Resource Allocation Algorithm For MU-MIMO Systems With Limited Feedback Under The Existence Of The Rank Deficient Channel Matrix

In order to meet people's demand for data rate,multiple antenna(Multiple-Input Multiple-Output,MIMO)technology is introduced in wireless communication,which is also an important part of LTE system.On this basis,as one of the key technologies of 5G,multi-user MIMO(Multi-User MIMO,MU-MIMO)technology can use the dimension of space to improve system throughput on the basis of not occupying spectrum resources.However,with the increase of the number of antennas in the MU-MIMO system,the power consumed by the transmitter is also increasing.How to consider the energy saving while ensuring the system performance,the concept of Energy Efficiency(EE)at this time It came into being.So far,how to optimize the energy efficiency and system throughput of the MU-MIMO system through effective resource allocation is still a research hotspot in the field of wireless communication.The MU-MIMO technology uses the dimension of space to greatly improve the performance of the communication system by equipping multiple antennas on the user side and the base station side.Since multiple users share the same time-frequency resource,a precoding technique is introduced in the MU-MIMO system to eliminate co-channel interference(Co-Channel Interference)between users.In a scenario with a large number of users and a large number of transmitting and receiving antennas,so that the uplink cannot bear the huge amount of feedback at this time.Therefore,in practical situations,the limited feedback technique based on codebook is generally adopted.In the current literature on the resource allocation of limited feedback MU-MIMO systems,the channel underrank situation has not been considered.When the channel is under-ranked,the number of users of the system capacity will increase,which will affect the system's resource allocation and user selection.In view of the above problems,this paper proposes a joint optimization of the effective system throughput and limited system under limited feedback under-ranked channels.The algorithm simultaneously optimizes the effective throughput and energy efficiency of the MU-MIMO system through user selection and power allocation.Specifically,the first step is to perform user scheduling on the basis of equal power allocation of user subchannels to ensure the QoS requirements of different services for users,and then the second step to redistribute power to maximize energy efficiency,and ensure that the throughput is not lower than the throughput obtained by the first step user scheduling to achieve joint optimization.The final simulation data shows that,compared with the existing algorithms,this algorithm has certain advantages in both energy efficiency optimization and throughput optimization.