Exploiting Amplitude Control in Intelligent Reflecting Surface Aided Wireless Communication With Imperfect CSI

Intelligent reflecting surface (IRS) is a promising new paradigm to achieve high spectral and energy efficiency for future wireless networks by reconfiguring the wireless signal propagation via passive reflection. To reap the promising gains of IRS, channel state information (CSI) is essential, wher...

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Vydáno v:IEEE transactions on communications Ročník 69; číslo 6; s. 4216 - 4231
Hlavní autoři: Zhao, Ming-Min, Wu, Qingqing, Zhao, Min-Jian, Zhang, Rui
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.06.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Amplitudes
Channel estimation
Coefficients
Data transmission
imperfect CSI
Intelligent reflecting surface
Minimization
MISO communication
Optimization
Performance gain
Phase shift
phase-shift control
rate maximization
Reconfigurable intelligent surfaces
reflection amplitude control
Signal reflection
Training
Transmission rate (communications)
Upper bounds
Wireless communications
Wireless networks
ISSN:0090-6778, 1558-0857
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Shrnutí:Intelligent reflecting surface (IRS) is a promising new paradigm to achieve high spectral and energy efficiency for future wireless networks by reconfiguring the wireless signal propagation via passive reflection. To reap the promising gains of IRS, channel state information (CSI) is essential, whereas channel estimation errors are inevitable in practice due to limited channel training resources. In this paper, in order to optimize the performance of IRS-aided multiuser communications with imperfect CSI, we propose to jointly design the active transmit precoding at the access point (AP) and passive reflection coefficients of the IRS, each consisting of not only the conventional phase shift and also the newly exploited amplitude variation. First, the achievable rate of each user is derived assuming a practical IRS channel estimation method, which shows that the interference due to CSI errors is intricately related to the AP transmit precoders, the channel training power and the IRS reflection coefficients during both channel training and data transmission. Next, for the single-user case, by combining the benefits of the penalty method, Dinkelbach method and block successive upper-bound minimization (BSUM) method, a new penalized Dinkelbach-BSUM algorithm is proposed to optimize the IRS reflection coefficients for maximizing the achievable data transmission rate subjected to CSI errors; while for the multiuser case, a new penalty dual decomposition (PDD)-based algorithm is proposed to maximize the users' weighted sum-rate. Finally, simulation results are presented to validate the effectiveness of our proposed algorithms as compared to benchmark schemes. In particular, useful insights are drawn to characterize the effect of IRS reflection amplitude control (with/without the conventional phase-shift control) on the system performance under imperfect CSI.
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ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2021.3064959