Decoding Algorithm Based on LDPC for UAV MISO Ultraviolet Communication System

Xingle Xue, Junyang Ji, Ping Su, Jianshe Ma, Bizhong Xia, Xingguang Li

Abstract: Unmanned aerial vehicle (UAV) ultraviolet (UV) communication has garnered significant attention due to its broad range of applications. Currently, there are few decoding algorithms specifically tailored for UAV UV multiple-input-single-output (MISO) communication scenarios. We propose an enhanced maximum a posteriori (MAP) and log-likelihood ratio belief propagation (LLRBP) algorithm for MISO UV communication systems. This algorithm strategically ranks interference signals based on the signal-to-interference plus noise ratio (SINR), effectively eliminates errors in transmitter information recovery, and is named the SINR-MAP-LLRBP Algorithm. Building upon this algorithm, we establish the optimal quantitative relationship for the signal-to-noise ratio (SNR) in the MISO UVC system. Additionally, we introduce an enhanced decoding algorithm for MISO UV communication systems, leveraging the residual-based loop iteration methodology, named as the Res-SINR-MAP-LLRBP Algorithm. This algorithm provides an additional decoding gain compared to the SINR-MAP-LLRBP Algorithm.