Movable Antenna Communications With Electromagnetical Spatial Discrete Sampling

Electromagnetic information theory (EIT) has emerged as a pivotal research area in 6G communications, due to its potential in revealing the performance limits of wireless communication systems. However, the high-dimensional characteristic of continuous electromagnetic (EM) channels is always a significant challenge in effectively characterizing multiple-input multiple-output (MIMO) systems in complex space. To address this issue, this paper establishes a stochastic multipath channel model grounded in EIT, where the continuous EM channel is approximated by a set of spatially discrete sampling points. Furthermore, inspired by the recently developed concept of movable antennas, a tabu search algorithm is proposed to optimize the sampling point selection. This method effectively leverages the spatial degrees of freedom offered by a limited number of antennas, thereby maximizing the utilization of the available EM space.