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source-channel-cooperation tradeoffs for adaptive coded communications

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2008年第9期7卷 3347-3358页

作者： Kwasinski, Andres Liu, K. J. Ray Rochester Inst Technol Rochester NY 14623 USA Univ Maryland College Pk MD 20742 USA

Transmit power limitations and quality-impairing channels present key challenges to wireless communications. A possible solution to these problems is the application of user-cooperation techniques so as to improve link quality. This paper studies the tradeoffs involved in combining user cooperation with practical source and channel coding in systems featuring rate-adaptive source and channel coding of conversational traffic. Performance is measured through the D-SNR curve, which measures the relation between end-to-end distortion and channel Signal-to-Noise Ratio (SNR). The D-SNR curve is accurately characterized as a linear function in log-log scales. Also, it is shown that the tradeoffs;involved in combining amplify-and-forward or decode-and-forward cooperation with source and channel coding translates into cooperative schemes showing a decrease in distortion at approximately half the rate as noncooperative schemes but with larger coding gain. Because of this, the studied non-cooperative schemes show better performance only at high SNR. In addition, the D-SNR characterization is used to compare amplify-and-forward and decode-and-forward cooperation for channel codes of different strength and to study the effects of source codec efficiency, where it is shown that diversity gain is reduced proportionally to the source codec loss of efficiency.

关键词： cooperative communications source coding channel coding joint source-channel coding

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The Distortions Region of Broadcasting Correlated Gaussians and Asymmetric Data Transmission Over a Gaussian BC

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IEEE TRANSACTIONS ON COMMUNICATIONS 2020年第4期68卷 2566-2578页

作者： Bross, Shraga I. Bar Ilan Univ Fac Engn IL-52900 Ramat Gan Israel

A memoryless bivariate Gaussian source is transmitted to a pair of receivers over an average-power limited bandwidth-matched Gaussian broadcast channel. Based on their observations, Receiver 1 reconstructs the first source component while Receiver 2 reconstructs the second source component both seeking to minimize the expected squared-error distortions. In addition to the source transmission digital information at a specified rate should be conveyed reliably to Receiver 1-the "stronger" receiver. Given the message rate we characterize the achievable distortions region. Specifically, there is an ${\sf SNR}$ -threshold below which Dirty Paper coding of the digital information against a linear combination of the source components is optimal. The threshold is a function of the digital information rate, the source correlation and the distortion at the "stronger" receiver. Above this threshold a Dirty Paper coding extension of the Tian-Diggavi-Shamai hybrid scheme is shown to be optimal.

关键词： Gaussian broadcast channel source broadcasting asymmetric data transmission joint source-channel coding

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Wireless Image Retrieval at the Edge

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2021年第1期39卷 89-100页

作者： Jankowski, Mikolaj Gunduz, Deniz Mikolajczyk, Krystian Imperial Coll London Dept Elect & Elect Engn London SW7 2BU England

We study the image retrieval problem at the wireless edge, where an edge device captures an image, which is then used to retrieve similar images from an edge server. These can be images of the same person or a vehicle taken from other cameras at different times and locations. Our goal is to maximize the accuracy of the retrieval task under power and bandwidth constraints over the wireless link. Due to the stringent delay constraint of the underlying application, sending the whole image at a sufficient quality is not possible. We propose two alternative schemes based on digital and analog communications, respectively. In the digital approach, we first propose a deep neural network (DNN) aided retrieval-oriented image compression scheme, whose output bit sequence is transmitted over the channel using conventional channel codes. In the analog joint source and channel coding (JSCC) approach, the feature vectors are directly mapped into channel symbols. We evaluate both schemes on image based re-identification (re-ID) tasks under different channel conditions, including both static and fading channels. We show that the JSCC scheme significantly increases the end-to-end accuracy, speeds up the encoding process, and provides graceful degradation with channel conditions. The proposed architecture is evaluated through extensive simulations on different datasets and channel conditions, as well as through ablation studies.

关键词： Image edge detection Servers Task analysis Wireless communication Performance evaluation Image coding Feature extraction Deep learning Internet of Things image retrieval joint source-channel coding person re-identification

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Adaptive Mode- and Diversity-Control for Video Transmission on MIMO Wireless channels

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2009年第9期57卷 3624-3637页

作者： Hormis, Raju Linzer, Elliot Wang, Xiaodong Analog Devices Inc High Speed Signal Proc Grp Somerset NJ 08873 USA Ambarella Sunnyvale CA 94089 USA Columbia Univ Dept Elect Engn New York NY 10027 USA

