Novel Beamforming Design for IRS-Assisted Cell-Free Massive MIMO Systems

Intelligent reflecting surface (IRS) assisted cell-free (CF) massive multiple-input multiple-output (mMIMO) offers substantial potential for enhancing spectral efficiency, energy efficiency, and coverage areas. In this letter, we introduce a novel approach aimed at maximizing the sum-rate in the downlink of IRS-assisted CF mMIMO systems. Our approach employs an alternating optimization strategy to design both active and passive beamforming techniques. Specifically, for active beamforming, we adopt zero-forcing beamforming to effectively eliminate inter-user interference, and we employ geometric programming to obtain optimal power allocation coefficients. For passive beamforming, we present innovative solutions through the alternating direction method of multipliers (ADMM) algorithm and the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. Additionally, we rigorously analyze the computational complexity of our proposed algorithms, providing a comparative assessment against existing approaches. Our simulations substantiate the superior sum-rate performance achieved by our algorithms, underscoring their efficacy in IRS-assisted CF mMIMO systems.