Frobenius Norm-Based IRS Selection Algorithm in Parallel Multi-IRS-assisted Spatial Modulation

Intelligent reflecting surface (IRS)-assisted multiple input multiple output (MIMO) has recently been considered as a prospective candidate for the future 6G wireless systems. This is mainly due to its ability to significantly improve the energy efficiency and network coverage by intelligently adapting the wireless propagation environment. In this paper, a parallel multi-IRS-aided spatial modulation (SM) scheme with Frobenius norm-based IRS selection is proposed to improve the error performance by selecting a subset of IRSs with the largest norm values out of parallel multiple IRSs for the transmission between the source and destination. Extensive computer simulations have been conducted to evaluate the bit error rate (BER) performance of the proposed scheme, and the performance of the parallel multi-IRS-assisted SM and conventional SM schemes is also evaluated for the sake of fair comparison. The results show that the proposed scheme has remarkable advantages, such as power-efficiency, over its counterparts. It is also shown that the BER performance can be further improved as the number of selected IRSs and their elements are increased.