Movable antenna (MA) technology has recently emerged as a promising paradigm to flexibly reshape wireless channels, thereby enhancing system performance beyond the limits of traditional fixed-position antennas (FPAs). In this paper, we investigate an MA-assisted multiple-input multiple-output (MIMO) simultaneous wireless information and power transfer (SWIPT) network, where an access point (AP) equipped with multiple MAs serves both multi-FPA information decoding users (IDUs) and multi-FPA energy harvesting users (EHUs). Our objective is to maximize the weighted sum harvested power of all EHUs by jointly optimizing the transmit precoding matrices and the positions of MAs, subject to the constraints on the maximum transmit power of the AP, quality of service of each IDU, confined MA moving region, and minimum inter-MA distance. To tackle the non-convexity of this problem, we first transform the original optimization problem into a more tractable equivalent form by leveraging the weighted minimum mean square error (WMMSE) approach. Next, we start with the single-IDU single-EHU scenario and propose an efficient block coordinate descent (BCD) algorithm. Specifically, the transmit precoding matrix and MA positions are iteratively optimized based on the successive convex approximation (SCA) technique. The proposed algorithm is then extended to the general multi-IDU multi-EHU scenario. Finally, simulation results show that the proposed MA-assisted MIMO SWIPT system significantly outperforms conventional FPA systems and other benchmark schemes in terms of the weighted sum harvested power, validating the superiority of MAs in proactively reconfiguring channel conditions to boost energy transfer efficiency.

In this work, we investigate a movable antenna (MA) enhanced secure uplink non-orthogonal multiple access (NOMA) network, where multiple legitimate users, each equipped with an MA, transmit confidential information to the base station in the presence of an eavesdropper. Our goal is to maximize the system's secrecy sum rate by jointly optimizing the positions of MAs, the transmit power of each user, and the receive combining vectors at the base station. To tackle the formulated non-convex problem, we first transform it into a more tractable form and then develop a customized heuristics algorithm by invoking particle swarm optimization (PSO) to obtain a high-quality suboptimal solution. Simulation results validate the efficacy of our proposed algorithm, demonstrating its superior performance over conventional fixed-position antenna (FPA) systems and other baselines.

Movable antenna (MA) has been deemed as a promising technology to flexibly reconfigure wireless channels by adjusting the antenna positions in a given local region. In this paper, we investigate the application of the MA technology in both decode-and-forward (DF) and amplify-and-forward (AF) relaying systems, where a relay is equipped with multiple MAs to assist in the data transmission between two single-antenna nodes. For the DF relaying system, our objective is to maximize the achievable rate at the destination by jointly optimizing the positions of the MAs in two stages for receiving signals from the source and transmitting signals to the destination, respectively. To drive essential insights, we first derive a closed-form upper bound on the maximum achievable rate of the DF relaying system. Then, a low-complexity algorithm based on projected gradient ascent (PGA) and alternating optimization (AO) is proposed to solve the antenna position optimization problem. For the AF relaying system, our objective is to maximize the achievable rate by jointly optimizing the two-stage MA positions as well as the AF beamforming matrix at the relay, which results in a more challenging optimization problem due to the intricate coupling variables. To tackle this challenge, we first reveal the hidden separability among the antenna position optimization in the two stages and the beamforming optimization. Based on such separability, we derive a closed-form upper bound on the maximum achievable rate of the AF relaying system and propose a low-complexity algorithm to obtain a high-quality suboptimal solution to the considered problem. Simulation results validate the efficacy of our theoretical analysis and demonstrate the superiority of the MA-enhanced relaying systems to the conventional relaying systems with fixed-position antennas (FPAs) and other benchmark schemes.