Position Optimization for Two-layer Movable Antenna Systems

TL;DR

A new two-layer MA array (TL-MA), where the positions of MAs are jointly determined by the large-scale movement of multiple subarrays and the small-scale fine-tuning of per-subarray MAs is proposed, and an optimization problem is formulated to maximize the sum-rate of the TL-MA-aided communication system.

Abstract

Movable antenna (MA) is a promising technology for improving the performance of wireless communication systems by providing new degrees-of-freedom (DoFs) in antenna position optimization. However, existing works on MA systems have mostly considered element-wise single-layer MA (SL-MA) arrays, where all the MAs move within the given movable region, hence inevitably incurring high control complexity and hardware cost in practice. To address this issue, we propose in this letter a new two-layer MA array (TL-MA), where the positions of MAs are jointly determined by the large-scale movement of multiple subarrays and the small-scale fine-tuning of per-subarray MAs. In particular, an optimization problem is formulated to maximize the sum-rate of the TL-MA-aided communication system by jointly optimizing the subarray-positions, per-subarray (relative) MA positions, and receive beamforming. To solve this non-convex problem, we propose an alternating optimization (AO)-based particle swarm optimization (PSO) algorithm, which alternately optimizes the positions of subarrays and per-subarray MAs, given the optimal receive beamforming. Numerical results verify that the proposed TL-MA significantly reduces the sum-displacement of MA motors (i.e., the total moving distances of all motors) of element-wise SL-MA, while achieving comparable rate performance.

Figures (4)

• Figure 1: Illustration of the proposed TL-MA and its comparison with conventional SL-MA.
• Figure 2: Sum-rate vs. number of subarrays $M_{\rm S}$.
• Figure 3: Sum-displacement vs. number of subarrays $M_{\rm S}$.
• Figure 4: Sum-rate vs. MA-array length $L$ (100 p: $I_{\rm P}=100$).