Performance Analysis of Channel Estimation in 5G millimeter-Wave-MIMO Heterogeneous Systems

Abstract

Millimeter Wave (mm-Wave) - massive Multiple-Input Multiple-Output (MIMO) technology has been a subject of today’s growing interest in both industry and academia for future wireless standards and has significant potential to provide considerable gains in data rates, link reliability and Energy Efficiency (EE).Sparse recovery has great capability in Channel Estimation (CE) for mm-Wave - Massive-MIMO (Ma-MIMO) heterogeneous wireless networks and in this context; the existing better candidate “Orthogonal Matching Pursuit” (OMP) algorithm is modified for CE in such networks. This paper will provide an opportunity in setting up of such a network, and the practical observation of the effect of a change in threshold, sparsity and noise levels as well as quantity of Radio Frequency (RF) chain systems. The performance analysis of CE accuracy in terms of Normalized Mean Square Error (NMSE)verses a given Signal-to-Noise (SNR) range in dB is calculated using this modified algorithm, much better than the existing OMP methods and compared against the ideal Genie case under a wide range of noise encountered. It has been observed that in a very high noise environment, NMSE of this noise resistant algorithm is approximate (100.5 to 10-3.5) in low SNR range (-10 to 30) dB and approximate (10-1.5 to10-5.5) in high SNR range (10 to 50) dB. It comes out to be approximate (10-1 to more than 10-5) in case of combined effect involvingthe reduction of quantity of RF chain systems to half and 10 times enhancement of threshold level in a very high noise environment and low SNR range.