An IRS-Enabled Phase Cooperative Framework for Sum Rate Maximization in B5G Networks

Abstract

Intelligent reflecting surfaces (IRSs) improves beyond fifth generation (B5G) systems performance in power- and cost-efficient ways. However, maintaining the performance of multiple IRSs-enabled networks without constraining available resources is challenging. In this paper, we propose a novel IRS-assisted phase cooperative framework to maximize the sum rate of the secondary phase cooperative system ( $\mathbf {SPC}_{\mathcal {S}ys}$ ) located in close proximity of the primary phase cooperative system ( $\mathbf {PPC}_{\mathcal {S}ys}$ ). We exploit transmit beamforming (BF) at base stations (BSs) and phase shift optimization at the IRS with effective phase cooperation between BSs. The maximization problem turns out to be NP-hard, so an alternating optimization is solved for the $\mathbf {PPC}_{\mathcal {S}ys}$ using an exhaustive search method, i.e., the branch-reduce-and-bound (BRB) algorithm, to obtain the optimal solution for active beamformers, and phase optimization is performed using the semidefinite relaxation (SDR) approach. Further, an active BF is carried out at the $\mathbf {SPC}_{\mathcal {S}ys}$ transmitter by utilizing optimal phase shifts of the $\mathbf {PPC}_{\mathcal {S}ys}$ . For the proposed framework, the performance of the BRB algorithm is compared with sub-optimal heuristic BF approaches, including transmit minimum-mean-square-error, zero-forcing BF, and maximum-ratio-transmission. The results support the benefits of deploying IRS in wireless networks to improve sum rate performance of $\mathbf {SPC}_{\mathcal {S}ys}$ through effective phase cooperation. The proposed framework significantly reduces the hardware cost of the system without constraining the resources of $\mathbf {PPC}_{\mathcal {S}ys}$ .