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Computation over multiple-access channels

IEEE TRANSACTIONS ON INFORMATION THEORY 2007年第10期53卷 3498-3516页

作者： Nazer, Bobak Gastpar, Michael Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA

The problem of reliably reconstructing a function of sources over a multiple-access channel (MAC) is considered. It is shown that there is no source-channel separation theorem even when the individual sources are independent. joint source-channel strategies are developed that are optimal when the structure of the channel probability transition matrix and the function are appropriately matched. Even when the channel and function are mismatched, these computation codes -often outperform separation-based strategies. Achievable distortions are given for the distributed refinement of the sum of Gaussian sources over a Gaussian multiple-access channel with a joint source-channel lattice code. Finally, computation codes are used to determine the multicast capacity of finite-field multiple-access networks, thus linking them to network coding.

关键词： distributed computation joint source-channel coding lattice codes linear codes multiple-access channel (MAC) network coding separation theorem

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joint turbo decoding and estimation of hidden Markov sources

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2001年第9期19卷 1671-1679页

作者： Garcia-Frias, J Villasenor, JD Univ Delaware Dept Elect & Comp Engn Newark DE 19716 USA Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90024 USA

We describe a joint source-channel scheme for modifying a turbo decoder in order to exploit the statistical characteristics of hidden Markov sources. The basic idea is to treat the trellis describing the hidden Markov source as another constituent decoder which exchanges information with the other constituent decoder blocks. The source block uses as extrinsic information the probability of the input bits that is provided by the constituent decoder blocks. On the other hand, it produces a new estimation of such a probability which will be used as extrinsic information by the constituent turbo decoders. The proposed joint source-channel decoding technique leads to significantly improved performance relative to systems in which source statistics are not exploited and avoids the need to perform any explicit source coding prior to transmission. Lack of a priori knowledge of the source parameters does not degrade the performance of the system, since these parameters can be jointly estimated with turbo decoding.

关键词： Baum-Welch algorithm hidden Markov sources iterative decoding joint source-channel coding turbo codes

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Error-resilient surveillance video transmission based on a practical joint source-channel distortion computing model

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JOURNAL OF SUPERCOMPUTING 2017年第3期73卷 1017-1043页

作者： Jung, Tae-jun Jeong, Yo-Won Lee, Hong-rae Seo, Kwang-deok Yonsei Univ Div Comp & Telecommun Engn Wonju Gangwon South Korea Samsung Elect Corp Digital Media & Commun R&D Ctr Suwon Gyeonggi South Korea

In recent years, IP (Internet Protocol)-based video surveillance has widely been useful for post-event analysis and assisting the work of privacy protection and public safety. To support high-quality IP video surveillance, error-resilience techniques are important for surveillance system design, because video has more stringent requirements than general video transmission for packet loss, latency, and jitter. The optimal FEC (forward error correction) code rate decision is a crucial procedure to determine the optimal source and channel coding rates to minimize the overall picture distortion when transporting video packets over packet loss channels. The conventional FEC code rate decision schemes using an analytical source-coding distortion model and a channel-induced distortion model are usually complex and typically employ the process of model parameter training, which involves potentially high computational complexity and implementation cost. To avoid the complex modeling procedure, we propose a simple but accurate joint source-channel distortion model to estimate the channel-loss threshold set for optimal FEC code rate decision. Since the proposed model is expressed as a simple closed form and has a small number of scene-dependent model parameters, a video sender of the surveillance system using the model can be easily implemented. For training the scene-dependent model parameters in real time, we propose a practical test-run procedure. This method accelerates the test-run while maintaining its accuracy for training the scene-dependent model parameters. Using the proposed simple model and practical test-run method, the video sender can find the optimal code rate for on-the-fly joint source-channel coding whenever there is a change in the packet-loss condition in the channel. Simulations show that the proposed method can accurately estimate the channel loss threshold set, resulting in an optimal FEC code rate with low computational complexity.

