The Error Probability of Spatially Coupled Sparse Regression Codes over Memoryless Channels
Information Theory
2024-09-10 v1 math.IT
Abstract
Sparse Regression Codes (SPARCs) are capacity-achieving codes introduced for communication over the Additive White Gaussian Noise (AWGN) channels and were later extended to general memoryless channels. In particular it was shown via threshold saturation that Spatially Coupled Sparse Regression Codes (SC-SPARCs) are capacity-achieving over general memoryless channels when using an Approximate Message Passing decoder (AMP). This paper, for the first time rigorously, analyzes the non-asymptotic performance of the Generalized Approximate Message Passing (GAMP) decoder of SC-SPARCs over memoryless channels, and proves exponential decaying error probability with respect to the code length.
Cite
@article{arxiv.2409.05745,
title = {The Error Probability of Spatially Coupled Sparse Regression Codes over Memoryless Channels},
author = {Yuhao Liu and Yizhou Xu and Tianqi Hou},
journal= {arXiv preprint arXiv:2409.05745},
year = {2024}
}