Joint Maneuver and Beamforming Design for UAV-Enabled Integrated Sensing and Communication

This paper studies the unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC), in which UAVs are dispatched as aerial dual-functional access points (APs) that can exploit the UAV maneuver control and strong line-of-sight (LoS) air-to-ground (A2G) links for efficient communication and sensing. In particular, we consider that one UAV-AP, equipped with a vertically placed uniform linear array (ULA), sends combined information and sensing signals to communicate with multiple users and at the same time sense potential targets at interested areas on the ground. Under this setup, we consider two scenarios with quasi-stationary and fully mobile UAVs, in which the UAV is deployed at an optimizable location over the whole ISAC mission period and can fly over different locations during the ISAC mission period, respectively. For the two scenarios, our objective is to jointly design the UAV maneuver (deployment location or flight trajectory) and the transmit beamforming, for maximizing the weighted sum-rate throughput of communication users, while ensuring the sensing beampattern gain requirements, subject to the transmit power and flight constraints. However, due to the ULA consideration at the UAV, the two formulated problems are highly non-convex and very difficult to be optimally solved, as the UAV’s location/trajectory variables are involved on the exponent parts of each entry in the steering vectors, and are closely coupled with the transmit beamforming vectors. To tackle this issue, we propose efficient algorithms to find their suboptimal but high-quality solutions, by using various techniques from convex and non-convex optimization. Finally, numerical results are provided to validate the superiority of our proposed designs as compared to various benchmark schemes with heuristic maneuver designs. It is shown that the joint maneuver and transmit beamforming design efficiently balances the inherent tradeoff between sensing and communication with regards to different beampattern gain thresholds.

I. Introduction

Recent advancements in fifth generation (5G)-and-beyond networks are envisioned to enable many environment- and location-aware intelligent applications such as auto-driving, remote healthcare, and smart industry. To support these applications, 5G-and-beyond networks are expected to provide high-precision sensing capabilities, in addition to conventional wireless communication services [2]. Towards this end, integrated sensing and communication (ISAC) [3], [4] (a.k.a. radar-communication (RadCom) [5], dual-functional radar communication (DFRC) [6], [7], joint communication and radar sensing (JCAS) [2]) has recently been recognized as one of the key technologies that has attracted tremendous research interests from both academia and industry [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12]. ISAC provides various advantages over conventional wireless networks with communication functionality only or with separately designed radar and communication [13], [14], [15]. First, ISAC allows wireless infrastructures and scarce spectrum resources to be seamlessly shared for the dual use of both sensing and communication, thus leading to significantly enhanced spectrum, energy, and hardware utilization efficiency. Next, with the on-going deployment of millimeter wave and massive multiple-input-multiple-output (MIMO), the communication signals become very effective in providing ultra-high sensing accuracy and resolution [16]. Furthermore, the integrated sensing functionality can also benefit the communication design [3], e.g., the sensory data can be leveraged to facilitate the beam training in vehicle-to-everything (V2X) networks [5].