BEGIN:VCALENDAR VERSION:2.0 PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4// BEGIN:VEVENT UID:20260525T141920EDT-48187faMLJ@132.216.98.100 DTSTAMP:20260525T181920Z DESCRIPTION:Abstract\n\nThrough spatial diversity\, multiplexing or beamfor ming gain\, the multiple-input multiple-output (MIMO) techniques can offer significant performance improvements in terms of user capacity\, spectral efficiency\, and peak data rates. Recently\, the application of MIMO tech niques along with non-orthogonal multiple access (NOMA) has aroused great interest as an enabling technology to meet the exacting demands of fifth g eneration (5G) and beyond 5G (B5G) wireless networks. In effect\, by allow ing multiple users to access overlapping time and frequency resources in t he same spatial layer\, NOMA has the potential to provide higher system th roughput and solve the massive connectivity needed for future wireless net works. The primary objective of this thesis is to develop new approaches f or multi-user MIMO NOMA systems from the perspectives of spectral and ener gy efficiency.\n\nFirst\, the joint design of user clustering\, downlink b eamforming and power allocation is formulated as a mixed-integer non-linea r programming (MINLP) model for a MIMO NOMA system. In this problem the ai m is to minimize the total transmission power while satisfying quality-of- service (QoS) and power constraints. To tackle this challenging problem\, we reformulate it into a more tractable form and conceive two algorithms b ased on the branch-and-bound and penalty dual decomposition techniques for its solution. The performance of the proposed joint design algorithms for MIMO NOMA is validated by means of simulations over millimeter-wave (mmWa ve) channels. The results show the advantages of the proposed algorithms i n terms of total transmit power and spectral efficiency over competing mul tiple access schemes.\n\nThen\, we study the application of spatial user c lustering along with downlink beamforming for MIMO sparse code multiple ac cess (SCMA) in a cloud radio access network (C-RAN). A user clustering al gorithm based on a constrained K-means method is proposed to limit the num ber of users in each cluster. Subsequently\, two iterative algorithms for beamforming design are developed by minimizing the total transmission powe r under QoS and fronthaul capacity constraints. The performance of the pro posed user clustering and downlink beamforming approaches in MIMO SCMA sys tems is evaluated through simulations. The results provide useful insights into the advantages of the proposed schemes over benchmark approaches\, i n terms of transmit power and spectral efficiency.\n\nFinally\, we propose a novel SCMA decoder based on deep residual neural network (ResNet)\, whe rein the decoder is trained to predict the transmit codewords. In our appr oach\, batch normalization is utilized to enhance the stability and robust ness of the decoder\, while residual blocks are employed to tackle the pro blems with deep learning-based decoder such as accuracy saturation and van ishing gradients. The performance of the proposed ResNet decoder for SCMA is validated by means of simulations over AWGN and Rayleigh fading channel s. The results show that besides a much-reduced complexity\, the proposed decoder leads to improvements in term of bit error rate (BER) over competi ng deep neural network (DNN) based decoders.\n\n \n DTSTART:20230217T190000Z DTEND:20230217T210000Z LOCATION:\, Room 603\, McConnell Engineering Building\, CA\, QC\, Montreal\ , H3A 0E9\, 3480 rue University SUMMARY:PhD defence of Sara Norouzi - Non-Orthogonal Multiple Access for MI MO Wireless Communications URL:/ece/channels/event/phd-defence-sara-norouzi-non-o rthogonal-multiple-access-mimo-wireless-communications-346081 END:VEVENT END:VCALENDAR