Resource Allocation for Multi-Cell Cooperative Integrated Sensing and Communication with UAVs

‍ ‍The integrated sensing and communication is to realize the dual functions of wireless communication and radar sensing at the same time through the reuse of radio frequency signals to achieve mutual benefit. On the one hand， different types of sensing missions can be processed based on existing communication systems； on the other hand， the sensing results can be used to assist communication， so as to improve the QoS （quality-of-service） and communication efficiency. However， since the purposes of sensing and communication are not exactly the same， this makes the performance trade-off between sensing and communication very critical. This paper studied the multi-cell cooperative integrated sensing and communication （ISAC） with unmanned aerial vehicles （UAVs）， in which the base stations （BSs） act as ISAC transceivers to send individual messages to their respective cellular-connected UAV users， and at the same time estimate the location of the sensing target. As such， we jointly designed the cooperative power control among BSs and UAV trajectory to minimize the energy consumption of the BSs， while satisfying the signal-to-interference-noise ratio （SINR） requirements of UAV users and the Cramer-Rao lower bound （CRLB） requirement for target location estimation. Since the variables are coupled together and the SINR constraints are non-convex， the formulated problem is non-convex and difficult to be tackled in general. To deal with this challenge， we proposed an efficient algorithm based on the alternating optimization to jointly optimize the BSs’ power control as well as the UAV trajectory. In particular， the power control problem and the UAV trajectory problem are solved by using the techniques of semi-definite relaxation （SDR） and successive convex approximation （SCA）， respectively. For each iteration， the updated objective value of the original problem is ensured to be monotonically non-decreasing， and as a result， the convergence of the proposed algorithm is ensured. Finally， the performance of the proposed joint design is verified by numerical results.