Cooperative Throughput Maximization in a Multi-Cluster WPCN

This paper investigates a multi-cluster Wireless Powered Communication Network (WPCN) where user clusters cooperate with a Cluster Head (CH) and a Hybrid Access Point (HAP). Employing beamforming, the HAP supplies energy in the downlink phase, while users transmit signals to the HAP and CHs in the uplink phase. We optimize the Energy Beamforming (EB) matrix, user transmit covariance matrices, and time slot allocation to enhance both max-min and sum network throughput. To tackle the non-convexity of the optimization problems, we decompose them into two subproblems and reformulate each as convex Second Order Cone Programming (SOCP) and Quadratic Constraint Quadratic Programming (QCQP) for the max-min and sum throughput problems, respectively. Notably, we account for imperfections in Channel State Information (CSI) and non-linear Energy Harvesting (EH) circuits. Additionally, we incorporate the active Intelligent Reflecting Surfaces (IRS) as a key component in our proposed method. Numerical examples illustrate the significant impact of these contributions across various scenarios.