Video transmitted over wireless channels incurs both encoder-induced distortion and distortion caused by transmission errors. To address these problems, we propose a framework to transmit video reliably over a Rayleigh-fading wireless channel employing multiple transmit and receive antennas. Although the formulation makes no assumptions about specific video-coding standards, it does presuppose some variation of motion-compensated block-transform coding. The scheme proposed here minimizes cumulative distortion over a window spanning multiple video units, and does so by adaptively controlling the diversity-and multiplexing-gain of the multiple-input multiple-output (MIMO) system. Crucially, this is done jointly with loss-aware rate-distortion optimization (LA-RDO) techniques at the video encoder. It turns out that MIMO and LA-RDO techniques, working in tandem, are more effective in minimizing distortion. The framework also ensures that delay and buffer constraints are satisfied for real-time transport. Numerical results with H.264-coded video show that adaptive MIMO and LA-RDO control yield tangible benefits (PSNR improvement), but only up to a point. Beyond this, real-time and buffer constraints limit what can be gained, even when the number of antennas is increased. In terms of solution approach, we show that the problem can be modelled as a sequence of geometric programs. Each problem can be solved optimally by a class of convex techniques known as primal-dual algorithms.

关键词： Convex programming diversity-multiplexing tradeoff geometric programs H.264 joint source-channel coding MIMO systems rate-distortion video coding

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Total system energy minimization for wireless image transmission

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JOURNAL OF VLSI SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY 2001年第1-2期27卷 99-117页

作者： Appadwedula, S Goel, M Shanbhag, NR Jones, DL Ramchandran, K Univ Illinois Dept Elect & Comp Engn Coordinated Sci Lab Urbana IL 61801 USA Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA

In this paper, we focus on the total-system-energy minimization of a wireless image transmission system including both digital and analog components. Traditionally, digital power consumption has been ignored in system design, since transmit power has been the most significant component. However, as we move to an era of pico-cell environments and as more complex signal processing algorithms are being used at higher data rates, the digital power consumption of these systems becomes an issue. We present an energy-optimized image transmission system for indoor wireless applications which exploits the variabilities in the image data and the wireless multipath channel by employing dynamic algorithm transformations and joint source-channel coding. The variability in the image data is characterized by the rate-distortion curve, and the variability in the channel characteristics is characterized by the path-loss and impulse response of the channel. The system hardware configuration space is characterized by the error-correction capability of the channel encoder/decoder, number of powered-up fingers in the RAKE receiver, and transmit power of the power amplifier. An optimization algorithm is utilized to obtain energy-optimal configurations subject to end-to-end performance constraints. The proposed design is tested over QCIF images, IMT-2000 channels and 0.18 mum, 2.5 V CMOS technology parameters. Simulation results over various images, various distances, two different channels, and two different rates show that the average energy savings in utilizing a total-system-energy minimization over a fixed system (designed for the worst image, the worst channel and the maximum distance) are 53.6% and 67.3%, respectively, for short-range (under 20 m) and long-range (over 20 m) systems.

关键词： joint source-channel coding low power indoor wireless transmission energy minimization

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Analysis of video transmission over lossy channels

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2000年第6期18卷 1012-1032页

作者： Stuhlmüller, K Färber, N Link, M Girod, B Univ Erlangen Nurnberg Telecommun Lab D-91058 Erlangen Germany Lucent Technol Nurnberg Germany Stanford Univ Informat Syst Lab Stanford CA 94305 USA

A theoretical analysis of the overall mean squared error (MSE) in hybrid video coding is presented for the case of error prone transmission. Our model covers the complete transmission system including the rate-distortion performance of the video encoder, forward error correction, interleaving, and the effect of error concealment and interframe error propagation at the video decoder. The channel model used is a 2-state Markov model describing burst errors on the symbol level. Reed-Solomon codes are used for forward error correction. Extensive simulation results using an H.263 video codec are provided for verification. Using the model, the optimal tradeoff between INTRA and INTER coding as well as the optimal channel code rate can be determined for given channel parameters by minimizing the expected MSE at the decoder. The main focus of this paper is to show the accuracy of the derived analytical model and its applicability to the analysis and optimization of an entire video transmission system.

