Throughput Maximization for Active Intelligent Reflecting Surface-Aided Wireless Powered Communications

This letter considers an active intelligent reflecting surface (IRS)-aided wireless powered communication network (WPCN), where devices first harvest energy and then transmit information to a hybrid access point (HAP). Different from the existing works on passive IRS-aided WPCNs, this is work that introduces IRS in WPCNs. To guarantee fairness, problem formulated as amplifying power-limited weighted sum throughput (WST) maximization problem, which solved by successive convex approximation technique fractional programming alternatively. balance performance complexity tradeoff, three beamforming setups are considered at IRS, namely user-adaptive beamforming, uplink-adaptive static beamforming. Numerical results demonstrate significant superiority of employing WPCNs benefits dynamic Specifically, it found compared not only improves WST greatly, but also more energy-efficient can significantly extend transmission coverage. Moreover, different symmetric deployment strategy preferable deploy near devices.