An Adaptive Algorithm for Joint Data Detection and Channel Estimation for Meteor Burst Communications Based on Per-Survivor Processing

Abstract

For meteor burst communications (MBC), although per-survivor processing (PSP) based on joint data and channel estimation provides superior performance and robustness for meteor burst communications (MBC), great computational complexity constrains its application in practice. On this occasion, a dimension-down PSP (D- PSP) algorithm and a adaptive state reduction of PSP (ASRP) algorithm are proposed to curve this problem in this paper. On the basis of this, the adaptive state reduction using a dimension-down PSP (ADPSP) is proposed to combine the advantages of D-PSP and ASRP, which reduces the computational time and memory size for exponentially decaying meteor burst channels and makes maximum likelihood sequence detection (MLSD) possible for adaptive data transmission. Simulation results are presented to validate the theoretical analysis. It is shown that deploying the proposed ADPSP algorithm can achieve a good tradeoff between performance and computational complexity dynamically, and provide reliable data transmission for MBC systems with adaptive coding and modulation.