Abstract | ||
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We study joint source-channel coding (JSCC) of compressed sensing (CS) measurements using vector quantizer (VQ). We develop a framework for realizing optimum JSCC schemes that enable encoding and transmitting CS measurements of a sparse source over discrete memoryless channels, and decoding the sparse source signal. For this purpose, the optimal design of encoder-decoder pair of a VQ is considered, where the optimality is addressed by minimizing end-to-end mean square error (MSE). We derive a theoretical lower bound on the MSE performance and propose a practical encoder-decoder design through an iterative algorithm. The resulting coding scheme is referred to as channel-optimized VQ for CS, coined COVQ-CS. In order to address the encoding complexity issue of the COVQ-CS, we propose to use a structured quantizer, namely low-complexity multistage VQ (MSVQ). We derive new encoding and decoding conditions for the MSVQ and then propose a practical encoder–decoder design algorithm referred to as channel-optimized MSVQ for CS, coined COMSVQ-CS. Through simulation studies, we compare the proposed schemes vis-à-vis relevant quantizers. |
Year | DOI | Venue |
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2014 | 10.1109/TSP.2014.2329649 | Signal Processing, IEEE Transactions |
Keywords | DocType | Volume |
combined source-channel coding,compressed sensing,iterative methods,mean square error methods,vector quantisation,COVQ-CS,channel-optimized MSVQ,discrete memoryless channels,encoder-decoder pair,end-to-end mean square error,iterative algorithm,joint source-channel coding,joint source-channel vector quantization,low-complexity multistage VQ,optimum JSCC schemes,practical encoder-decoder design algorithm,vector quantizer,Vector quantization,compressed sensing,joint source-channel coding,mean square error,multi-stage vector quantization,noisy channel,sparsity | Journal | 62 |
Issue | ISSN | Citations |
14 | 1053-587X | 5 |
PageRank | References | Authors |
0.40 | 24 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Amirpasha Shirazinia | 1 | 62 | 6.90 |
Saikat Chatterjee | 2 | 320 | 40.34 |
Mikael Skoglund | 3 | 1397 | 175.71 |