A Joint Optimization Method Of User Scheduling And Power Allocation For MIMO-OFDMA Systems With User Buffer

Wireless communication has been one of the research hotpots in recent years.Because of the fast development of smart-phones,the technology of wireless communication is developing rapidly.MIMO uses antennas at both transmitter and receiver to suppress channel fading so as to raise wireless channel capacity via space division multiplexing.Thus MIMO can exponentially improve the spectrum utilization without increasing the bandwidth and larger transmit power.This paper studies MIMO-OFDMA systems and RBs(resource blocks)are allocated to users.RB is a set of subcarriers and subcarriers in the same RB are allocated to the same user.As the number of antennas rises,the consumption of electric energy also increases.Green communications has drawn a lot of attentions in current researches.Thus the concept of energy efficiency(EE,represented by transmission data rate per unit energy)has been emerged as the optimization goal in wireless telecommunication systems.It has been the focus of researches both in and outside our country to improve energy efficiency.In addition,real-time services and non real time services are different in terms of delay requirements,so it is also very important to ensure the QoS of different services.Therefore,in user scheduling and power allocation,it is particularly important to consider the user's QoS requirements and energy efficiency comprehensively.In background of the MIMO-OFDMA downlink systems,this paper carries out an algorithm to guarantee user's QoS and optimize the energy efficiency via user scheduling and resource allocation.The algorithm considers the influence of user side buffer on user rate in the process of user scheduling,which ensures user delay and improves energy efficiency.The power allocation step ensures the upper and lower limit of user speed and further improves the energy efficiency.The simulation results show that the algorithm can fully consider the influence of buffer size on user speed,and on this basis and it ensures the optimization of energy efficiency.