Joint Beamforming and Position Design for Movable Antenna Assisted LEO ISAC Systems

TL;DR

This paper proposes a joint beamforming and position optimization method for movable antenna-assisted LEO ISAC systems, significantly improving sensing accuracy and communication performance through an innovative AO-based algorithm.

Contribution

It introduces a novel joint optimization framework for beamforming and antenna positioning in LEO ISAC systems, employing SDR and AO techniques to enhance sensing and communication trade-offs.

Findings

At least 25% gain in sensing performance.

Effective convergence of the proposed algorithm.

Improved trade-off between communication and sensing.

Abstract

Low earth orbit (LEO) satellite-assisted integrated sensing and communications (ISAC) systems have been extensively studied to achieve ubiquitous connectivity. However, the severe signal attenuation and limited transmit power at LEO satellites can degrade ISAC performance. To address this issue, this paper investigated movable antenna (MA)-assisted LEO ISAC systems. We derive the communication signal-to-interference-plus-noise ratio (SINR) and the sensing squared position error bound (SPEB) for evaluating the ISAC performance. Then, we jointly optimize the transmit beamforming and the MA positions to minimize the SPEB under the SINR constraints, total transmit power constraint, and several inherent physical constraints of the MA array. We first simplify the complex problem using the semidefinite relaxation (SDR). Then, we present a novel alternating optimization (AO)-based algorithm to decouple the original problem into two subproblems, consequently convexified and solved. Simulations demonstrate the convergence and effectiveness of the proposed algorithm. Better trade-off between communication and sensing performance, and at least 25% gain in sensing performance are achieved, compared to the benchmarks.