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

TL;DR

This paper presents a networked ISAC framework for low-altitude economy, jointly optimizing UAV trajectories and GBS beamforming to enhance communication and sensing in 3D space, with algorithms addressing complex non-convex problems.

Contribution

It introduces a novel joint design of transmit beamforming and UAV trajectories for integrated sensing and communications in 3D space, considering multiple GBSs and UAV capabilities.

Findings

Proposed algorithms effectively balance sensing and communication tradeoffs.

Joint design significantly outperforms benchmark schemes.

Achieves high UAV sum rate with sensing constraints satisfied.

Abstract

This paper exploits the networked integrated sensing and communications (ISAC) to support low-altitude economy (LAE), in which a set of networked ground base stations (GBSs) cooperatively transmit joint information and sensing signals to communicate with multiple authorized unmanned aerial vehicles (UAVs) and concurrently detect unauthorized objects over the interested region in the three-dimensional (3D) space. We assume that each GBS is equipped with uniform linear array (ULA) antennas, which are deployed either horizontally or vertically to the ground. We also consider two types of UAV receivers, which have and do not have the capability of canceling the interference caused by dedicated sensing signals, respectively. Under each setup, we jointly design the coordinated transmit beamforming at multiple GBSs together with the authorized UAVs' trajectory control and their GBS associations, for enhancing the authorized UAVs' communication performance while ensuring the sensing requirements. In particular, we aim to maximize the average sum rate of authorized UAVs over a given flight period, subject to the minimum illumination power constraints toward the interested 3D sensing region, the maximum transmit power constraints at individual GBSs, and the flight constraints of UAVs. These problems are highly non-convex and challenging to solve, due to the involvement of binary UAV-GBS association variables as well as the coupling of beamforming and trajectory variables. To solve these non-convex problems, we propose efficient algorithms by using the techniques of alternating optimization, successive convex approximation, and semi-definite relaxation. Numerical results show that the proposed joint coordinated transmit beamforming and UAV trajectory designs efficiently balance the sensing-communication performance tradeoffs and significantly outperform various benchmarks.