Movable Antenna Enhanced MIMO Communications with Spatial Modulation
Kaihe Wang, Ran Yang, Lipeng Zhu, Rongyan Xi, Yue Xiu, Zhongpei Zhang
TL;DR
This paper tackles BER minimization in movable-antenna (MA) enabled SM-MIMO by jointly optimizing transmit beamforming and antenna positions under the maximum minimum distance (MMD) criterion. It develops an alternating optimization (AO) framework, where transmit beamforming is updated via successive convex approximation (SCA) and antenna positions are refined through block-coordinate descent with concave surrogates, all under power, movement, and spacing constraints. The proposed algorithm converges rapidly (about five iterations) and achieves substantial BER improvements over fixed-position SM-MIMO and greedy antenna schemes, illustrating the benefit of dynamic MA placement in exploiting spatial diversity. The work demonstrates that movable antennas can enhance SM-MIMO performance without increasing RF-chain count, with potential implications for ultra-massive MIMO and robust wireless links in challenging channels.
Abstract
Movable antenna (MA) has demonstrated great potential in enhancing wireless communication performance. In this paper, we investigate an MA-enabled multiple-input multiple-output (MIMO) communication system with spatial modulation (SM), which improves communication performance by utilizing flexible MA placement while reducing the cost of RF chains. To this end, we propose a joint transceiver design framework aimed at minimizing the bit error rate (BER) based on the maximum minimum distance (MMD) criterion. To address the intractable problem, we develop an efficient iterative algorithm based on alternating optimization (AO) and successive convex approximation (SCA) techniques. Simulation results demonstrate that the proposed algorithm achieves rapid convergence performance and significantly outperforms the existing benchmark schemes.