Research On Energy Efficiency Optimization Of Massive MIMO System In Ultra-Dense Network

The next generation of mobile communication(5G)aims at providing users with high-quality communication services of higher data rate and lower latency.While new technologies such as ultra-dense network(UDN)and massive MIMO bring significant improvements in quality of service(QoS)and spectral efficiency(SE),the issue of the ecological environment such as communication energy consumption has also attracted wide attention.As a key technical indicator of 5G,further research on energy efficiency(EE)is an important way to achieve sustainable development and green communications.In this paper,the energy efficiency of massive MIMO systems in ultra-dense networks is studied in depth to find out the optimal deployment strategy for maximizing energy efficiency.First of all,the energy efficiency of multi-layer HetNet is analyzed by stochastic geometric method.Taking two-tier HetNet as an example,this paper illustrates the impact of macrocell base station density and small cell base station density on network energy efficiency.Then,this paper puts forward a circuit power consumption model suitable for MIMO system and disscusses the influence of base station antenna number,number of users and transmission power on the single-cell multi-user MIMO energy efficiency.Thus,an iterative optimization algorithm for rapidly finding the optimal point of EE is obtained.Finally,considering the ultra-dense network,massive MIMO technology and the proposed new circuit power consumption model,this paper analyzes the impact of more factors such as base station density,transmit power,number of base station antennas,users per cell,and pilot reuse factor on the energy efficiency of multi-cell multi-user MIMO systems.The optimal network deployment scheme is also obtained,as well as the relationship between the optimal variables,hardware characteristics and propagation environment.Furthermore,simulation and numerical results show that the ultra-dense network deployment can significantly improve the energy efficiency,and the optimal network deployment scheme is also in line with the massive MIMO scenario.