Networked ISAC for Low-Altitude Economy: Transmit Beamforming and UAV Trajectory Design

TL;DR

This paper proposes a joint design of transmit beamforming and UAV trajectories in a networked ISAC system to enhance UAV communication and airspace sensing, balancing both objectives effectively.

Contribution

It introduces an innovative joint optimization framework for beamforming and UAV paths in networked ISAC, addressing non-convex challenges with an efficient algorithm.

Findings

Significant performance improvements over benchmarks.

Effective tradeoff between sensing and communication.

Validated through numerical simulations.

Abstract

This paper studies the exploitation of networked integrated sensing and communications (ISAC) to support low-altitude economy (LAE), in which a set of networked ground base stations (GBSs) transmit wireless signals to cooperatively communicate with multiple authorized unmanned aerial vehicles (UAVs) and concurrently use the echo signals to detect the invasion of unauthorized objects in interested airspace. Under this setup, we jointly design the cooperative transmit beamforming at multiple GBSs together with the trajectory control of authorized UAVs and their GBS associations, for enhancing the authorized UAVs' communication performance while ensuring the sensing requirements for airspace monitoring. In particular, our objective is to maximize the average sum rate of authorized UAVs over a particular flight period, subject to the minimum illumination power constraints for sensing over the interested airspace, the maximum transmit power constraints at individual GBSs, and the flight constraints at UAVs. This problem is non-convex and challenging to solve, due to the involvement of integer variables and the coupling of optimization variables. To solve this non-convex problem, we propose an efficient algorithm by using the techniques of alternating optimization (AO), successive convex approximation (SCA), and semi-definite relaxation (SDR). Numerical results show that the obtained transmit beamforming and UAV trajectory designs in the proposed algorithm efficiently balance the tradeoff between the sensing and communication performances, thus significantly outperforming various benchmarks.