PROJECT TITLE :

Efficient Soft Cancelation Decoder Architectures for Polar Codes - 2017

ABSTRACT:

The flooding belief propagation (FO-BP) and also the soft-cancelation (SCAN) algorithms are the 2 most standard soft-output BP algorithms for the decoding of capacity-achieving polar codes. The FO-BP algorithm has high throughput at the cost of performance degradation in high signal-to-noise ratio (SNR) region or with giant block length. The SCAN algorithm has much higher decoding performance whereas stricken by long decoding latency and low throughput. In this paper, an improved BP algorithm, named reduced complexity soft-cancelation (RCSC) algorithm, is proposed. Compared with the SCAN algorithm, the amount of memory entries required by the RCSC algorithm is reduced by additional than 50percent generally, while achieving comparable or even better (e.g., when block size N = 2 fifteen ) decoding performance. When block size is giant (e.g., N = a pair of 15), the proposed RCSC algorithm reduces the required memory entries by a lot of than 23% compared with the state-of-the-art FO-BP algorithm. The numerical results show that the error performance improvement of the RCSC algorithm is a lot of significant when the SNR will increase. For a different tradeoff, a reduced latency soft-cancelation (RLSC) algorithm is proposed to reduce the decoding latency and increase the throughput of the RCSC algorithm whereas slightly sacrificing decoding performance. Finally, the optimized VLSI architectures are presented for the RCSC and RLSC algorithms, respectively. The synthesis results demonstrate the potency of the proposed algorithms and architectures.


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