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Implementation of Soft Decision Low-Density Parity-Check Decoder for Bahl-Cocke-Jelinek-Raviv Algorithm
| Content Provider | Semantic Scholar |
|---|---|
| Author | Varma, Manthena V. S. Ramaraju, J. S. S. Srinivas, Subhashini |
| Copyright Year | 2013 |
| Abstract | In this paper we focus on the BCJR algorithm, and its prior estimate of the channel state information (CSI), In case of uncertainties during the estimation, overconfident posterior probability tends to mislead the performance of soft decoders. Our approach takes into consideration not only the uncertainty due to the noise in the channel, but also the uncertainty in the CSI estimate. Thus, we resort to a Bayesian approach for the computation of the APP. Hence, we also put forward an approximation for each symbol’s posterior, using the expectation propagation algorithm, which is optimal from the KullbackLeibler divergence. View pointed yields an equalization with a complexity identical to the BCJR algorithm. This algorithm has the same complexity as the BCJR, exhibiting lower bit error rate at the out of the channel decoder than the standard BCJR that considers maximum likelihood (ML) to estimate the CSI. We also use a graphical model representation of the full posteriori which the proposed approximation can be readily understood. This proposed method exhibits a much better performance compared to the ML-BCJR when a LDPC decoder, which needs the exact posterior for each symbol to detect the incoming word and it is sensitive to a mismatch in those posterior estimates, for example, for QPSK modulation and a channel with three taps, we can expect gains over 0.5db with same computational complexity as the ML |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ijera.com/papers/Vol3_issue4/KC3418141820.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
