Secure Analog Beamforming Design for Wireless Communication Systems With Movable Antennas

TL;DR

This paper introduces a novel movable antenna system for wireless communication that optimizes analog beamforming and antenna positions to enhance physical layer security, using a penalty product manifold optimization approach.

Contribution

It proposes a new optimization framework combining penalty functions and manifold methods to jointly optimize beamforming and antenna positions for improved secrecy.

Findings

Movable antennas significantly increase secrecy rate.

The proposed PPM method efficiently solves the non-convex optimization problem.

Simulation confirms superior performance over fixed-position antenna systems.

Abstract

Movable antennas (MA) are a novel technology that allows for the flexible adjustment of antenna positions within a specified region, thereby enhancing the performance of wireless communication systems. In this paper, we explore the use of MA to improve physical layer security in an analog beamforming (AB) communication system. Our goal is to maximize the secrecy rate by jointly optimizing the transmit AB and MA position, subject to constant modulus (CM) constraints on the AB and position constraints for the MA. The resulting problem is non-convex, and we propose a penalty product manifold (PPM) method to solve it efficiently. Specifically, we convert the inequality constraints related to MA position into a penalty function using smoothing techniques, thereby reformulating the problem as an unconstrained optimization on the product manifold space (PMS). We then derive a parallel conjugate gradient descent (PCGD) algorithm to update both the AB and MA position on the PMS. This method is efficient, providing an analytical solution at each step and ensuring convergence to a KKT point. Simulation results show that the MA system achieves a higher secrecy rate than systems with fixed-position antennas.