A Generalized Adjusted Min-Sum Decoder for 5G LDPC Codes: Algorithm and Implementation

Fuente: arXiv
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Autori principali: Ren, Yuqing, Harb, Hassan, Shen, Yifei, Balatsoukas-Stimming, Alexios, Burg, Andreas
Natura: Preprint
Pubblicazione: 2023
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author Ren, Yuqing
Harb, Hassan
Shen, Yifei
Balatsoukas-Stimming, Alexios
Burg, Andreas
author_facet Ren, Yuqing
Harb, Hassan
Shen, Yifei
Balatsoukas-Stimming, Alexios
Burg, Andreas
contents 5G New Radio (NR) has stringent demands on both performance and complexity for the design of low-density parity-check (LDPC) decoding algorithms and corresponding VLSI implementations. Furthermore, decoders must fully support the wide range of all 5G NR blocklengths and code rates, which is a significant challenge. In this paper, we present a high-performance and low-complexity LDPC decoder, tailor-made to fulfill the 5G requirements. First, to close the gap between belief propagation (BP) decoding and its approximations in hardware, we propose an extension of adjusted min-sum decoding, called generalized adjusted min-sum (GA-MS) decoding. This decoding algorithm flexibly truncates the incoming messages at the check node level and carefully approximates the non-linear functions of BP decoding to balance the error-rate and hardware complexity. Numerical results demonstrate that the proposed fixed-point GAMS has only a minor gap of 0.1 dB compared to floating-point BP under various scenarios of 5G standard specifications. Secondly, we present a fully reconfigurable 5G NR LDPC decoder implementation based on GA-MS decoding. Given that memory occupies a substantial portion of the decoder area, we adopt multiple data compression and approximation techniques to reduce 42.2% of the memory overhead. The corresponding 28nm FD-SOI ASIC decoder has a core area of 1.823 mm2 and operates at 895 MHz. It is compatible with all 5G NR LDPC codes and achieves a peak throughput of 24.42 Gbps and a maximum area efficiency of 13.40 Gbps/mm2 at 4 decoding iterations.
format Preprint
id arxiv_https___arxiv_org_abs_2310_15801
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle A Generalized Adjusted Min-Sum Decoder for 5G LDPC Codes: Algorithm and Implementation
Ren, Yuqing
Harb, Hassan
Shen, Yifei
Balatsoukas-Stimming, Alexios
Burg, Andreas
Information Theory
Hardware Architecture
Signal Processing
5G New Radio (NR) has stringent demands on both performance and complexity for the design of low-density parity-check (LDPC) decoding algorithms and corresponding VLSI implementations. Furthermore, decoders must fully support the wide range of all 5G NR blocklengths and code rates, which is a significant challenge. In this paper, we present a high-performance and low-complexity LDPC decoder, tailor-made to fulfill the 5G requirements. First, to close the gap between belief propagation (BP) decoding and its approximations in hardware, we propose an extension of adjusted min-sum decoding, called generalized adjusted min-sum (GA-MS) decoding. This decoding algorithm flexibly truncates the incoming messages at the check node level and carefully approximates the non-linear functions of BP decoding to balance the error-rate and hardware complexity. Numerical results demonstrate that the proposed fixed-point GAMS has only a minor gap of 0.1 dB compared to floating-point BP under various scenarios of 5G standard specifications. Secondly, we present a fully reconfigurable 5G NR LDPC decoder implementation based on GA-MS decoding. Given that memory occupies a substantial portion of the decoder area, we adopt multiple data compression and approximation techniques to reduce 42.2% of the memory overhead. The corresponding 28nm FD-SOI ASIC decoder has a core area of 1.823 mm2 and operates at 895 MHz. It is compatible with all 5G NR LDPC codes and achieves a peak throughput of 24.42 Gbps and a maximum area efficiency of 13.40 Gbps/mm2 at 4 decoding iterations.
title A Generalized Adjusted Min-Sum Decoder for 5G LDPC Codes: Algorithm and Implementation
topic Information Theory
Hardware Architecture
Signal Processing
url https://arxiv.org/abs/2310.15801