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.
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 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.
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