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International Conference on Information and Communication Technology Convergence (ICTC)

Selective Layered BP Decoding for low-latency NR LDPC Codes

Chanho Yoon, Woncheol Cho, Young‐Jo Ko

Published Oct 19, 2022• 2 citations
Publisher

Abstract

In this paper, we propose selective layered BP decoding approach for decoding 3GPP NR rate compatible punctured LDPC codes that eliminates the ambiguity of BP decoding for information bit punctured codes. Conventional BP or layered BP decoding approach for NR LDPC codes does not perform well in frequency selective fading channels, and, with the sub iteration applying to the sub matrix portion, the proposed SL layered BP decoding improves the performance drastically. We show that faster decoding speed by applying the proposed scheme to the 3GPP NR LDPC code is achieved in terms of decoding latency.

DOI
10.1109/ictc55196.2022.9952457

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In this paper, we propose selective layered BP decoding approach for decoding 3GPP NR rate compatible punctured LDPC codes that eliminates the ambiguity of BP decoding for information bit punctured codes. Conventional BP or layered BP decoding approach for NR LDPC codes does not perform well in frequency selective fading channels, and, with the sub iteration applying to the sub matrix portion, the proposed SL layered BP decoding improves the performance drastically. We show that faster decoding speed by applying the proposed scheme to the 3GPP NR LDPC code is achieved in terms of decoding latency.
Rate-compatible punctured LDPC codes have shown to perform well over a wide variety of code rates, both theoretically and practically. However it has been reported that the belief propagation (BP) decoding for these codes converges slower than for unpunctured codes. Layered BP algorithm is a modified BP algorithm that accelerates the decoding convergence by means of sequential scheduling of check node updates. In this letter, we propose an efficient scheduling of check node updates for rate-compatible punctured LDPC codes that performs well. We show that the convergence speed of the proposed scheduling outperforms conventional (random) scheduling and conventional BP decoding. Performance improvements become more distinctive with the growing fraction of punctured bits
While rate-compatible punctured low-density parity-check (RCP-LDPC) codes offer high flexibility in terms of code rate at a relatively low cost in implementation complexity, they are reported to require more decoding iterations than unpunctured LDPC codes. In this paper1we consider layered belief propagation decoding and propose efficient check node layering that significantly accelerates the decoding convergence of RCP-LDPC codes. We show that the proposed layering outperforms both random layering and conventional BP decoding. The performance improvements become more distinctive at high rates and they come at no additional implementation cost.
Low-density parity-check (LDPC) codes have been selected as the channel coding scheme for 5G NR standard, which have excellent performance approaching the Shannon limit and are easy to implement in hardware. The decoding algorithm and scheduling scheme of LDPC codes have a significant impact on performance. The row degree (RD) and the number of punctured bits (PBs) are widely used to determine the update order of layers. In this letter, we used Matlab to simulate the error performance of the 5G LDPC codes. We completed the bit error rate and frame error rate simulations of six different decoding algorithms, including flooding LLR-BP, flooding NMS, layered LLR-BP, layered NMS, the lowest degree and least-punctured (LD-LP) layered LLR-BP and LD-LP layered NMS methods, for the 5G LDPC code with a base graph of size [46, 68], code rate 1/3, and code length of 1584.We further compared the performance of LD-LP layered decoding and LP-LD layered decoding. Moreover, we simulated the error performance of the core part of the LDPC code, which consists of four layers. We evaluated the effect of the update order of the four layers on the error performance of the code, and concluded that some update orders might give slightly better error performance than others.
The Layered Belief Propagation L-BP algorithm is is a modified Belief Propagation BP algorithm, where the check nodes are divided in subgroups called layers and each iteration is broken into multiple sub-iterations. In this paper, we consider layered belief propagation decoding and propose an efficient variable node layering for decoding LDPC codes that performs well. We compare the performance of the first introduced LDPC decoding algorithm BP and Layered BP using check node layering with Layered BP using variable node layering in terms of bit error rate (BER). We show that the convergence for decoding LDPC codes is increasing by using a simple and efficient layering strategy.
Low-density parity-check (LDPC) codes have been chosen for the fifth-generation (5G) new radio (NR) enhanced Mobile Broad Band (eMBB) data channel. Since NR LDPC codes puncture the first two block columns of the parity-check matrix, the decoding complexity is reduced, but it slows down the convergence rate. In this letter, we propose a fixed schedule that decodes the layers with the least-punctured edges and those with the highest-degree (LPHD), which has much faster convergence speed than conventional schemes. The fixed scheduling schemes cannot take full advantage of the dynamic changes of decoding messages. As a result, the residual-based layered belief propagation (RB-LBP) is proposed to rearrange the layers dynamically among different iterations. Compared with some informed dynamic scheduling (IDS) strategies, RB-LBP reduces the decoding complexity with slight performance loss.
Channel coding technique is a fundamental building block in any modern communication system to realize reliable, fast, and secure data transmission. At the same time, it is a challenging and crucial task, as the data transmission happens in a channel where noise, fading, and other impairments are present. The Low-Density Parity-Check (LDPC) codes give substantial results close to the Shannon limit when the complexity and processing delay time are unlimited. In this paper, the performance of the LDPC decoding with four algorithms was investigated. The investigated four algorithms were Belief Propagation (BP), Layered Belief Propagation (LBP), Normalized min-sum (NMS), and Offset min-sum (OMS). These algorithms were examined for code rates ranging from 1/3 to 9/10 and message block lengths (64, 512, 1024, and 5120) bits. The simulation results revealed the flexibility of these decoders in supporting these code rates and block lengths, which enables their usage in a wide range of applications and scenarios for fifth-generation (5G) wireless communication. In addition, the effect of the maximum number of decoding iterations on the error correction performance was investigated, and a gain of 5.6 dB can be obtained by using 32 decoding iterations at BER=2*10-3 instead of one decoding iteration. The results showed that the decoders performed better for longer message blocks than for short message blocks, and less power was required for transmitting longer messages. Finally, the comparison results of their performance in terms of bit error rate (BER) under the same conditions showed a gain of 0.8 dB using LBP at BER= 10-5 compared with the NMS decoding algorithm.