Multiuser Full-Duplex Two-Way Communications via Intelligent Reflecting Surface

Low-cost passive intelligent reflecting surfaces (IRSs) have recently been envisioned as a revolutionary technology capable of reconfiguring the wireless propagation environment through carefully tuning reflection elements. This paper proposes deploying an IRS to cover the dead zone of cellular mult...

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Veröffentlicht in:IEEE transactions on signal processing Jg. 69; S. 837 - 851
Hauptverfasser: Peng, Zhangjie, Zhang, Zhenkun, Pan, Cunhua, Li, Li, Swindlehurst, A. Lee
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Cochannel interference
Convergence
full-duplex
Intelligent Reflecting Surface (IRS)
Matrix algebra
Matrix methods
Max-Min Fairness (MMF)
Optimization
Precoding
Reconfigurable Intelligent Surface (RIS)
Reconfigurable intelligent surfaces
Reflectance
Reflection
Reflection coefficient
Signal processing algorithms
Simulation
Surface treatment
two-way communications
ISSN:1053-587X, 1941-0476
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Zusammenfassung:Low-cost passive intelligent reflecting surfaces (IRSs) have recently been envisioned as a revolutionary technology capable of reconfiguring the wireless propagation environment through carefully tuning reflection elements. This paper proposes deploying an IRS to cover the dead zone of cellular multiuser full-duplex (FD) two-way communication links while suppressing user-side self-interference (SI) and co-channel interference (CI). This approach, allowing the base station (BS) and all users to exchange information simultaneously, can potentially double the spectral efficiency. To ensure network fairness, we jointly optimize the precoding matrix of the BS and the reflection coefficients of the IRS to maximize the weighted minimum rate (WMR) of all users, subject to maximum transmit power and unit-modulus constraints. We reformulate this non-convex problem and decouple it into two subproblems. Then the optimization variables in the equivalent problem are alternately optimized by adopting the block coordinate descent (BCD) algorithm. In order to further reduce the computational complexity, we propose the minorization-maximization (MM) algorithm for optimizing the precoding matrix and the reflection coefficient vector by defining minorizing functions in the surrogate problems. Finally, simulation results confirm the convergence and efficiency of our proposed algorithm, and validate the advantages of introducing IRS to improve coverage in blind areas.
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2021.3049652