In this paper, we study jointsourcechannelcoding 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) t...
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In this paper, we study jointsourcechannelcoding 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.
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) o...
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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.
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...
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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.
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) detectio...
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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.
jointsource-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 ...
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jointsource-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.
In this letter, we propose a joint source-channel coding scheme based on polarizing matrix extension (PME-JSCC). The PME-JSCC can combine channel received signal and source side information to form a longer polar code...
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In this letter, we propose a joint source-channel coding scheme based on polarizing matrix extension (PME-JSCC). The PME-JSCC can combine channel received signal and source side information to form a longer polar code. We extend the source encoding matrix and place channel bits on the extended bits. Due to the lower triangular structure of the polarizing matrix, source bits will not be changed by channel bits. The PME-JSCC can obtain enhanced jointsource-channel polarization (JSCP) effect. This effect enhances the reliabilities of both channel bits and source encoded bits simultaneously. The bound on the block error probability for PME-JSCC is improved. And the PME-JSCC can be proved to reach the fundamental limit on JSCC. Simulation results show that the PME-JSCC scheme outperforms the DP-LDPC and the D-Polar codes under the joint successive cancellation list (J-SCL) decoder and can approximate the JSCC finite length bound in the short blocklength regime.
Reliable transmission of a pair of arbitrarily correlated sources over a discrete memoryless cognitive radio channel is studied. We derive a sufficient condition for lossless transmission of such communication scenari...
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Reliable transmission of a pair of arbitrarily correlated sources over a discrete memoryless cognitive radio channel is studied. We derive a sufficient condition for lossless transmission of such communication scenario using superposition coding, correlation preserving technique, random source partition, a binning scheme and joint typicality decoding. This sufficient condition reduces to the known rate regions for interference channels with independent, specially correlated and arbitrarily correlated sources.
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.
The bivariate Gaussian multiterminal sourcecoding problem with transmission over the Gaussian multiple-access channel is studied. We propose the use of low-delay jointsource-channel mappings and show how performance...
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The bivariate Gaussian multiterminal sourcecoding problem with transmission over the Gaussian multiple-access channel is studied. We propose the use of low-delay jointsource-channel mappings and show how performance saturation, which is unavoidable with linear transmission, can be overcome by optimizing the mappings. The optimized mappings are in general nonlinear and perform a combination of hard and soft decision signaling for the error-resilient transmission of analog data.
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.
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