关键词： error resilience intra-update joint source-channel coding robust video transmission tradeoff source-channel coding video transmission system model

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Real-time unequal error protection algorithms for progressive image transmission

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2003年第10期21卷 1526-1535页

作者： Stankovic, VM Hamzaoui, R Charfi, Y Xiong, ZX Texas A&M Univ Dept Elect Engn College Stn TX 77843 USA Univ Konstanz Dept Comp & Informat Sci D-78457 Constance Germany

We consider unequal error protection strategies for the efficient progressive transmission of embedded image codes over noisy channels. In progressive transmission, the reconstruction quality is important not only at the target transmission rate but also at the intermediate rates. An adequate error protection strategy may, thug, consist of optimizing the average performance over the set of intermediate rates. The performance can be the expected number of correctly decoded source bits or the expected distortion. For the rate-based performance, we prove some interesting properties of an optimal solution and give an optimal linear-time algorithm to compute it. For the distortion-based performance, we propose an efficient linear-time local search algorithm. For a binary symmetric channel, two state-of-the-art source coders (SPIHT and JPEG2000), we compare the progress give ability of our proposed solutions to that of the strategies that optimize the end-to-end performance of the system. Experimental results showed that the proposed solutions had a slightly worse performance at the target transmission rate and a better performance at most of the intermediate rates, especially at the lowest ones.

关键词： joint source-channel coding progressive transmission unequal error protection

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Globally optimal uneven error-protected packetization of scalable code streams

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IEEE TRANSACTIONS ON MULTIMEDIA 2004年第2期6卷 230-239页

作者： Dumitrescu, S Wu, XL Wang, Z McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4K1 Canada

In this paper, we present a family of new algorithms for rate-fidelity optimal packetization of scalable source bit streams with uneven error protection. In the most general setting where no assumption is made on the probability function of packet loss or on the rate-fidelity function of the scalable code stream, one of our algorithms can find the globally optimal solution to the problem in O((NL2)-L-2) time, compared to a previously obtained O((NL2)-L-3) complexity, where N is the number of packets and L is the packet payload size. If the rate-fidelity function of the input is convex, the time complexity can be reduced to O(NL2) for a class of erasure channels, including channels for which the probability function of losing n packets is monotonically decreasing in n and independent erasure channels with packet erasure rate no larger than N/2(N + 1). Furthermore, our O (N L-2) algorithm for the convex case can be modified to find an approximation solution for the general case. All of our algorithms do away with the expediency of fractional bit allocation, a limitation of some existing algorithms.

关键词： joint source-channel coding multimedia streaming optimization uneven error protection

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CDDM: channel Denoising Diffusion Models for Wireless Semantic Communications

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2024年第9期23卷 11168-11183页

作者： Wu, Tong Chen, Zhiyong He, Dazhi Qian, Liang Xu, Yin Tao, Meixia Zhang, Wenjun Shanghai Jiao Tong Univ Cooperat Medianet Innovat Ctr CMIC Shanghai 200240 Peoples R China Shanghai Key Lab Digital Media Proc & Transmiss Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China

Diffusion models (DM) can gradually learn to remove noise, which have been widely used in artificial intelligence generated content (AIGC) in recent years. The property of DM for eliminating noise leads us to wonder whether DM can be applied to wireless communications to help the receiver mitigate the channel noise. To address this, we propose channel denoising diffusion models (CDDM) for semantic communications over wireless channels in this paper. CDDM can be applied as a new physical layer module after the channel equalization to learn the distribution of the channel input signal, and then utilizes this learned knowledge to remove the channel noise. We derive corresponding training and sampling algorithms of CDDM according to the forward diffusion process specially designed to adapt the channel models. We also theoretically prove that the well-trained CDDM can effectively reduce the conditional entropy of the received signal under small sampling steps. Moreover, we apply CDDM to a semantic communications system based on joint source-channel coding (JSCC) for image transmission and design a three-stage training algorithm for combining them. Extensive experimental results demonstrate that CDDM can further reduce the mean square error (MSE) after minimum mean square error (MMSE) equalizer, and the joint CDDM and JSCC system achieves better performance than the JSCC system, the traditional JPEG2000 with low-density parity-check (LDPC) code approach and other benchmarks in diverse scenarios.

关键词： Wireless communication Semantics Decoding Generative adversarial networks channel estimation Adaptation models Image communication Diffusion models wireless image transmission semantic communications joint source-channel coding

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channel-optimized quantizers for decentralized detection in sensor networks

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IEEE TRANSACTIONS ON INFORMATION THEORY 2006年第7期52卷 3349-3358页

作者： Liu, Bin Chen, Biao Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

Motivated by the delay and resource constraints omnipresent in most wireless sensor network applications, we design channel-optimized scalar quantizers for a canonical decentralized detection system. Aimed at minimizing the error probability of the fusion center output, we first establish the optimality of monotone likelihood ratio partition of the observation space for the local quantizer design. We then devise an iterative algorithm to construct distributed quantizers that are person-by-person optimal. The channel-optimized approach is shown to offer better performance compared with various alternatives. It also exhibits inherent adaptivity in resource (bit) allocation in response to varying channel conditions.

关键词： channel-optimized quantizer distributed detection distributed signal processing joint source-channel coding sensor networks

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