Fast-Converging and Low-Power LDPC Decoding: Algorithm, Architecture, and VLSI Implementation
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Signal Processing Systems"
DOI: 10.1007/s11265-021-01680-0
Abstract: Low-latency and energy-efficient multi-Gbps LDPC decoding requires fast-converging iterative schedules. Hardware decoder architectures based on such schedules can achieve high throughput at low clock speeds, resulting in reduced power consumption and relaxed timing closure requirements… read more here.
Keywords: fast converging; power; ldpc; ldpc decoding ... See more keywords
A Low-Complexity Neural Normalized Min-Sum LDPC Decoding Algorithm Using Tensor-Train Decomposition
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2022.3207506
Abstract: Compared with traditional low-density parity-check (LDPC) decoding algorithms, the current model-driven deep learning (DL)-based LDPC decoding algorithms face the disadvantage of high computational complexity. Based on the Neural Normalized Min-Sum (NNMS) algorithm, we propose a… read more here.
Keywords: normalized min; ldpc decoding; nnms algorithm; neural normalized ... See more keywords
Normalized Min-Sum Neural Network for LDPC Decoding
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Cognitive Communications and Networking"
DOI: 10.1109/tccn.2022.3212438
Abstract: The success of deep learning has encouraged its applications in decoding error-correcting codes, e.g., LDPC decoding. In this paper, we propose a model-driven deep learning method for normalized min-sum (NMS) low-density parity-check (LDPC) decoding, namely… read more here.
Keywords: network; normalized min; ldpc decoding; min sum ... See more keywords