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UID:20260602T043325EDT-7219eroUEt@132.216.98.100
DTSTAMP:20260602T083325Z
DESCRIPTION: \n\nAbstract\n\nThe massive multiple-input multiple-output (mM
 IMO) technology brings great potential for supporting various emerging app
 lications by means of large antenna arrays\, high beamforming gain\, enhan
 ced spectral efficiency\, and coverage. Two-stage hybrid beamforming (HBF)
  has been proposed as a promising architecture for a reduced hardware cost
 /complexity in mMIMO systems. HBF employs a low number of radio-frequency 
 (RF) chains to interconnect analog RF beamformer and digital baseband (BB)
  precoder/combiner. In this thesis\, we propose novel HBF techniques for v
 arious mMIMO systems for half-duplex or full-duplex communications. We aim
  to address a set of versatile objectives\, such as user grouping\, beamfo
 rming optimization\, interference mitigation\, sum-rate maximization\, fai
 rness\, energy efficiency\, self-interference cancellation (SIC)\, and low
  channel estimation overhead.\n\n \n\nFirst\, we investigate the half-dupl
 ex mMIMO wireless communications. For the single-cell downlink transmissio
 n\, we initially develop a user-grouping algorithm for efficient clusterin
 g in the multi-user mMIMO (MU-mMIMO) systems. Afterwards\, the proposed RF
  beamformer design aims to jointly reduce hardware cost/complexity\, maxim
 ize the beamforming gain in the intended direction\, mitigate the inter-gr
 oup interference\, and lower the channel estimation overhead size. For thi
 s purpose\, we build the RF beamformer via slow time-varying channel state
  information (CSI)\, i.e.\, angular parameters. Then\, the BB-stage is con
 structed via the reduced-size effective instantaneous CSI. During the BB-s
 tage design\, in addition to equal power allocation\, we propose to apply 
 artificial intelligence (AI)-based solutions for sum-rate maximization and
  fairness objectives. According to the cloud radio access network (C-RAN)\
 , we also investigate cooperation strategies among the base stations in th
 e multi-cell downlink transmission\, where our primary objectives include 
 mitigating the effect of inter-cell interference and enhancing the sum-rat
 e capacity\, especially for cell-edge users. Later on\, we analyze the eff
 ect of low-resolution hardware components in HBF for the point-to-point mM
 IMO (P2P-mMIMO) systems.\n\n \n\nSecond\, we explore the full-duplex mMIMO
  wireless communications. Full-duplex technology further extends the impac
 ts of mMIMO systems by enabling simultaneous transmission/reception over t
 he same frequency to theoretically double the spectral efficiency of the c
 onventional half-duplex operation. However\, strong self-interference is p
 otentially the major limiting factor in the full-duplex operation. For thi
 s\, we introduce HBF techniques for full-duplex P2P-mMIMO and MU-mMIMO sys
 tems. Along with the above-mentioned objectives in the RF beamformer desig
 n\, we also aim to successfully cancel the strong self-interference by pro
 posing and developing both orthogonal and non-orthogonal beamforming schem
 es. Illustrative results indicate that the proposed full-duplex HBF techni
 ques achieve large SIC sufficient to double the capacity of their half-dup
 lex counterparts.\n
DTSTART:20221014T170000Z
DTEND:20221014T190000Z
LOCATION:\, Room 603\, McConnell Engineering Building\, CA\, QC\, Montreal\
 , H3A 0E9\, 3480 rue University
SUMMARY:PhD defence of Asil Koc - Hybrid Beamforming Techniques in Full-Dup
 lex/Half-Duplex Massive MIMO Wireless Communications
URL:https://www.mcgill.ca/ece/channels/event/phd-defence-asil-koc-hybrid-be
 amforming-techniques-full-duplexhalf-duplex-massive-mimo-wireless-342723
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