Channel estimation and user association for distributed intelligent reflecting surfaces assisted MISO communications
department or school: Applied Science, Faculty of
department or school: Engineering, School of (Okanagan)
data provider: DSpace
degree campus: UBCO
creator: Alwazani, Hibatallah Asem M.N
issued: 2021-04-22T19:27:42Z
issued: 2021
related degree: Master of Applied Science - MASc
degree grantor: University of British Columbia
description: Distributed intelligent reflecting surfaces (IRS)s deployed in wireless systems promise improved system performance, while spurring on diverse challenges such as channel estimation (CE), average signal-to-interference and noise (SINR) analysis, and IRS-user association. This is due to the passive nature of the reflecting elements and large multi-user system dimensions. In light of these challenges, we undertake the CE problem for the distributed IRSs-assisted multi-user MISO system. An optimal CE protocol requiring relatively low training overhead is developed using Bayesian techniques under the practical assumption that the base-station (BS)-IRSs channels are dominated by the line-of-sight (LoS) components. Simulation results corroborate the normalized MSE (NMSE) analysis and establish the advantage of the proposed protocol as compared to a benchmark scheme in terms of training overhead. In addition, we derive the average SINR for the distributed IRSs system with perfect channel state information (CSI) using a sub-optimal IRS reflecting configuration. After that, a successive refinement method is developed to find IRS-user association for the formulated max-min SINR problem which motivates user-fairness. Simulations validate the average SINR analysis while confirming the superiority of deploying a distributed IRSs scheme as well as an optimized IRS-user association as opposed to a centralized IRS deployment and random assignment.
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/77907
note: Channel Estimation and UserAssociation for Distributed IntelligentReflecting Surfaces Assisted MISOCommunicationsbyHibatallah Asem M.N AlwazaniB.Sc. Hons., Effat University, 2019A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF APPLIED SCIENCEinTHE COLLEGE OF GRADUATE STUDIES(Electrical Engineering)THE UNIVERSITY OF BRITISH COLUMBIA(Okanagan)March 2021© Hibatallah Asem M.N Alwazani, 2021The following individuals certify that they have read, and recommendto the College of Graduate Studies for acceptance, a thesis/dissertation en-titled:Channel Estimation and User Association for Distributed IntelligentReflecting Surfaces Assisted MISO Communicationssubmitted by Hibatallah Asem M.N Alwazani in partial fulfilment ofthe requirements of the degree of Master of Applied ScienceProf. Anas Chaaban, School of EngineeringSupervisorProf. Hossain Jahangir, School of EngineeringSupervisory Committee MemberProf. Loic Markley, School of EngineeringSupervisory Committee MemberProf. Abbas Milani, School of EngineeringUniversity ExamineriiAbstractDistributed intelligent reflecting surfaces (IRS)s deployed in wireless sys-tems promise improved system performance, while spurring on diverse chal-lenges such as channel estimation (CE), average signal-to-interference andnoise (SINR) analysis, and IRS-user association. This is due to the passivenature of the reflecting elements and large multi-user system dimensions. Inlight of these challenges, we undertake the CE problem for the distributedIRSs-assisted multi-user MISO system. An optimal CE protocol requiringrelatively low training overhead is developed using Bayesian techniques un-der the practical assumption that the base-station (BS)-IRSs channels aredominated by the line-of-sight (LoS) components. Simulation results cor-roborate the normalized MSE (NMSE) analysis and establish the advantageof the proposed protocol as compared to a benchmark scheme in terms oftraining overhead. In addition, we deri…
has type: Thesis/Dissertation
date issued: 2021-05
is shown at: 10.14288/1.0396917
language: eng
degree discipline: Electrical Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/77907