关键词： FEC code rate decision Forward error correction Error-resilient surveillance video transmission joint source-channel coding

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Performances of linear tools and models for error detection and concealment in subband image transmission

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2002年第5期11卷 518-529页

作者： Labeau, F Desset, C Vandendorpe, L Macq, B McGill Univ Dept Elect & Comp Engn Montreal PQ H3A 2A7 Canada Catholic Univ Louvain Commun & Remote Sensing Lab Louvain Belgium

In this paper, we investigate the performances of Gaussian modeling and linear prediction tools for error detection and concealment in the transmission of still images. We consider the transmission of subband encoded images through two types of channels. We model the residual correlation between subband coefficients by considering them as jointly Gaussian variables. The first transmission medium considered is a packet-oriented channel, where some packets are lost during transmission. The problem is to estimate the values of missing coefficients. In this case, particular care must be taken while evaluating correlation matrices from incomplete data. The other system considered is based on a discrete memoryless noisy channel affecting the data being transmitted. The challenge is here first to determine the locations of the errors-which is done through hypotheses tests-and then to replace them by estimates based on their neighbors. The reconstruction via linear prediction is shown to give better results than median filtering based reconstruction. Error detection through this Gaussian model also shows promising results, in particular when channel statistics are taken into account in a joint source-channel decoding framework.

关键词： error detection and concealment joint source-channel coding residual redundancy

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joint mode selection and unequal error protection for bitplane coded video transmission over wireless channels

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2005年第4-5期16卷 412-431页

作者： Cai, JF Wu, JH Ngan, KN He, ZH Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore Chinese Univ Hong Kong Dept Elect Engn Hong Kong Hong Kong Peoples R China Univ Missouri Dept Elect Engn Columbia MO 65211 USA

In this paper, we study joint source channel coding for bitplane based video coding over wireless channels. We consider using frame-level intra-mode to stop error propagation and using unequal error protection (UEP) to combat channel errors. Our focus is on how to optimally select coding modes and find UEP solutions for bitplane based video coding. In particular, we propose an overall end-to-end rate-distortion (R-D) function, which considers not only the source distortion and the channel distortion introduced in the current frame but also the propagated channel distortion from the previous frames. Based on this end-to-end R-D function, we are able to find the optimal solutions for both mode selection and UEP so that an optimal tradeoff between efficiency and robustness can be achieved. Experimental results demonstrate the significant performance gain. (c) 2005 Elsevier Inc. All rights reserved.

关键词： joint source-channel coding bitplane based video coding mode selection unequal error protection wireless video fine granularity scalability

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Iterative joint source-channel decoding of variable-length codes using residual source redundancy

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2005年第3期4卷 919-929页

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

We present a novel symbol-based soft-input a posteriori probability (APP) decoder for packetized variable-length encoded source indexes transmitted over wireless channels where the residual redundancy after source encoding is exploited for error protection. In combination with a mean-square or maximum APP estimation of the reconstructed source data, the whole decoding process is close to optimal. Furthermore, solutions for the proposed APP decoder with reduced complexity are discussed and compared to the near-optimal solution. When, in addition, channel codes are employed for protecting the variable-length encoded data, an iterative source-channel decoder can be obtained in the same way as for serially concatenated codes, where the proposed APP source decoder then represents one of the two constituent decoders. The simulation results show that this iterative decoding technique leads to substantial error protection for variable-length encoded correlated source signals, especially, when they are transmitted over highly corrupted channels.

