Joint Antenna Selection and Intelligent Reflecting Surface Aided MISO Downlink Networks

Intelligent Reflecting Surface (IRS) has been recognized as one of the effective ways to enhance the system performance of multiple input single output (MISO) downlink communication system. In order to reduce energy consumption and further improve system performance in the entire MISO system, we incorporate the transmitter antenna selection (AS) technology into the IRS-aided MISO communication system. We aim to maximize the user instantaneous receiver signal-to-noise ratio (SNR) by jointly optimizing antenna subset, transmit beamforming of the access point (AP) and passive phase-shift matrix of the IRS. We propose to solve the problem using a novel discrete cuckoo algorithm combined with optimization theory (NDCOT). NDCOT consists of AS and optimization steps. In AS steps, a novel discrete cuckoo algorithm is exploited to reduce the complexity of AS. In the optimization step, the semidefinite relaxation (SDR) algorithm is employed to obtain the optimal transmit beamforming vector at the transmitter and phase matrix at the IRS. The simulation results validate the effectiveness of AS in reducing energy consumption and improving the performance of the IRS-aided MISO communication system.