A Class of Low-Complexity Transmit Antenna Selection Schemes for Spatial Modulation

Euclidean distance optimized antenna selection (EDAS) has emerged as a promising technique within spatial modulation (SM) systems, renowned for its ability to mitigate the severe impact of channel fading through increased diversity gain. However, the conventional EDAS approach may introduce excessive complexity, particularly in large-scale antenna configurations, which poses significant challenges for direct application in future wireless communication systems. To address this issue, we propose a novel transmit antenna selection scheme that integrates the priority-based genetic algorithm (PGA) into EDAS, effectively generating a near-optimal antenna subset with reduced complexity. Our simulation results demonstrate that the proposed scheme not only maintains the single radio-frequency (RF) chain characteristics of SM-TAS but also approaches the optimal bit error rate (BER) performance while lowering computational complexity.