Research On Receiving Algorithm Based On Interference Measurement In Millimeter-Wave Massive MIMO System

For current wireless communication system,high data rate and high reliability are the basic requirements.In view of the shortage of spectrum resource,the introduction and use of millimeter-wave has greatly eased spectrum pressure.The rich frequency resource in the millimeter-wave band can meet the need of high data rate transmission,but it brings serious path loss,which becomes an urgent problem to be solved.Large-scale antenna technology can increase the system capacity while effectively improving the transmission link quality.Hybrid beamforming technology based on large-scale antenna arrays can achieve high-gain directional beams,so an effective beam selection algorithm will bring great performance gains to millimeter-wave systems.Wireless signal propagation is severely affected by fading,interference,and noise,thus adopting effective channel equalization techniques at the receiver can effectively compensate the weakened signal strength.In addition,as an important influence of millimeter-wave communication system,the realization of accurate measurement of interference is of great significance to improve the system performance.The main work and innovation of this paper are as follows:1.Compared with the traditional beam selection scheme based on a single criterion,an adaptive beam selection algorithm is proposed.The algorithm perform interference detection with interference correlation matrix,so as to achieve adaptive dynamic switching among given beam selection criteria in different interference environments.Simulations show that the adaptive beam selection algorithm can effectively balance transmission performance and beam selection overhead.2.To ensure effective channel equalization,we propose an adaptive receiver algorithm,which aims to dynamically switch between maximum ratio combining(MRC)and interference suppression combining(IRC)according to the interference level of the transmission link.Compared with traditional hard switching schemes,interference detection based on machine learning algorithms can achieve more accurate judgment of the channel interference level,so that the appropriate receiving algorithm can be selected under different interference states,which has a good compromise on the receiving performance and complexity.3.Aiming at the interference detection process involved in the aforementioned problem,this paper proposes an interference measurement algorithm based on tracking reference signal(TRS),thus the measured interference information can be applied to the aforementioned technology and any other communication related processes to further improve the performance of the communication system.This algorithm is based on the effective channel estimation of the TRS,and through various learning algorithms,it implements effective interference measurement in various channel scenarios.In order to reduce system overhead and improve interference measurement accuracy,three enhanced interference measurement schemes are further proposed.Simulation results show that the algorithm can achieve effective interference measurement,and the enhanced algorithm achieves accurate interference measurement while reducing overhead.