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

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Design of Code Pair for Protograph-LDPC Codes-Based JSCC System With joint Shuffled Scheduling Decoding Algorithm

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IEEE COMMUNICATIONS LETTERS 2021年第12期25卷 3770-3774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 Xiamen Univ Shenzhen Res Inst Shenzhen 518057 Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong 999077 Peoples R China

Although there are many studies on code optimization of the joint source-channel coding (JSCC) system based on double protograph low-density parity-check codes with the joint belief propagation (JBP) algorithm, but it is still unknown whether the source code and channel code (as a code pair) can perform well when the joint shuffled scheduling decoding (JSSD) algorithm is adopted. In this letter, two decoding threshold analysis algorithms, including joint shuffled protograph extrinsic information transfer (PEXIT) and source shuffled PEXIT algorithm, are proposed to calculate joint/source decoding thresholds for this system with the JSSD algorithm. With the proposed algorithms, it is found that the optimized code pairs for this system with the JBP algorithm may not perform well with the JSSD algorithm, implying that code pair with the JSSD algorithm needs to be redesigned. Then, a two-stage optimized framework is proposed to design the code pair for this system with the JSSD algorithm. Simulations and decoding threshold analysis both show that the proposed code pair for this system with the JSSD algorithm can obtain lower error floor and better waterfall performance than the existing code pairs.

关键词： Decoding Parity check codes Scheduling Tools Entropy source coding channel coding Protograph LDPC code joint source-channel coding shuffled scheduling decoding PEXIT analysis

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Transmission Energy Allocation with Low Peak-to-Average Ratio

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IEEE COMMUNICATIONS LETTERS 1997年第6期1卷 166-168页

作者： Gadkari, Shrinivas Rose, Kenneth Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

Transmission energy allocation (TEA) to bits according to their sensitivity is known to significantly enhance robustness to channel errors. These advantages are gained at the cost of high peak-to-average ratio (PAR) of the signal energy employed to transmit different bits. We show that, in the case of 4-QAM, appropriate grouping of bits allows achieving all the gains of optimal TEA while maintaining PAR at a small fraction of a decibel. Alternatively, we show how to achieve close to optimal TEA under the constraint of perfect (0 dB) PAR, thus extending the application of TEA to constant envelope modulation schemes. Performance is illustrated with an example of Gauss-Markov sources compressed by vector quantization.

关键词： joint source-channel coding peak-to-average ratio quadrature amplitude modulation vector quantization

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Binary Signaling of Correlated sources Over Orthogonal Multiple-Access channels

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IEEE WIRELESS COMMUNICATIONS LETTERS 2015年第5期4卷 501-504页

作者： Mitchell, Tyson P. Alajaji, Fady Linder, Tamas Queens Univ Dept Math & Stat Kingston ON K7L 3N6 Canada

The optimal energy allocations for minimizing the joint symbol error rate for binary signaling of two correlated sources over the orthogonal multiple-access Gaussian channel under joint maximum a priori (MAP) detection are determined. An exact expression for the system's probability of joint symbol error, as well as its union bound, is derived. Analytic minimization of the union bound reveals that the optimal energy allocation coincides with that of nonuniform binary signaling over the single-user additive white Gaussian noise channel. It is also shown numerically that the optimal energies that minimize the union bound also minimize the exact probability of error. Finally, it is shown via simulations for strongly biased sources that the use of joint MAP detection over two independent single-user systems leads to significant gains.

关键词： Error analysis joint source-channel coding MAP detection multiple-access channels nonuniform sources

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Improved image decoding over noisy channels using minimum mean-squared estimation and a Markov mesh

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1999年第6期8卷 863-867页

作者： Park, MS Miller, DJ Penn State Univ Dept Elect Engn University Pk PA 16802 USA

joint source-channel (JSC) decoding based on residual source redundancy is a technique for providing channel robustness to quantized data. Previous work assumed a model equivalent to viewing the encoder/noisy channel tandem as a discrete hidden Markov model (HMM) with transmitted indices the hidden, states. Here, me generalize this HMM-based (I-D) approach for images, using the more powerful hidden Markov mesh random field (HMMRF) model. While previous state estimation methods for HMMRF's base estimates on only a causal subset of the observed data, our new method uses both causal and anticausal subsets. For JSC-based image decoding, the new method provides significant benefits over several competing techniques.

关键词： hidden Markov models image coding joint source-channel coding least mean square methods Markov mesh model

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