Optimization Of Joint Communication And Sensing System Assisted By Distributed Multi-hop RISs

Joint Communication and Sensing(JCAS)technology is considered as one of the key technologies of 6G network as the requirements of end-to-end information processing capability of future network become higher and higher.This technology integrates communication and perception together,which can achieve the purpose of improving performance and reducing cost.In order to make the interaction between the base Station(BS)and vehicles more frequent,and enhance the information processing ability of the BS,the JCAS technology is introduced into the connected automated vehicles(CAV)network.At the same time,in CAV network,the huge number of vehicles and the demand for high data transmission rate make energy consumption become a problem that can not be ignored in CAV network design,so energy efficiency and rate are important performance indicators in CAV network.In order to maximize the energy efficiency and sensing rate of the communication and sensing system,Reconfigurable Intelligence Surfaces(RISs)are applied to the JCAS system.The BS operating in the millimeter wave frequency band provides communication and sensing services for vehicles.Specifically,the BS senses the information around the vehicle and transmits real-time road condition information to the vehicle.However,the direct link formed between the BS and the vehicle may be blocked by obstacles(high-rise buildings,hills,etc.),which leads to excessive signal propagation loss and affects the performance of communication and sensing.Therefore,multi-hop RISs is introduced into the system to enhance the quality of the signal in a specific direction by dynamically adjusting the amplitude and phase of the signal,so as to ensure the smooth progress of communication and perception.According to this model,in the communication phase,this paper proposes an energy-saving optimization strategy,which maximizes the energy efficiency of the system by jointly optimizing the phase shift matrix,the transmit power and the RISs switch.In this optimization problem,the successive convex approximation-based alternating optimization algorithm is used to solve the RISs phase shift matrix optimization subproblem,and the Lambert-w function and Newton method are used to solve the transmission power optimization subproblem in the communication phase,and the coordinate descent method is used to solve the RISs switches optimization subproblem.In the sensing phase,the sensing rate and the sensing energy efficiency are taken as the optimization objectives,respectively,and the transmit power allocation problem is solved by using the interior point method and the greedy algorithm.In order to verify the feasibility of the model,this paper uses matlab to carry out numerical simulations.The results show that the energy efficiency of the proposed distributed multi-hop RISs-assisted CAV communication network is better than that of the traditional amplify-and-forward relay.In the sensing phase,the maximum sensing rate and the optimal energy efficiency are obtained by using the interior point method and the greedy algorithm,respectively.And in the greedy algorithm,the step size of the arithmetic sequence used is better than the fixed step size in terms of convergence speed and accuracy.