Research On Power Model And Energy Efficiency Of Massive MIMO System Based On ZF Processing

Massive MIMO has been widely studied as a key 5G technology.The main feature of the massive MIMO system is that hundreds of antennas are deployed at the base station to serve tens of terminal users in the cell.This technology can make full use of the space freedom without increasing the bandwidth,not only can significantly increase the channel capacity,but also can effectively improve the energy efficiency.Due to the large number of antennas configured by the base station in a massive MIMO system,and each antenna needs to be equipped with a corresponding radio frequency link,the power consumed by the total radio frequency link rapidly increases.In addition,large-scale antenna arrays also increase system hardware and computational complexity.Therefore,configuring a proper number of antennas at the base station and maintaining high energy efficiency is a subject worthy of study.The research work in this paper mainly includes the following points:First,the main sources of power consumption in a massive MIMO system are analyzed.Based on analysis,choose a power consumption model more suitable for massive MIMO.This model not only reflects the changing trend of the power consumption of the radio frequency link with the increase of the number of antennas,but also considers the power consumed by the signal encoding and decoding,the linear processing at both ends of the transmission and reception,and the channel estimation.Secondly,considering the requirement of future wireless communication for energy saving,this paper uses a high energy efficiency scheme to maximize system energy efficiency.Based on the above power consumption model,the optimal closed-form expressions of the three parameters of the number of users,the number of base station antennas,and the transmission power when using the ZF algorithm are derived.By combining these three coefficients,the optimal energy efficiency of the system is fully exploited.For the problem that the computational complexity of exhaustive calculations in a single cell is large,an iterative algorithm is used in this paper to speed up the convergence rate of the optimal system.The iterative algorithm used in this paper achieves the same performance and lower complexity as the exhaustive algorithm in the simulation.Finally,in order to study the relationship between different levels of pilot pollution and energy efficiency,this paper studies the comparison of maximum energy efficiency under different pilot reuse factors in a large-scale MIMO multi-cell system.In the simulation results,similar conclusions are obtained as for a single cell: When the number of base station antennas increases,the system energy efficiency can be increased by increasing the transmit power;the parameter values obtained by the closed-form expression can make the system achieve the best energy efficiency.