Pan, Yijin, Wang, Kezhi, Pan, Cunhua, Zhu, Huiling and Wang, Jiangzhou (2022) Sum-Rate Maximization for Intelligent Reflecting Surface Assisted Terahertz Communications. IEEE Transactions on Vehicular Technology, 71 (3). pp. 3320-3325. ISSN 0018-9545
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Sum_Rate_Maximization_for_Intelligent_Reflecting_Surface_Assisted_Terahertz_Communications.pdf - Accepted Version Download (909kB) | Preview |
Abstract
In this paper, an intelligent reflecting surface (IRS) is deployed to assist the terahertz (THz) communications. The sum-rate of user equipments (UEs) is maximized while guaranteeing the rate requirement of each UE. A block coordinate searching (BCS) algorithm is proposed to jointly optimize the IRS's coordinates, phase shifts, THz sub-bands allocation and power control. Specifically, the relaxation with penalties based (RPB) algorithm is developed to guarantee the feasibility of obtained IRS's coordinates and the monotonicity of objective value. In addition, to optimize the IRS's phase shifts, the sub-gradient descent (SGD) algorithm is proposed, where the IRS phase shifts are formulated as closed-form expressions with introduced pricing factors. Simulation results show that the proposed scheme can significantly enhance system performance.
| Item Type: | Article |
|---|---|
| Additional Information: | Funding information: This work was supported in part by the National Natural Science Foundation of China under Grants 62001107, No. 61971129, No. 61960206005, No. 61871128, Basic Research Project of Jiangsu Provincial Department of Science and Technology under Grant No. BK20190339, No. Bk20192002. |
| Uncontrolled Keywords: | Bandwidth, Propagation losses, Wireless communication, Scattering, Resource management, Reflection, Intelligent reflecting surface (IRS), Terahertz (THz) communication, Reconfigurable intelligent surface (RIS) |
| Subjects: | G400 Computer Science G700 Artificial Intelligence H600 Electronic and Electrical Engineering |
| Department: | Faculties > Engineering and Environment > Computer and Information Sciences |
| Depositing User: | Rachel Branson |
| Date Deposited: | 24 Jan 2022 12:16 |
| Last Modified: | 08 Apr 2022 13:45 |
| URI: | http://nrl.northumbria.ac.uk/id/eprint/48228 |
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