Utility Maximization in Digital Twin Enabled 6G Network with Joint Communication and Sensing

Autonomous mobility with joint communication and sensing is an emerging paradigm of 6G networks. Further, Digital Twin is another aspect when integrated with autonomous mobility augments the real-world in virtual space. In this paper, we consider a scenario where Digital Twin of an autonomous vehicle having joint communication and sensing capability resides in an edge computing platform as applicable in a 6G network. In this context, our objective is to maximize the overall utility of the system while considering the network constraints such as bandwidth, latency, reliability, and power constraints. Initially, we prove the NP-hardness of the problem by reduction from the multiple knapsack problem and propose a greedy heuristic and a two-phase approximation algorithm with a - approximation ratio. The simulation results show how the two algorithms perform in terms of latency, reliability, and computational power requirements.