Radar mutual information maximization for movable antenna-enabled ISAC systems
Author Identifier (ORCID)
Abstract
This letter jointly optimizes transmit beamforming and antenna positions for an integrated sensing and communication (ISAC) system equipped with movable antennas (MAs). We consider a downlink dual-functional radar-communication system, where a base station (BS) serves a group of communication users while detecting multiple targets. The objective is to maximize the radar mutual information (MI), subject to the transmit power, communication signal-to-interference-plus-noise-ratio (SINR) and MA geometry constraints. This problem is challenging due to the strong non-convexity of the objective and tightly coupled variables. We derive an asymptotically tight upper bound for the radar MI, and develop an efficient alternating optimization algorithm that applies semidefinite relaxation (SDR) for beamforming and successive convex approximation (SCA) for antenna positions. The optimality of the beamforming is ensured by retaining the rank-one property after SDR. Simulations show that our algorithm offers a substantial gain in sensing capability, improving radar MI considerably over benchmarks.
Keywords
Integrated sensing and communication, movable antennas, mutual information, successive convex approximation
Document Type
Journal Article
Date of Publication
1-1-2026
Volume
15
Publication Title
IEEE Wireless Communications Letters
Publisher
IEEE
School
School of Engineering
Funders
Innovation Program of Shanghai Municipal Science and Technology Commission (Grant Number: 25DP1500300) / National Natural Science Foundation of China (Grant Number: 62231010).
Copyright
subscription content
First Page
2574
Last Page
2578
Comments
Liu, B., Zhu, P., Ni, W., & Wang, X. (2026). Radar mutual information maximization for movable antenna-enabled ISAC systems. IEEE Wireless Communications Letters, 15, 2574–2578. https://doi.org/10.1109/LWC.2026.3683202