Distributed Source-Channel Coding Based on Real-Field BCH Codes

Vaezi, Mojtaba; Labeau, Fabrice

doi:10.1109/tsp.2014.2300039

Cited by 17 publications

(6 citation statements)

References 46 publications

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“…(b) Bernoulli-Gaussian. quantized BU source using RSSC (12), BCHSC (13), AC, Huffman encoder, and run length encoding, plus the Shannon's lower bound (45), as a function of the average sparsity ratio p, for b = 8 bits/sample. It is noted that the rates indicated by both RSSC and AC are coincident, while the BCHSC can achieve a higher compression gain (up to 15% compared to RSSC).…”

Section: A Performance Analysismentioning

confidence: 99%

“…For example, a compression scheme for continuous sources considering that the decoder has side information, i.e., a noisy version of the source, is proposed in [38]. Several works have discussed designing codes for similar problems, e.g., multi-terminal source coding [39]- [42], successive refinement source compression [43], and joint source channel coding [44], [45].…”

Section: Introductionmentioning

confidence: 99%

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Lossy Compression of Noisy Sparse Sources Based on Syndrome Encoding

Elzanaty

Giorgetti

Chiani

2019

IEEE Trans. Commun.

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Data originating from devices and sensors in Internet of Things scenarios can often be modeled as sparse signals. In this paper, we provide new source compression schemes for noisy sparse and non-strictly sparse sources, based on channel coding theory. Specifically, nonlinear excision filtering by means of model order selection or thresholding is first used to detect the support of the non-zero elements of sparse vectors in noise. Then, the sparse sources are quantized and compressed using syndrome based encoders. The theoretical performance of the schemes is provided, accounting for the uncertainty in the support estimation. In particular, we derive the operational distortionrate and operational distortion-energy of the encoders for noisy Bernoulli-uniform and Bernoulli-Gaussian sparse sources. It is found that the performance of the proposed encoders approaches the information-theoretic bounds for sources with low sparsity order. As a case study, the proposed encoders are used to compress signals gathered from a real wireless sensor network for environmental monitoring.

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Section: A Performance Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Lossy Compression of Noisy Sparse Sources Based on Syndrome Encoding

Elzanaty

Giorgetti

Chiani

2019

IEEE Trans. Commun.

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“…As http://asp.eurasipjournals.com/content/2013/1/166 we also demonstrate in the result section, the performance of a feedback-free non-rate-adaptive code is limited by the block length and for short-and medium-length codes clearly inferior compared with the performance of its rateadaptive counterpart. In the context of non-rate-adaptive codes, quasi-arithmetic codes for DSC have been investigated in [12], and in the field of real-number codes, BCH-DFT codes [13] have been proposed.…”

Section: H(x|y ) Is Lowmentioning

confidence: 99%

Rate-adaptive BCH codes for distributed source coding

Salmistraro

Larsen

Forchhammer

2013

EURASIP J. Adv. Signal Process.

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This paper considers Bose-Chaudhuri-Hocquenghem (BCH) codes for distributed source coding. A feedback channel is employed to adapt the rate of the code during the decoding process. The focus is on codes with short block lengths for independently coding a binary source X and decoding it given its correlated side information Y. The proposed codes have been analyzed in a high-correlation scenario, where the marginal probability of each symbol, X i in X, given Y is highly skewed (unbalanced). Rate-adaptive BCH codes are presented and applied to distributed source coding. Adaptive and fixed checking strategies for improving the reliability of the decoded result are analyzed, and methods for estimating the performance are proposed. In the analysis, noiseless feedback and noiseless communication are assumed. Simulation results show that rate-adaptive BCH codes achieve better performance than low-density parity-check accumulate (LDPCA) codes in the cases studied.

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“…Posterior to the RS decoding removing the noise, the residual effect of ISI can be removed by a Galois field equalizer in the second stage. The judicious selection of the code parameters can effectively remove the problem of high PAPR and BER [15]. BCH codes have the ability to recover the synchronization problem because of its self synchronizing capability.…”

Section: Introductionmentioning

confidence: 99%

BER Assessment of FEC Incorporated OFDM-MPSK Wireless System

Kansal

Sharma²,

Singh³

2015

2015 Fifth International Conference on Advanced Computing &Amp; Communication Technologies

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Due to elevated data rate transmission, fading immunity and bandwidth efficient capability, OFDM comes out as a key technology in contemporary wireless communication systems. Additionally, to access error free transmission, diverse channel codes for instance Convolution Codes (CC), Reed Solomon (RS) and BCH codes are being used in the previous work. In this work, an OFDM based M-PSK wireless system is demonstrated incorporating diverse channel encoding techniques over Rayleigh fading channel.The performance of the simulated test-bed is investigated via BER assessment as a function of SNR. Our simulation results reports a significant improvement in BER of the simulated system using BCH over CC and RS.

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Distributed Source-Channel Coding Based on Real-Field BCH Codes

Cited by 17 publications

References 46 publications

Lossy Compression of Noisy Sparse Sources Based on Syndrome Encoding

Lossy Compression of Noisy Sparse Sources Based on Syndrome Encoding

Rate-adaptive BCH codes for distributed source coding

BER Assessment of FEC Incorporated OFDM-MPSK Wireless System

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