Generalized sparse codes for non-Gaussian channels: Code design, algorithms, and applications - Chen, Zhao; Sun, Zhen; Pei, Yukui; Yin, Liuguo (Fundamental research (Beijing), 2022)
[Display omitted] In this paper, generalized sparse (GS) codes are proposed to support reliable and efficient transmission over non-Gaussian channels. Specifically, by expanding the single-parity check (SPC) code constraints with powerful algebraic codes, GS codes generalize conventional sparse codes with enhanced error-correcting capability, as well as better code design flexibility by covering a wide range of block-lengths and coding rates with reduced encoding/decoding complexity. Moreover, by introducing a universal communication channel model, a general framework for performance analysis and code design of GS codes is formulated, by which the coding parameters can be optimized for different target channel conditions. Finally, example codes are constructed for several critical application scenarios with non-Gaussian channels. Numerical simulations are performed to demonstrate the superiority of the proposed GS coding scheme to traditional channel coding schemes.