Performance enhancement of multi-IRS-assisted B5G/6G wireless communication systems

The demand for wireless communication is rapidly increasing due to smart devices, high-bandwidth applications, and emerging technologies such as the internet of things, Beyond Five-Generation (B5G), and Sixth-Generation (6 G) networks. Existing infrastructures face challenges, including limited spectrum and high energy consumption, while 5 G introduces additional complexity with mmWave, massive MIMO, and ultra-dense deployments. This study investigates intelligent, environment-aware technologies to enhance performance and sustainability in B5G/6 G networks. In particular, intelligent reflecting surfaces (IRSs) improve signal strength, coverage, spectral efficiency, and energy efficiency (EE) by passively reflecting signals and mitigating path loss and interference. Optimizing IRS configurations alongside base station (BS) beamforming is challenging due to the non-convex nature of the problem, especially in multi-IRS deployments. We propose a joint optimization of IRS phase shifts and BS beamforming under power and hardware constraints, solved via an alternating optimization algorithm. Simulation results show that at 100 m, single-IRS, 2-IRS, 4-IRS, and 6-IRS systems achieve 10, 15, 29, and 32 bps/Hz, respectively, while at 300 m, the 6-IRS system provides a sixfold improvement over a single IRS. At 50 dBm transmit power, the system reaches 63 bps/Hz. EE results indicate that at short distances (50 m), EE reaches 8 bits/Joule for 1-IRS, 16 bits/Joule for 2-IRS (100% improvement), 33 bits/Joule for 4-IRS (312.5% improvement), and 51 bits/Joule for 6-IRS (537.5% improvement). At longer distances ( 800 m), EE decreases due to path loss but remains substantially higher for multi-IRS deployments: 4 bits/Joule (1-IRS), 7 bits/Joule (2-IRS, 75% improvement), 12 bits/Joule (4-IRS, 200% improvement), and 13 bits/Joule (6-IRS, 225% improvement). Overall, these results demonstrate that multi-IRS systems significantly enhance signal coverage and long-range communication performance with low computational complexity, providing a scalable and practical solution for future wireless networks.