We propose a joint source-channel coding scheme for wireless communication systems with multiple transmit and receive antennas. The source coder is realized by a multiple description encoder that generates multiple bi...
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We propose a joint source-channel coding scheme for wireless communication systems with multiple transmit and receive antennas. The source coder is realized by a multiple description encoder that generates multiple bit streams. Each description is then separately turbo coded and transmitted using multiple antennas. For the receiver, we describe a suitable iterative jointsource-channel decoding technique that exploits the correlations between the descriptions. We present several examples that illustrate the performance of the proposed system, and compare it with other approaches.
We propose a novel distortion minimization technique for the transmission of a packetized progressive bitstream. The optimality of our proposed algorithm is analytically proved for a class of sources satisfying a stat...
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We propose a novel distortion minimization technique for the transmission of a packetized progressive bitstream. The optimality of our proposed algorithm is analytically proved for a class of sources satisfying a stated condition. It is shown that Gauss-Markov sources belong to the latter class for which the algorithm is optimal. We show that our proposed optimization technique is robust and has a linear complexity in the transmission rate. Simulation results show the effectiveness of our proposed algorithm.
In this letter, we propose a soft-decoding method for quantized overcomplete frame expansions that are binary transmitted through noisy channels. The frame expansions can be viewed as real-valued block codes that are ...
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In this letter, we propose a soft-decoding method for quantized overcomplete frame expansions that are binary transmitted through noisy channels. The frame expansions can be viewed as real-valued block codes that are directly applied to waveform signals prior to quantization. The explicit redundancy introduced in the continuous amplitude domain is exploited by the decoder in two stages. First, the index-based redundancy is used by a soft-input soft-output source decoding approach that outputs decoded symbols together with their reliability information. In a second stage, the soft information on the symbols and the structure of the introduced redundancy are used to correct errors. The performance of the proposed approach is evaluated for different code constructions based on the discrete Fourier transform (DFT), the discrete cosine transform (DCT), and the discrete Hadamard transform (DHT), and is compared to standard approaches without soft decoding.
In this correspondence, we consider a problem of optimal source, channelcoding rate pair allocation over a wireless link based on the channel fading state and the queue length of the transmitter. The source is delay ...
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In this correspondence, we consider a problem of optimal source, channelcoding rate pair allocation over a wireless link based on the channel fading state and the queue length of the transmitter. The source is delay sensitive. Therefore, our objective is to minimize the mean delay under given mean power and distortion constraints. We show that by jointly optimizing the source and channel rates, one can gain substantially in performance as compared to only source or channel rate optimization, as is usually considered in the literature. This is shown for single user, single-input-single-output (SISO), multiple-input-multiple-output (MIMO), and multiuser systems. The methods used are from Markov decision theory.
The problem of efficient video communications over multiple-input-multiple-output (MIMO) wireless systems is of great significance due to the high capacity of the multiple antenna system. The high data rates provided ...
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The problem of efficient video communications over multiple-input-multiple-output (MIMO) wireless systems is of great significance due to the high capacity of the multiple antenna system. The high data rates provided by the MIMO system can be traded off with diversity gain by using different channel-coding schemes. Also, by using different video source-coding methods, high compression gain can be traded off with the error resilience gain. One should jointly consider sourcecoding and channelcoding when designing a MIMO wireless video system. However, little is known so far about what combinations of channel-coding and source-coding methods have the best overall performance in a MIMO system. In this paper, by comparing the performances of several different typical combinations through both theoretical and simulation studies, we show that no single combination is the best for the entire range of channel conditions, but rather, different combinations may be best for a subrange.
This paper proposes a unified framework for addressing progressive image transmission over noisy channels based on the finite-state Markov channel (FSMC) model. FSMC models are simple yet general enough to model binar...
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This paper proposes a unified framework for addressing progressive image transmission over noisy channels based on the finite-state Markov channel (FSMC) model. FSMC models are simple yet general enough to model binary symmetric, Gilbert-Elliott, and fading channels. They Allow error sequence analysis that facilitates quantifying the statistical characteristics of the embedded bitstreams transmitted over FSMC in closed form. Using a concatenation of rate-compatible puncturing convolutional code and cyclic redundancy check code for error protection, we use a concatenation of rate-compatible punctured convolutional code and cyclic redundancy check code for error protection, which results in an unequal error protection (UEP) system, and find (sub-)optimal rate allocation solutions for our setup. By mapping fading channels to FSMCs, the JSCC problem is thus solved without the burden of simulations using an image-dependent lookup table. Fast algorithms are proposed to search for the optimal UEP. Experiments on embedded image bitstreams over FSMCs confirm our analytical results.
