Robust Resource Allocation for MISO Cognitive Radio Networks under Two Practical Non-Linear Energy Harvesting Models

Date

ORCID

Journal Title

Journal ISSN

Volume Title

Publisher

Institute of Electrical and Electronics Engineers Inc.

item.page.doi

Abstract

To achieve a good tradeoff between the consumed power and the harvested power, a robust resource optimization problem is studied in a multiple-input single-output cognitive radio network with simultaneous wireless information and power transfer under imperfect channel state information. Unlike most of the existing works that assume an ideal linear energy harvesting (EH) model, we assume two practical non-linear EH models. In order to solve the resulting challenging non-convex problem, we propose an algorithm based on successive convex approximation and prove that a rank-one solution is obtained in each iteration of the proposed algorithm. Our simulation results quantify the effect of the sensitivity threshold of the EH circuit on the harvested power. ©2018 IEEE

Description

Full text access from Treasures at UT Dallas is restricted to current UTD affiliates (use the provided Link to Article).

Keywords

Signal processing, Cognitive radio networks, Integrated circuits, Energy harvesting, Robust control, Heuristic algorithms, Array processors, Energy transfer, IIterative methods (Mathematics), Resource allocation

item.page.sponsorship

The research was supported in part by the Natural Science Foundation of China (61701214, 61261010 and 61661028), in part by the Graduate Student Innovation and Entrepreneurship Project of Jiangxi Province (CX2017196), in part by the Young Natural Science Foundation (20171BAB212002), in part by The Postdoctoral Science of Jiangxi Province (2017M610400, 2017KY04 and 2017RC17), in part by the key Project for Young Natural Science of Jiangxi Province (20152ACB21008), and in part by the Young Scientist of Jiangxi province (20142BCB2300). The work of N. Al-Dhahir was made possible by NPRP grant # 8-627-2-260 from the Qatar National Research Fund (a member of Qatar Foundation).

Rights

©2018 IEEE

Citation