Rotatable and Movable Antenna-Enabled Near-Field Integrated Sensing and Communication

Integrated sensing and communication (ISAC) is regarded as a promising technology for next-generation communication networks. As the demand for communication performance significantly increases, extremely large-scale antenna arrays and tremendously high-frequency bands get widely applied in communication systems, leading to the expansion of the near-field region. On a parallel track, movable antennas (MAs) and six-dimensional MAs (6DMAs) are proposed as emerging technologies to improve the performance of communication and sensing. Based on such a background, this paper investigates the performance of ISAC systems in the near-field region, focusing on a novel system architecture that employs rotatable MAs (RMAs). Additionally, a spherical wave near-field channel model with respect to RMAs' rotations and positions is derived by considering the effective aperture loss. Two designs are explored: a sensing-centric design that minimizes the Cram\'er-Rao bound (CRB) with signal-to-interference-plus-noise ratio (SINR) constraints, and a communication-centric design that maximizes the sum-rate with a CRB constraint. To solve the formulated optimization problems, the paper proposes two alternating optimization (AO) based algorithms composed of the semidefinite relaxation (SDR) method and the particle swarm optimization (PSO) method. Numerical results demonstrate the convergence and effectiveness of the proposed algorithms and the superiority of the proposed setups for both sensing and communication performance compared to traditional fixed antenna systems, highlighting the potential of RMAs to enhance ISAC systems in near-field scenarios.

Sum-Rate Optimization for RIS-Aided Multiuser Communications with Movable Antenna

Reconfigurable intelligent surface (RIS) is known as a promising technology to improve the performance of wireless communication networks, which has been extensively studied. Movable antenna (MA) is a novel technology that fully exploits the antenna position for enhancing the channel capacity. In this paper, we propose a new RIS-aided multiuser communication system with MAs. The sum-rate is maximized by jointly optimizing the beamforming, the reflection coefficient (RC) values of RIS and the positions of MAs. A fractional programming-based iterative algorithm is proposed to solve the formulated non-convex problem, considering three assumptions for the RIS. Numerical results are presented to verify the effectiveness of the proposed algorithm and the superiority of the proposed MA-based system in terms of sum-rate.