Joint Optimization of Massive MIMO System Resources Based on Service QoS

Abstract

Aiming at the problem of low throughput and energy efficiency caused by the mutual restriction of energy efficiency and spectral efficiency in massive MIMO systems and the fact that resource allocation does not consider the factors of user service QoS and the upper and lower speed limits, a resource joint optimization method based on user service QoS guarantee is proposed. The method first performs user scheduling according to service delay and channel state under the condition of equal power distribution and calculates the current system capacity, and then combines transmit antenna power and service QoS constraints to redistribute power, and corrects the system capacity, establishing the objective function for the joint optimization of the spectral efficiency and energy efficiency. An algorithm combining deep learning and Q learning is used to solve the problem, and finally, the purpose of joint optimization is achieved. The simulation shows that the joint optimization method proposed in this paper can control the timeout of user data packets more finely and, at the same time, obtain greater energy efficiency and throughput.