Hybrid optimization algorithm to estimate azimuth angle for millimeter wave massive MIMO system

Abstract

Further enhancement of 4G (or 4G-LTE advanced) spectral efficiency is possible only by allocating more bandwidth i.e., broadcasting on millimeter wave (mmWave) spectrum, by using the concept of small cells and also by increasing the number of spatial channels which is referred to as MIMO systems. However, recognizing the mmWave in MIMO remains a complex task that faces the issues like increased propagation loss. A new optimization based estimation algorithm is proposed to estimate the mm wave channel and to improve the performance of hybrid precoding. Azimuth angle is considered as objective function and is optimized without deviating from the actual characteristics. In this paper, Dragonfly Evaluated Grey Wolf Optimization (DE-GWO) model is introduced that hybridizes the concepts of DA and GWO respectively. The proposed algorithm is validated by comparing with Deer Hunting Optimization Algorithm (DHOA), Lion Algorithm (LA) and LDHOA (combination of LA and DHOA). Finally, the performance of proposed work is compared and validated over other state-of-the-art models with respect to CSI and error measures.