Movable-Antenna Position Optimization for Physical-Layer Security via Discrete Sampling

Abstract: Fluid antennas (FAs) and mobile antennas (MAs) are innovative technologies in wireless communications that are able to proactively improve channel conditions by dynamically adjusting the transmit/receive antenna positions within a given spatial region. In this paper, we investigate an MA-enhanced multiple-input single-output (MISO) secure communication system, aiming to maximize the secrecy rate by jointly optimizing the positions of multiple MAs. Instead of continuously searching for the optimal MA positions as in prior works, we propose to discretize the transmit region into multiple sampling points, thereby converting the continuous antenna position optimization into a discrete sampling point selection problem. However, this point selection problem is combinatory and thus difficult to be optimally solved. To tackle this challenge, we ingeniously transform this combinatory problem into a recursive path selection problem in graph theory and propose a partial enumeration algorithm to obtain its optimal solution without the need for high-complexity exhaustive search. To further reduce the complexity, a linear-time sequential update algorithm is also proposed to obtain a high-quality suboptimal solution. Numerical results show that our proposed algorithms yield much higher secrecy rates as compared to the conventional FPA and other baseline schemes.