RIS Assisted Wireless Powered IoT Networks With Phase Shift Error and Transceiver Hardware Impairment

• Published in: IEEE transactions on communications Vol. 70; no. 7; pp. 4910 - 4924
• Main Authors: Chu, Zheng, Zhong, Jie, Xiao, Pei, Mi, De, Hao, Wanming, Tafazolli, Rahim, Feresidis, Alexandros P.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: complex circle manifold (CCM); Convexity; Downlink; element-wise block coordinate decent (EBCD); Energy transfer; Hardware; Impairment; Information transfer; Internet of Things; IoT networks; Kuhn-Tucker method; Optimization; Performance evaluation; Phase shift; phase shift error (PSE); Power plants; Reconfigurable intelligent surface (RIS); Scheduling; successive convex approximation (SCA); transceiver hardware impairment (THI); Transceivers; Uplink; Wireless communication; Wireless networks; Wireless sensor networks
• DOI: 10.1109/TCOMM.2022.3175833
• ISSN: 0090-6778

Considering a reconfigurable intelligent surface (RIS) aided wireless powered Internet of Things (WP IoT) network. To address the energy-limitation issue, IoT devices in such a network can be wirelessly powered by a power station (PS) first and then connect with an access point (AP) using their own harvested energy. The RIS helps enhance energy and information receptions in the downlink wireless energy transfer (WET) and uplink wireless information transfer (WIT), respectively. This work unveils the impact of phase shift error (PSE) and transceiver hardware impairment (THI) on the considered network. Our investigation starts with a scenario where only the impact of the PSE on system under study is considered, then moves toward a scenario with the compound effect of both PSE and THI. A maximization problem of the system sum throughput is formulated to evaluate the overall performance for these two scenarios, subject to the constraints of the adjustable RIS phase shifts, the statistical PSE and the transmission time scheduling. To handle the non-convexity of the formulated problem due to those coupled variables, we first adopt the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions to derive the optimal time scheduling in closed-form. Next, we recast the stochastic PSE into the deterministic counterpart for its tractability. Then, we adopt a successive convex approximation (SCA) to iteratively derive the optimal WIT's phase shifts, and element-wise block coordinate decent (EBCD) and complex circle manifold (CCM) methods to iteratively derive the optimal WET's phase shifts. Finally, we complete our solution approach for the scenario with both PSE and THI. Simulation results highlight the performance of the proposed scheme and the benefits induced by the RIS in comparison to benchmark schemes.