Low-Latency Polar Decoding for Error-Free and Single-Error Cases

Jiayu Xiao, Yangcan Zhou, Suwen Song +1 more

The ultra-reliable low-latency communication (URLLC), one of the three main scenarios in the fifth-generation (5G) mobile communication system, is promising to be used in various emerging applications with stringent latency and performance requirements. Recently, the guessing random additive noise decoding (GRAND) is proposed, which can perform well for the URLLC due to its excellent error-correction performance with short code length. Compared to other variants of the GRAND, the ordered reliability bits GRAND (ORBGRAND) can provide a good trade-off between error-correction performance and hardware overhead. In this work, the ORBGRAND with a reduced schedule for polar codes is implemented for the first time, which utilizes the special structure of the parity-check matrix of polar codes to reduce the decoding latency while keeping the error-correction performance unaltered. Besides, the sorter employed in the ORBGRAND decoder is well optimized to reduce the area occupation. At a target frame error rate of 10−5when using a (128, 105) 5G polar code, the average decoding latency of the proposed decoder is only 2.46 ns. Moreover, compared to the state-of-the-art ORBGRAND decoder, the proposed decoder can achieve 15% higher decoding throughput and 71% higher area efficiency without any error-correction performance loss.

Qingyun Xu, Zhiwen Pan, Nan Liu +1 more

Toshiaki Koike–Akino, Congzhe Cao, Ye Wang +8 more

Next-generation fiber-optic communications call for ultra-reliable forward error correction codes that are capable of low-power and low-latency decoding. In this paper, we propose a new class of polar codes, whose polarization units are irregularly pruned to reduce computational complexity and decoding latency without sacrificing error correction performance. We then experimentally demonstrate that the proposed irregular polar codes can outperform state-of-the-art low-density parity-check (LDPC) codes, while decoding complexity and latency can be reduced by at least 30% and 70%, respectively, versus regular polar codes, while also obtaining a marginal performance improvement.

Dongsheng Wu, Qingshuang Zhang, Yingxian Zhang

Bo Yuan, Keshab K. Parhi

Polar codes, as the first provable capacity-achieving error-correcting codes, have received much attention in recent years. However, the decoding performance of polar codes with traditional successive-cancellation (SC) algorithm cannot match that of the low-density parity-check or Turbo codes. Because SC list (SCL) decoding algorithm can significantly improve the error-correcting performance of polar codes, design of SCL decoders is important for polar codes to be deployed in practical applications. However, because the prior latency reduction approaches for SC decoders are not applicable for SCL decoders, these list decoders suffer from the long-latency bottleneck. In this paper, we propose a multibit-decision approach that can significantly reduce latency of SCL decoders. First, we present a reformulated SCL algorithm that can perform intermediate decoding of 2 b together. The proposed approach, referred as 2-bit reformulated SCL (2b-rSCL) algorithm, can reduce the latency of SCL decoder from (3n-2) to (2n-2) clock cycles without any performance loss. Then, we extend the idea of 2-b-decision to general case, and propose a general decoding scheme that can perform intermediate decoding of any 2Kbits simultaneously. This general approach, referred as 2K-bit reformulated SCL (2Kb-rSCL) algorithm, can reduce the overall decoding latency to as short as n/2K-2-2 cycles. Furthermore, on the basis of the proposed algorithms, very large-scale integration architectures for 2b-rSCL and 4b-rSCL decoders are synthesized. Compared with a prior SCL decoder, the proposed (1024, 512) 2b-rSCL and 4b-rSCL decoders can achieve 21% and 60% reduction in latency, 1.66 and 2.77 times increase in coded throughput with list size 2, and 2.11 and 3.23 times increase in coded throughput with list size 4, respectively.

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