We consider the problem of obtaining channel state information (CSI) via a fast feedback link for transmission on the downlink of a multiuser MIMO system. We examine the relative merits of channel feedback schemes bas...
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We consider the problem of obtaining channel state information (CSI) via a fast feedback link for transmission on the downlink of a multiuser MIMO system. We examine the relative merits of channel feedback schemes based on Shannon's source-channel separation principle (digital schemes) and non-separation based schemes and show that the latter are preferable in this application when small to moderate bandwidth expansion ratios are used as in many current cellular systems. For comparison, we first compute upper-bounds on the performance of the system as a function of SNR. For the non-separation based schemes, we first consider a simple analog transmission and then develop a hybrid digital-analog transmission scheme which quantizes the CSI using a few bits and sends these bits and also the quantization error using analog transmission. We show that the hybrid scheme achieves a higher throughput compared to both analog and digital transmissions and has a much lower computational complexity compared to a digital scheme.
This paper proposes an unequal error protection (UEP) scheme for transporting scalable video packets over packet-lossy peer-to-peer networks. In our scheme, given an estimated system uplink capacity, a receiver-driven...
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This paper proposes an unequal error protection (UEP) scheme for transporting scalable video packets over packet-lossy peer-to-peer networks. In our scheme, given an estimated system uplink capacity, a receiver-driven joint source-channel coding (JSCC) mechanism is proposed by which each child-peer minimizes the received visual distortion by subscribing to appropriate numbers of source and channelcoding packets. Because the bandwidth for inter-peer transmissions may fluctuate largely due to peer dynamics, in our method, a peer estimates the available system uplink capacity based on consensus propagation to avoid the fluctuating allocations of JSCC. To efficiently utilize the uplink bandwidth of peers, parent-peers utilize sender-driven contribution-guided peer selection to reject the low-contribution subscriptions requested from candidate child-peers. Simulation results demonstrate that our method significantly improves the visual quality, compared to other state-of-the-art schemes. (C) 2016 Elsevier Inc. All rights reserved.
Several recent publications have shown that jointsource-channel decoding could be a powerful technique to take advantage of residual source redundancy for fixed- and variable-length source codes. This letter gives an...
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Several recent publications have shown that jointsource-channel decoding could be a powerful technique to take advantage of residual source redundancy for fixed- and variable-length source codes. This letter gives an in-depth analysis of a low-complexity method recently proposed by Guivarch et al, where the redundancy left by a Huffman encoder is used at a bit level in the channel decoder to improve its performance. Several simulation results are presented, showing for two first-order Markov sources of different sizes that using a priori knowledge of the source statistics yields a significant improvement, either with a Viterbi channel decoder or with a turbo decoder.
We consider the problem of learned speech transmission. Existing methods have exploited joint source-channel coding (JSCC) to encode speech directly to transmitted symbols to improve the robustness over noisy channels...
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We consider the problem of learned speech transmission. Existing methods have exploited joint source-channel coding (JSCC) to encode speech directly to transmitted symbols to improve the robustness over noisy channels. However, the fundamental limit of these methods is the failure of identification of content diversity across speech frames, leading to inefficient transmission. In this paper, we propose a novel neural speech transmission framework named NST. It can be optimized for superior rate-distortion-perception (RDP) performance toward the goal of high-fidelity semantic communication. Particularly, a learned entropy model assesses latent speech features to quantify the semantic content complexity, which facilitates the adaptive transmission rate allocation. NST enables a seamless integration of the source content with channel state information through variable-length joint source-channel coding, which maximizes the coding gain. Furthermore, we present a streaming variant of NST, which adopts causal coding based on sliding windows. Experimental results verify that NST outperforms existing speech transmission methods including separation-based and JSCC solutions in terms of RDP performance. Streaming NST achieves low-latency transmission with a slight quality degradation, which is tailored for real-time speech communication.
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