Multi-Factor Pruning for Recursive Projection-Aggregation Decoding of RM Codes
Information Theory
2022-09-05 v2 math.IT
Abstract
The recently introduced recursive projection aggregation (RPA) decoding method for Reed-Muller (RM) codes can achieve near-maximum likelihood (ML) decoding performance. However, its high computational complexity makes its implementation challenging for time- and resource-critical applications. In this work, we present a complexity reduction technique called multi-factor pruning that reduces the computational complexity of RPA significantly. Our simulation results show that the proposed pruning approach with appropriately selected factors can reduce the complexity of RPA by up to for while keeping the comparable error-correcting performance.
Cite
@article{arxiv.2208.13659,
title = {Multi-Factor Pruning for Recursive Projection-Aggregation Decoding of RM Codes},
author = {Marzieh Hashemipour-Nazari and Kees Goossens and Alexios Balatsoukas-Stimming},
journal= {arXiv preprint arXiv:2208.13659},
year = {2022}
}