Reference : Intelligent Reflecting Surface-assisted MU-MISOSystems with Imperfect Hardware: Chann...
Scientific journals : Article
Engineering, computing & technology : Computer science
Computational Sciences
http://hdl.handle.net/10993/53078
Intelligent Reflecting Surface-assisted MU-MISOSystems with Imperfect Hardware: ChannelEstimation and Beamforming Design
English
Papazafeiropoulos, Anastasios []
Pan, Cunhua []
Kourtessis, Pandelis []
Chatzinotas, Symeon mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Senior, John M. []
Mar-2022
IEEE Transactions on Wireless Communications
Institute of Electrical and Electronics Engineers
21
3
2077 - 2092
Yes
International
1536-1276
1558-2248
New York
United States - New York
[en] Intelligent reflecting surface (IRS), consisting of low-cost passive elements, is a promising technology for improvingthe spectral and energy efficiency of the fifth-generation (5G)and beyond networks. It is also noteworthy that an IRS canshape the reflected signal propagation. Most works in IRS-assisted systems have ignored the impact of the inevitable residualhardware impairments (HWIs) at both the transceiver hardwareand the IRS while any relevant works have addressed only simplescenarios, e.g., with single-antenna network nodes and/or withouttaking the randomness of phase noise at the IRS into account.In this work, we aim at filling up this gap by considering ageneral IRS-assisted multi-user (MU) multiple-input single-output(MISO) system with imperfect channel state information (CSI)and correlated Rayleigh fading. In parallel, we present a generalcomputationally efficient methodology for IRS reflect beamforming(RB) optimization. Specifically, we introduce an advantageouschannel estimation (CE) method for such systems accounting forthe HWIs. Moreover, we derive the uplink achievable spectralefficiency (SE) with maximal-ratio combining (MRC) receiver,displaying three significant advantages being: 1) its closed-formexpression, 2) its dependence only on large-scale statistics, and3) its low training overhead. Notably, by exploiting the first twobenefits, we achieve to perform optimization with respect to thethat can take place only at every several coherence intervals,and thus, reduces significantly the computational cost comparedto other methods which require frequent phase optimization.Among the insightful observations, we highlight that uncorrelatedRayleigh fading does not allow optimization of the SE, whichmakes the application of an IRS ineffective. Also, in the case thatthe phase drifts, describing the distortion of the phases in theRBM, are uniformly distributed, the presence of an IRS providesno advantage. The analytical results outperform previous worksand are verified by Monte-Carlo (MC) simulations.
http://hdl.handle.net/10993/53078
10.1109/TWC.2021.3109391
https://ieeexplore.ieee.org/document/9534477

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
Intelligent Reflecting Surface-assisted MU-MISO Systems with Imperfect Hardware Channel Estimation and Beamforming Design.pdfPublisher postprint1.87 MBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.