Intelligent Joint Beamforming Optimization for IRS-Enhanced MISO Communication Systems

Intelligent Reflecting Surfaces (IRS) have emerged as a promising paradigm to enhance spectral and energy efficiency in wireless communications. This paper addresses the joint active and passive beamforming design for an IRS-Assisted singleuser multiple-input single-output (MISO) system, aiming to maximize spectral efficiency through coordinated transmission design at both the access point (AP) and the IRS. The original non-convex and coupled problem is reformulated as a mixed-integer quadratically constrained quadratic program (MIQCQP). To tackle the inherent non-convexity, we propose a convexification framework based on optimal diagonal perturbations derived from the semidefinite programming (SDP) relaxation of the primal problem. Extensive simulations demonstrate that the proposed method achieves significant reduction in computation time compared to direct global solvers, with the efficiency gain increasing with the number of IRS elements. Moreover, the optimized beamforming configuration significantly improves the signal-To-noise ratio (SNR) and extends coverage compared to systems without IRS. These results highlight the potential of IRS technology as a key enabler for next-generation wireless networks.