Integrated sensing and communication(IS AC)is emerging as a key technology for future cellular networks.This paper focuses on the collaborative ISAC mechanism between base stations(BSs)and users using reference signal...Integrated sensing and communication(IS AC)is emerging as a key technology for future cellular networks.This paper focuses on the collaborative ISAC mechanism between base stations(BSs)and users using reference signals(RSs).The main challenges we address are the joint optimization of downlink communication and sensing resources,the selection of users as sensing anchors,as well as the fusion of estimation data between the BS and users.We formulate the collaborative ISAC problem as a multiobjective programming framework,which can balance system performance in sensing and individual benefits in communication.Particularly,to ensure fairness,we propose minimizing the largest sensing age across all users.On this basis,we put forward an efficient solution algorithm that enables a low-complexity computation of the Pareto front when it exists.Simulation results demonstrate that the proposed collaborative ISAC mechanism is capable of efficiently enhancing the system’s sensing capacity while ensuring fairness in user scheduling for sensing.展开更多
基金supported by the National Natural Science Foundation of China under Grant 62201032Fundamental Research Founds for the Central Universities under Grant FRF-TP-22-045A1Young Elite Scientists Sponsorship Program by BAST.
文摘Integrated sensing and communication(IS AC)is emerging as a key technology for future cellular networks.This paper focuses on the collaborative ISAC mechanism between base stations(BSs)and users using reference signals(RSs).The main challenges we address are the joint optimization of downlink communication and sensing resources,the selection of users as sensing anchors,as well as the fusion of estimation data between the BS and users.We formulate the collaborative ISAC problem as a multiobjective programming framework,which can balance system performance in sensing and individual benefits in communication.Particularly,to ensure fairness,we propose minimizing the largest sensing age across all users.On this basis,we put forward an efficient solution algorithm that enables a low-complexity computation of the Pareto front when it exists.Simulation results demonstrate that the proposed collaborative ISAC mechanism is capable of efficiently enhancing the system’s sensing capacity while ensuring fairness in user scheduling for sensing.
