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Physical Communication

Novel memory efficient LDPC decoders for beyond 5G

Hongyuan Li, Zhenghong Yu, Tongwei Lu, Wanjun Zheng, Haijie Feng, Zi-Qian Ma, Fusheng Zhu

Published Dec 3, 2021• 6 citations
Publisher
DOI
10.1016/j.phycom.2021.101538

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This paper presents a high-throughput decoding method for quasi-cyclic low-density parity-check (QC-LDPC) codes, optimized for both CPU and GPU-based Software-Defined Radios (SDRs). The approach leverages a SIMD data alignment architecture that minimizes cache misses and is designed to take full advantage of modern CPUs and GPUs with rich registers and caches. An innovative decoding algorithm is introduced, exploiting the SIMD capabilities of contemporary CPUs to enhance parallelism, while optimizing memory access patterns to align SIMD operations and minimize branching and cache misses on AMD EPYC CPUs (2xEPYC-9754). This results in significant throughput improvements. The method is further extended to GPUs, utilizing their large-scale parallelism through efficient use of registers and local memory. To maximize performance, a memory-efficient check node decoding strategy is employed, ensuring that operations fit within the cache of the Streaming Multiprocessors (SM) to reduce memory access overhead. Simulation results demonstrate the effectiveness of this approach: the CPU-based 8-iteration layered min-sum decoder with early termination achieves coded bit throughputs of up to 72.9 Gbps for 16200-bit codes and 50.9 Gbps for 64800-bit DVB-S2 QC-LDPC codes. On GPUs, the decoder reaches 132 Gbps for short 802.11n Wi-Fi 1944-bit codes and 22.3 Gbps for 5G Base Graph 1 26112-bit codes on an NVIDIA RTX 4090. For 6G prototype QC-LDPC codes, the proposed 3-layer design achieves up to 76 Gbps for 1920-bit codes, with surpassing 104 Gbps on the NVIDIA RTX 5090. Compared to the open-source AFF3CT CPU framework, the proposed method offers 5 to 12 times higher throughput across various code lengths. Even when AFF3CT is optimized with MIPP intrinsics, the new decoder provides 3.2 to 5.7 times better throughput. The GPU implementation delivers up to 120 times the speed of previously published results and offers 13 to 40 times improvement over older GPUs like the GTX 1080 Ti and Titan X, scaling effectively with modern GPUs like the RTX 4090. This approach establishes new performance benchmarks for QC-LDPC decoding, positioning it as an ideal solution for next-generation 5G/6G wireless and satellite communications.