Movable Antenna-Aided Near-Field Integrated Sensing and Communication

Integrated sensing and communication (ISAC) is emerging as a pivotal technology for next-generation wireless networks. However, existing ISAC systems are based on fixed-position antennas (FPAs), which inevitably incur a loss in performance when balancing the trade-off between sensing and communication. Movable antenna (MA) technology offers promising potential to enhance ISAC performance by enabling flexible antenna movement. Nevertheless, exploiting more spatial channel variations requires larger antenna moving regions, which may invalidate the conventional far-field assumption for channels between transceivers. Therefore, this paper utilizes the MA to enhance sensing and communication capabilities in near-field ISAC systems, where a full-duplex base station (BS) is equipped with multiple transmit and receive MAs movable in large-size regions to simultaneously sense multiple targets and serve multiple uplink (UL) and downlink (DL) users for communication. We aim to maximize the weighted sum of sensing and communication rates (WSR) by jointly designing the transmit beamformers, sensing signal covariance matrices, receive beamformers, and MA positions at the BS, as well as the UL power allocation. The resulting optimization problem is challenging to solve, while we propose an efficient two-layer random position (RP) algorithm to tackle it. In addition, to reduce movement delay and cost, we design an antenna position matching (APM) algorithm based on the greedy strategy to minimize the total MA movement distance. Extensive simulation results demonstrate the substantial performance improvement achieved by deploying MAs in near-field ISAC systems. Moreover, the results show the effectiveness of the proposed APM algorithm in reducing the antenna movement distance, which is helpful for energy saving and time overhead reduction for MA-aided near-field ISAC systems with large moving regions.

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.

Prototype of Secure Wire-Line Telephone

This paper proposes a secure wire-line telephone prototype that leverages physical layer security (PLS) techniques to protect communications from wiretapping. The system generates artificial noise (AN) in both directions over a telephone line and utilizes a telephone hybrid circuit to achieve effective AN cancellation. We conduct a thorough analysis of the secrecy capacity and evaluate the system's performance through both simulations and practical experiments. The results demonstrate that the proposed scheme significantly enhances communication security while preserving the integrity of legitimate signals, making it a robust and viable solution for secure telephone systems.

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).

High-Precision Channel Estimation for Sub-Noise Self-Interference Cancellation

Self-interference cancellation plays a crucial role in achieving reliable full-duplex communications. In general, it is essential to cancel the self-interference signal below the thermal noise level, which necessitates accurate reconstruction of the self-interference signal. In this paper, we propose a high-precision channel estimation method specifically designed for sub-noise self-interference cancellation. Exploiting the fact that all transmitted symbols are known to their respective receivers, our method utilizes all transmitted symbols for self-interference channel estimation. Through analytical derivations and numerical simulations, we validate the effectiveness of the proposed method. The results demonstrate the superior performance of our approach in achieving sub-noise self-interference cancellation.

Next-Generation Full Duplex Networking System Empowered by Reconfigurable Intelligent Surfaces

Full duplex (FD) radio has attracted extensive attention due to its co-time and co-frequency transceiving capability. {However, the potential gain brought by FD radios is closely related to the management of self-interference (SI), which imposes high or even stringent requirements on SI cancellation (SIC) techniques. When the FD deployment evolves into next-generation mobile networking, the SI problem becomes more complicated, significantly limiting its potential gains.} In this paper, we conceive a multi-cell FD networking scheme by deploying a reconfigurable intelligent surface (RIS) at the cell boundary to configure the radio environment proactively. To achieve the full potential of the system, we aim to maximize the sum rate (SR) of multiple cells by jointly optimizing the transmit precoding (TPC) matrices at FD base stations (BSs) and users and the phase shift matrix at RIS. Since the original problem is non-convex, we reformulate and decouple it into a pair of subproblems by utilizing the relationship between the SR and minimum mean square error (MMSE). The optimal solutions of TPC matrices are obtained in closed form, while both complex circle manifold (CCM) and successive convex approximation (SCA) based algorithms are developed to resolve the phase shift matrix suboptimally. Our simulation results show that introducing an RIS into an FD networking system not only improves the overall SR significantly but also enhances the cell edge performance prominently. More importantly, we validate that the RIS deployment with optimized phase shifts can reduce the requirement for SIC and the number of BS antennas, which further reduces the hardware cost and power consumption, especially with a sufficient number of reflecting elements. As a result, the utilization of an RIS enables the originally cumbersome FD networking system to become efficient and practical.