Residential College | false |
Status | 已發表Published |
Energy Efficiency Maximization for IRS-Assisted Uplink Systems: Joint Resource Allocation and Beamforming Design | |
Forouzanmehr, Maliheh1; Akhlaghi, Soroush1; Khalili, Ata1; Wu, Qingqing2,3 | |
2021-12-01 | |
Source Publication | IEEE Communications Letters |
ISSN | 1089-7798 |
Volume | 25Issue:12Pages:3932-3936 |
Abstract | This letter investigates the design of resource allocation to maximize the energy efficiency (EE) in a multiuser multiple-input multiple-output (MIMO) intelligent reflecting surface (IRS)-assisted uplink network. The design is formulated as a mixed-integer non-convex optimization problem which jointly optimizes the antenna selection (AS) and power allocation at user sides and the beamforming matrices adopted at the BS and IRS. To facilitate the design of a suboptimal solution, we first decompose the original problem into two sub-problems via the alternative optimization (AO) method. In particular, for the first sub-problem, we propose an iterative algorithm based on the majorization minimization (MM) approach to make the numerator of the fractional problem into a concave form and then we employed the Dinkelbach algorithm. For the second sub-problem, we adopt the inner approximation (IA) method to optimize the beamforming matrices at the BS and IRS. Simulation results demonstrate the superiority of the proposed method over benchmark schemes for the case of a single antenna case and also provide considerable performance gains due to the use of an antenna selection strategy. |
Keyword | And Antenna Selection (As) Energy Efficiency (Ee) Intelligent Reflecting Surface (Irs) |
DOI | 10.1109/LCOMM.2021.3115812 |
URL | View the original |
Indexed By | SCIE |
Language | 英語English |
WOS Research Area | Telecommunications |
WOS Subject | Telecommunications |
WOS ID | WOS:000728924700040 |
Scopus ID | 2-s2.0-85119618450 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) |
Corresponding Author | Akhlaghi, Soroush |
Affiliation | 1.Electrical Engineering Department, Shahed University, Tehran, 3319118651, Iran 2.State Key Laboratory of Internet of Things for Smart City, University of Macau, Macao 3.National Mobile Communications Research Laboratory, Southeast University, Nanjing, 210096, China |
Recommended Citation GB/T 7714 | Forouzanmehr, Maliheh,Akhlaghi, Soroush,Khalili, Ata,et al. Energy Efficiency Maximization for IRS-Assisted Uplink Systems: Joint Resource Allocation and Beamforming Design[J]. IEEE Communications Letters, 2021, 25(12), 3932-3936. |
APA | Forouzanmehr, Maliheh., Akhlaghi, Soroush., Khalili, Ata., & Wu, Qingqing (2021). Energy Efficiency Maximization for IRS-Assisted Uplink Systems: Joint Resource Allocation and Beamforming Design. IEEE Communications Letters, 25(12), 3932-3936. |
MLA | Forouzanmehr, Maliheh,et al."Energy Efficiency Maximization for IRS-Assisted Uplink Systems: Joint Resource Allocation and Beamforming Design".IEEE Communications Letters 25.12(2021):3932-3936. |
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