Joint channel decoding with feedback power control in sensor networks with correlated sources
ABSTRACT In this paper, we derive feedback power control strategies for block-faded multiple access schemes with correlated sources. In particular, upon the derivation of the feasible signal-to-noise ratio (SNR) region for the considered multiple access schemes, i.e., the multidimensional SNR region where error-free communications are, in principle, possible, two feedback power control strategies are proposed: (i) a ldquoclassicalrdquo feedback power control strategy, which aims at ldquoequalizingrdquo the SNRs at the AP over all communication links, and (ii) an ldquooptimalrdquo feedback power control strategy, which tries to make the network operational point fall in the feasible SNR region at the lowest energy consumption. These strategies will be referred to as balanced SNR and unbalanced SNR, respectively. While they require unlimited power control range at the sources (the sensors), we then propose ldquopracticalrdquo implementations by limiting the power control range. We evaluate the benefits brought by the use of the proposed feedback power control strategies considering joint channel decoding (JCD) schemes, where the sensors use channel coding and a proper iterative decoding algorithm is considered at the AP. The analysis is carried out considering the use of low-density parity-check (LDPC) codes and a serially concatenated convolutional code (SCCC).
- SourceAvailable from: Gianluigi Ferrari[Show abstract] [Hide abstract]
ABSTRACT: In this paper, we consider multiple access schemes with correlated sources. Distributed source coding is not used; rather, the correlation is exploited at the access point (AP). In particular, we assume that each source uses a channel code to transmit, through an additive white Gaussian noise (AWGN) channel, its information to the AP, where component decoders, associated with the sources, iteratively exchange soft information by taking into account the correlation. The key goal of this paper is to investigate whether there exist optimized channel codes for this scenario, i.e., channel codes which guarantee a desired performance level (in terms of average bit error rate, (BER) at the lowest possible signal-to-noise ratio (SNR). A two-dimensional extrinsic information transfer (EXIT) chart-inspired optimization approach is proposed. Our results suggest that by properly designing serially concatenated convolutional codes (SCCCs), the theoretical performance limits can be approached better than by using parallel concatenated convolutional codes (PCCCs) or low-density parity-check (LDPC) codes. It is also shown that irregular LDPC codes tend to perform better than regular LDPC codes, so that the design of appropriate LDPC codes remains an open issue.Information Theory and Applications Workshop, 2009; 03/2009
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ABSTRACT: Parallel independent channels where no encoding is allowed for one of the channels are studied. The Slepian-Wolf theorem on source coding of correlated sources is used to show that any information source whose entropy rate is below the sum of the capacity of the coded channel and the input/output mutual information of the uncoded channel is transmissible with arbitrary reliability. The converse is also shown. Thus, coding of the side information channel is unnecessary when its mutual information is maximized by the source distribution. Applications to superposed coded/uncoded transmission on Gaussian channels are studied and an information-theoretic interpretation of Parallel-Concatenated channel codes and, in particular. Turbo codes is put forth.European Transactions on Telecommunications 08/1995; 6(5):587 - 600. · 1.05 Impact Factor
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ABSTRACT: A serially concatenated code with interleaver consists of the cascade of an outer encoder, an interleaver permuting the outer codewords bits, and an inner encoder whose input words are the permuted outer codewords. The construction can be generalized to h cascaded encoders separated by h-1 interleavers. We obtain upper bounds to the average maximum-likelihood bit error probability of serially concatenated block and convolutional coding schemes. Then, we derive design guidelines for the outer and inner encoders that maximize the interleaver gain and the asymptotic slope of the error probability curves. Finally, we propose a new, low-complexity iterative decoding algorithm. Throughout the paper, extensive comparisons with parallel concatenated convolutional codes known as “turbo codes” are performed, showing that the new scheme can offer superior performanceIEEE Transactions on Information Theory 06/1998; · 2.65 Impact Factor