Polarforming for Wireless Communications: Modeling and Performance Analysis

This paper presents, for the first time, the concept of \textit{polarforming} for wireless communications. Polarforming refers to a novel technique that enables dynamic adjustment of antenna polarization using reconfigurable polarized antennas (RPAs). It can fully leverage polarization diversity to improve the performance of wireless communication systems by aligning the effective polarization state of the incoming electromagnetic (EM) wave with the antenna polarization. To better demonstrate the benefits of polarforming, we propose a general RPA-aided system that allows for tunable antenna polarization. A wavefront-based channel model is developed to properly capture depolarization behaviors in both line-of-sight (LoS) and non-line-of-sight (NLoS) channels. Based on this model, we provide a detailed description of transmit and receive polarforming on planes of polarization (PoPs). We also evaluate the performance gains provided by polarforming under stochastic channel conditions. Specifically, we derive a closed-form expression for the relative signal-to-noise ratio (SNR) gain compared to conventional fixed-polarization antenna (FPA) systems and approximate the cumulative distribution function (CDF) for the RPA system. Our analysis reveals that polarforming offers a diversity gain of two, indicating full utilization of polarization diversity for dual-polarized antennas. Furthermore, extensive simulation results validate the effectiveness of polarforming and exhibit substantial improvements over conventional FPA systems. The results also indicate that polarforming not only can combat depolarization effects caused by wireless channels but also can overcome channel correlation when scattering is insufficient.

Power-Efficient Full-Duplex Satellite Communications Aided by Movable Antennas

This letter investigates a movable antenna (MA)-aided full-duplex (FD) satellite communication system, where the satellite, equipped with both transmit and receive MAs, serves multiple uplink (UL) and downlink (DL) user terminals (UTs) in FD mode. Specifically, we formulate a multiobjective optimization problem to minimize the UL and DL transmit powers under imperfect channel state information (CSI) conditions. To jointly optimize the MA positions and transmit powers, we propose a two-loop particle swarm optimization (PSO) algorithm based on a multiobjective optimization framework. Simulation results demonstrate that flexible adjustments of MA positions can effectively reduce the total UL and DL transmit powers, while also alleviating the burden on self-interference (SI) cancellation modules.

Near-Field Multiuser Communications Aided by Movable Antennas

This letter investigates movable antenna (MA)-aided downlink (DL) multiuser communication systems under the near-field channel condition, in which both the base station (BS) and the users are equipped with MAs to fully exploit the degrees of freedom (DoFs) in antenna position optimization by leveraging the wireless channel variation in spatial regions of large size. The objective is to minimize the transmit power by jointly optimizing the beamformers and the MA positions while satisfying the minimum-achievable-rate requirement for each user. We propose a two-loop dynamic neighborhood pruning particle swarm optimization (DNPPSO) algorithm that significantly reduces computational complexity while effectively maintaining the performance of the standard particle swarm optimization (PSO) algorithm. Simulation results validate the effectiveness and advantages of the proposed scheme in power-saving for multiuser communications.

New Paradigm for Secure Full-Duplex Transmission: Movable Antenna-Aided Multi-User Systems

In this paper, we investigate physical layer security (PLS) for full-duplex (FD) multi-user systems. To simultaneously protect uplink (UL) and downlink (DL) transmissions and ensure efficient use of time-frequency resources, we consider a base station (BS) that operates in FD mode and enables to emit the artificial noise (AN). Conventional fixed-position antennas (FPAs) at the BS struggle to fully exploit spatial degrees of freedom (DoFs). Therefore, we propose a new paradigm for secure FD multi-user systems, where multiple transmit and receive movable antennas (MAs) are deployed at the BS to serve UL and DL users and effectively counter the cooperative interception by multiple eavesdroppers (Eves). Specifically, the MA positions, the transmit, receive, and AN beamformers at the BS, and the UL powers are jointly optimized to maximize the sum of secrecy rates (SSR). To solve the challenging non-convex optimization problem with highly coupled variables, we propose an alternating optimization (AO) algorithm. This algorithm decomposes the original problem into three sub-problems, which are iteratively solved by the proposed multi-velocity particle swarm optimization (MVPSO) and successive convex approximation (SCA). Simulation results demonstrate that the proposed scheme for MA-aided secure FD multi-user systems can significantly enhance security performance compared to conventional FPA systems.

Secure Full-Duplex Communication via Movable Antennas

This paper investigates physical layer security (PLS) for a movable antenna (MA)-assisted full-duplex (FD) system. In this system, an FD base station (BS) with multiple MAs for transmission and reception provides services for an uplink (UL) user and a downlink (DL) user. Each user operates in half-duplex (HD) mode and is equipped with a single fixed-position antenna (FPA), in the presence of a single-FPA eavesdropper (Eve). To ensure secure communication, artificial noise (AN) is transmitted to obstruct the interception of Eve. The objective of this paper is to maximize the sum secrecy rate (SSR) of the UL and DL users by jointly optimizing the beamformers of the BS and the positions of MAs. This paper also proposes an alternating optimization (AO) method to address the non-convex problem, which decomposes the optimization problem into three subproblems and solves them iteratively. Simulation results demonstrate a significant performance gain in the SSR achieved by the proposed scheme compared to the benchmark schemes.

Movable Antenna-Enabled Co-Frequency Co-Time Full-Duplex Wireless Communication

Movable antenna (MA) provides an innovative way to arrange antennas that can contribute to improved signal quality and more effective interference management. This method is especially beneficial for co-frequency co-time full-duplex (CCFD) wireless communication, which struggles with self-interference (SI) that usually overpowers the desired incoming signals. By dynamically repositioning transmit/receive antennas, we can mitigate the SI and enhance the reception of incoming signals. Thus, this paper proposes a novel MA-enabled point-to-point CCFD system and formulates the minimum achievable rate of two CCFD terminals. To maximize the minimum achievable rate and determine the near-optimal positions of the MAs, we introduce a solution based on projected particle swarm optimization (PPSO), which can circumvent common suboptimal positioning issues. Moreover, numerical results reveal that the PPSO method leads to a better performance compared to the conventional alternating position optimization (APO). The results also demonstrate that an MA-enabled CCFD system outperforms the one using fixed-position antennas (FPAs).