Multiple Descriptions With Symbol Based Turbo Codes Over Noisy Channels With Packet Loss: Design and Performance Analysis

Valipour, Mehrdad; Lahouti, Farshad

doi:10.1109/jstsp.2008.922511

Cited by 2 publications

(1 citation statement)

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“…The design of a MD vector quantizer using deterministic annealing [17] is presented in [18], and based on simulated annealing in [19]. Recently, the design of multiple descriptions over noisy channels with and without PL has received noticeable attention, e.g., [20][21].…”

Section: Introductionmentioning

confidence: 99%

Channel Optimized Distributed Multiple Description Coding

Valipour

Lahouti

2012

IEEE Trans. Signal Process.

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In this paper, channel optimized distributed multiple description vector quantization (CDMD) schemes are presented for distributed source coding in symmetric and asymmetric settings. The CDMD encoder is designed using a deterministic annealing approach over noisy channels with packet loss. A minimum mean squared error asymmetric CDMD decoder is proposed for effective reconstruction of a source, utilizing the side information (SI) and its corresponding received descriptions. The proposed iterative symmetric CDMD decoder jointly reconstructs the symbols of multiple correlated sources. Two types of symmetric CDMD decoders, namely the estimated-SI and the soft-SI decoders, are presented which respectively exploit the reconstructed symbols and a posteriori probabilities of other sources as SI in iterations. In a multiple source CDMD setting, for reconstruction of a source, three methods are proposed to select another source as its SI during the decoding. The methods operate based on minimum physical distance (in a wireless sensor network setting), maximum mutual information and minimum end-to-end distortion. The performance of the proposed systems and algorithms are evaluated and compared in detail.EDICS: SEN-DCSC Distributed channel and source coding 2

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