Pan, Cunhua, Ren, Hong, Wang, Kezhi, Elkashlan, Maged, Nallanathan, Arumugam, Wang, Jiangzhou, Hanzo, Lajos (2020) Intelligent Reflecting Surface Aided MIMO Broadcasting for Simultaneous Wireless Information and Power Transfer. IEEE Journal on Selected Areas in Communications, . ISSN 0733-8716. (doi:10.1109/JSAC.2020.3000802) (KAR id:82041)
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Official URL: https://doi.org/10.1109/JSAC.2020.3000802 |
Abstract
An intelligent reflecting surface (IRS) is invoked for enhancing the energy harvesting performance of a simultaneous wireless information and power transfer (SWIPT) aided system. Specifically, an IRS-assisted SWIPT system is considered, where a multi-antenna aided base station (BS) communicates with several multi-antenna assisted information receivers (IRs), while guaranteeing the energy harvesting requirement of the energy receivers (ERs). To maximize the weighted sum rate (WSR) of IRs, the transmit precoding (TPC) matrices of the BS and passive phase shift matrix of the IRS should be jointly optimized. To tackle this challenging optimization problem, we first adopt the classic block coordinate descent (BCD) algorithm for decoupling the original optimization problem into several subproblems and alternatively optimize the TPC matrices and the phase shift matrix. For each subproblem, we provide a low-complexity iterative algorithm, which is guaranteed to converge to the Karush-Kuhn-Tucker (KKT) point of each subproblem. The BCD algorithm is rigorously proved to converge to the KKT point of the original problem. We also conceive a feasibility checking method to study its feasibility. Our extensive simulation results confirm that employing IRSs in SWIPT beneficially enhances the system performance and the proposed BCD algorithm converges rapidly, which is appealing for practical applications.
Item Type: | Article |
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DOI/Identification number: | 10.1109/JSAC.2020.3000802 |
Uncontrolled keywords: | Intelligent Reflecting Surface (IRS), Large Intelligent Surface (LIS), SWIPT, Energy Harvesting, MIMO |
Subjects: | T Technology |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | Jiangzhou Wang |
Date Deposited: | 08 Jul 2020 15:00 UTC |
Last Modified: | 05 Nov 2024 12:48 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/82041 (The current URI for this page, for reference purposes) |
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