Intelligent Reflecting Surfaces for Sum-Rate Maximization in Cognitive Radio Enabled Wireless Powered Communication Network

In this paper, we study a cognitive radio (CR)-enabled wireless powered communication network (WPCN) with an intelligent reflecting surface (IRS). A (CWPCN) consisting of one secondary network, in which hybrid access point broadcasts energy to multiple users on downlink and receives information signals uplink, shares the same spectrum existing primary network. consider underlay CWPCN is regulated by given interference temperature constraint (ITC) such that kept no greater than predefined threshold. To enhance performance CWPCN, IRS-assisted passive reflection elements are configured reflect any desired phase/direction. Our main goal maximize sum throughput while managing constraint. For this, jointly optimize uplink phase shift matrices IRS optimal time slots for transfer (WET) uplink. finding solution, formulated optimization problem non-convex, complex, intractable. propose alternating (AO)-based solution successive convex approximation (SCA) technique. We show through simulation results proposed provides significant enhancement over conventional CWPCN.