Performance comparison of LMS and RLS adaptive array on high speed train delivered from High Altitude Platforms

Abstract

The performance of the Least Mean Square (LMS) and Recursive Least Square (RLS) adaptive array are compared via Monte Carlo simulation. The comparisons are in terms of the convergence behavior, the Mean Square Error (MSE) of weight tracking, and the Bit Error Rate (BER). The communication systems is the downlink from High Altitude Platforms (HAPs) to antenna arrays onboard high speed train on Ka-band. Although RLS has advantage in terms of convergence behavior, its tracking performance is almost equivalent to LMS, thus the latter provides an alternative as a compensation technique for time varying channel induced by the moving train. Nevertheless, the Signal to Noise Ratio (SNR) of interest has to be taken into consideration.