Mitigating impulsive noise in airborne PLC: Introducing the S-SAMP-PV algorithm for MIMO OFDM systems

Abstract

Power Line Communication (PLC) offers an efficient solution for data transmission over electrical power lines, presenting a promising avenue for in-flight communication in More Electrical Aircraft (MEA). A significant challenge in airborne PLC is Impulsive Noise (IN), which hampers transmission reliability. Existing noise mitigation methods, while valuable, face limitations in airborne settings due to computational intensiveness and sub-optimal sparse recovery performance. This paper introduces the Structured Sparsity Adaptive Matching Pursuit with Preliminary partial support estimation and Variable step-size (S-SAMP-PV) algorithm, devised for Multiple-Input-Multiple-Output (MIMO) systems. It uniquely pre-estimates partial support of sparse IN signals, enabling adaptive convergence without prior sparsity knowledge. This methodology substantially reduces computational demands, satisfying stringent real-time requirements of airborne applications. In simulation, the S-SAMP-PV algorithm exhibits marked advantages over traditional algorithms such as Orthogonal Matching Pursuit (OMP). Specifically, it realizes an approximate 81.3$\text{\%}$ reduction in Normalized Mean Square Error (NMSE) and demonstrates around 37$\text{\%}$ improvement in computational efficiency relative to OMP. Moreover, its Bit Error Rate (BER) performance at high Signal to Noise Ratio (SNR) approaches the ideal scenario where IN is assumed to be perfectly eliminated. These results emphasize the promise of S-SAMP-PV in elevating the performance of airborne PLC systems by efficient IN mitigation.