Research On Efficient Resource Allocation Algorithm Of Cellular And D2D Converged Communication System

Device-to-Device(D2D)communication technology is a research hotspot in the field of wireless communication in recent years.It supports the direct communication of terminal equipment by reusing the spectrum resources of the cellular system,which can greatly reduce the base station load while increasing the system capacity and spectrum utilization.However,the introduction of D2 D also brings additional interference and energy consumption to the cellular system.How to coordinate the resource allocation of cellular users and D2 D users,and improve energy efficiency while improving spectrum efficiency,has become a challenging problem for current D2 D communication.Aiming at this problem,this thesis studies the efficient allocation of resources in the cellular and D2 D converged communication system from the perspectives of working mode selection,joint power control,and time-frequency resource scheduling,and designs the corresponding resource allocation algorithm.The main research contents and results of this thesis are as follows:(1)A scheme of Underlay mode selection based on distance and joint power control is proposed.The solution determines whether D2 D users use Underlay mode to communicate according to the ratio of the distance between D2 D users and cellular users and the base station,and then realizes the joint power control of D2 D and cellular links under the condition of restricting the transmission power of cellular users and D2 D users,and deduced The optimal user power allocation scheme that can maximize the total system throughput.The simulation results show that the mode selection scheme and its power control algorithm proposed in this thesis can effectively reduce the interference between the cellular system and the D2 D system,and at the same time increase the total throughput of the D2 D and cellular fusion system.(2)A high-energy-efficient resource allocation algorithm for multi-user D2 D systems based on Q-learning is proposed.Mapping the resource allocation problem of the multi-user D2 D system to a reinforcement learning problem,designing a corresponding Q learning algorithm to dynamically optimize the resource block selected by each D2 D user for multiplexing,and realizing all D2 D links under the premise of ensuring the Qo S of cellular users Maximum total energy efficiency.The simulation results show that the D2 D resource allocation algorithm based on Q-learning proposed in this paper can effectively improve the total energy efficiency of the multi-user D2 D system,and the algorithm complexity is low.The research in this thesis shows that a reasonable choice of D2D/cellular communication mode and power optimization control can effectively improve the system capacity;the introduction of machine learning into the resource management of the D2 D system can help improve the energy efficiency of the system.The research results of this thesis have certain guiding significance for solving the resource allocation problem of the cellular and D2 D converged communication system.