Resource Allocation Strategy Of IRS-aided D2D Communication Systems

Multimedia services and wireless devices are gaining popularity,the number of device connections in wireless networks has increased dramatically.Traditional wireless communication systems are increasingly struggling to meet the increasing demand for transmission rate and spectral efficiency.Device-to-Device(D2D)communication is considered to be one of the most promising solutions.Although D2 D communication has the potential to improve bandwidth utilization and reduce the load of base station(BS),it also brings serious interference due to spectrum sharing.How to allocate resources reasonably to reduce co-channel interference between users has become one of the biggest challenges for D2 D communication.On the other hand,Intelligent Reflective Surface(IRS)is an emerging low-cost technology that can improve signal propagation to enhance the wireless network by controlling the phase shift and amplitude of the intelligent reflector components.While providing reflection path gain,IRS will also bring reflection interference to the user.The signal reflected by IRS can adjust the phase shift and amplitude of the received signal through the component,enhance the signal that the receiver expects to receive,and suppress the interference of the reflected signal.Applying the IRS to the D2 D communication system can further improve the throughput,but the interference suppression problem becomes more complicated.Therefore,how to effectively optimize the allocation of wireless resources is still a problem to be solved in the IRS-assisted D2 D communication system,especially when multiple D2 D users share a channel.In this paper,the total rate optimization of IRS-assisted D2 D communication system is studied from the aspects of subchannel allocation,phase shift selection and power control.The specific research contents and innovations are summarized as follows :1.The applicable scene and principle of IRS working in wireless network are introduced.In order to derive the expression of the system sum rate,the interference of IRS aided D2 D communication system is analyzed.The simulation results show that the sum rate of D2 D communication system assisted by IRS is significantly higher than that of the traditional D2 D communication system even if the phase shift of the component is not optimized under the condition of equal power.Other than that,the simulation results also show that when the number of D2 D users increases,effective radio resource management strategies are needed to improve the system rate due to the increase of co-channel interference and the decrease of system performance.2.In the scenario of IRS assisted coexistence of multiple cellular users and D2 D users,a distributed resource allocation strategy based on combinatorial auction is proposed.Firstly,a combinatorial auction model for maximizing the sum rate of IRS-assisted D2 D communication system is constructed.Then,the sub-channel allocation is completed by using the multi-round combinatorial auction game including the bidding stage and the adjustment stage.Finally,an alternating iterative optimization scheme is designed to complete the phase shift selection and power control sub-problems.Simulation results show that compared with the traditional resource allocation scheme,the proposed algorithm has obvious advantages in improving the system sum rate and reducing the power consumption of users.3.In order to reduce the complexity of the optimization algorithm,the previous alternating iterative algorithm is improved,and a joint power and phase shift optimization algorithm based on particle swarm optimization is proposed.Firstly,the fitness function with penalty term is established with the goal of maximizing the system sum rate and the user signal to interference plus noise ratio(SINR)as the constraint condition.Then,an update scheme based on penalty value priority is designed for discrete phase shift optimization variables and continuous power optimization variables.Finally,the proposed scheme is simulated.The simulation results show that the proposed scheme effectively reduces the complexity of the algorithm and the optimization effect is close to the alternating iterative optimization scheme.