Exploiting Benefits of IRS in Wireless Powered NOMA Networks

We consider an intelligent reflecting surface (IRS) wireless-powered NOMA Internet-of-Things (IoT) network, where multiple NOMA IoT devices can communicate with access point (AP) with the aid of IRS. Specifically, IoT devices can harvest energy from a nearby appropriative power station (PS) during the wireless energy transfer (WET) phase through the direct links as well as the reflecting links from IRS. Then, the harvested energy can achieve the wireless information transfer (WIT) during the uplink between IoT devices and AP by adopting NOMA protocol. A novel resource allocation scheme is proposed to maximized the sum throughput of the considered system by jointly optimizing the time allocation factor and phase shift matrices of WET and WIT. The optimization problem is non-convex due to multiple variables. We first transfer this problem into convex function by assuming one of the phase shift matrices fixed, and solve the transferred problem by obtaining closed-form solution. Then, the elements collaborative approximate (ECA) and the manifold space gradient descent (MSGD) algorithms are designed to optimize the phase shift matrix. ECA is iteratively optimizing one element and MSGD is focus on the derivation of a gradient descent over the manifold space. Numerical results indicate the sum throughput enhancement by IRS compared with no IRS, and highlight the advantages of IRS.