simone Calvagno, Giancarlo Univ Padua Dept Informat Engn I-35131 Padua Italy

The problem of enabling robust video transmission over lossy networks has become increasingly important because of the growing interest in video delivery over unreliable channels such as wireless networks. The more the coding process relies on an intensive use of prediction to improve the coding gain, the more the reconstructed sequence proves to be sensitive to information losses. As a matter of fact, it is necessary to introduce some redundant data in order to increase the robustness of the coded bit stream. A possible solution can be found filling a matrix structure with RTP packets and applying a Forward Error Correction (FEC) code on its rows. However, the matrix size and the chosen FEC code affect the performance of the coding system. The paper proposes a novel adaptation technique that tunes the amount of redundant information included in the packet stream and differs from previously proposed solutions since it relies on the percentage of null quantized transform coefficients in place of the activity or the Mean Square Error (MSE). This strategy is then integrated in a joint source-channel coder rate allocation algorithm that shares the available bits between the H.264/AVC coder and the channel coder according to the significance of the frame in the decoding process. Experimental results show that the presented approach significantly improves the quality of the reconstructed sequences at the decoder with respect to activity-based strategies and requires a low computational complexity. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Video coding H.264/AVC joint source-channel coding Bit allocation R-D parameterization Low complexity

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joint source-channel turbo coding for binary Markov sources

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2006年第5期5卷 1065-1075页

作者： Zhu, Guang-Chong Alajaji, Fady Lawrence Technol Univ Dept Math & Comp Sci Southfield MI 48075 USA Queens Univ Dept Math & Stat Kingston ON Canada Queens Univ Dept Elect & Comp Engn Kingston ON Canada

We investigate the construction of joint source-channel (JSC) Turbo codes for the reliable communication of binary Markov sources over additive white Gaussian noise and Rayleigh fading channels. To exploit the source Markovian redundancy, the first constituent Turbo decoder is designed according to a modified version of Berrou's original decoding algorithm that employs the Gaussian assumption for the extrinsic information. Due to interleaving, the second constituent decoder is unable to adopt the same decoding method;so its extrinsic information is appropriately adjusted via a weighted correction term. The Turbo encoder is also optimized according to the Markovian source statistics and by allowing different or asymmetric constituent encoders. Simulation results demonstrate substantial gains over the original (unoptimized) Turbo codes, hence significantly reducing the performance gap to the Shannon limit. Finally, we show that our JSC coding system considerably outperforms tandem coding schemes for bit error rates smaller than 10(-4), while enjoying a lower system complexity.

关键词： joint source-channel coding turbo codes AWGN and Rayleigh fading channels Shannon limit Markov sources iterative decoding bit error rate

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