Multi-IRS deployment strategies for joint EE–SE optimization in B5G/6G wireless networks

The rapid growth of mobile technologies has increased the demand for high-speed, reliable, and energy-efficient wireless communication systems. Intelligent Reflecting Surfaces (IRSs) provide a promising solution for B5G and 6G networks by improving coverage, spectral efficiency (SE), and energy efficiency (EE). This study investigates a downlink multi-user MISO system assisted by single and multiple IRS deployments while considering path loss, Rayleigh fading, and user distance variations. A joint optimization problem is formulated to maximize EE and SE through base station beamforming and IRS phase shift design under transmit power constraints. To solve the problem efficiently, a low-complexity alternating optimization (AO) algorithm is proposed to iteratively update the beamforming vectors and IRS configurations. Simulation results show that distributed multi-IRS deployments significantly outperform single-IRS and non-IRS systems. In particular, a six-IRS configuration achieves EE of 55 Mbits/J, SE up to 65 bps/Hz, and a sum rate of 65 Mbps. The AO algorithm also demonstrates fast convergence, typically requiring 12–15 iterations for a single IRS and 14–18 iterations for six IRSs. These results demonstrate that scalable multi-IRS-assisted MISO systems provide an energy-efficient and high-capacity solution for next-generation 6G networks while maintaining manageable computational complexity.