Ministère de l'Enseignement Supérieur et RS Ministère des Technologies de la Communication et de l'Economie Numérique
Université de Carthage
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Doctorate thesis defense of Halima BERGAOUI
Doctorate thesis defense on December 16th 2021 .
Entitled :Modeling and Optimization of Switching Techniques in a Massive MIMO Context for 5G Wireless Networks
Presented by :Halima BERGAOUI
In this work, we propose two resources adaptation techniques destined to enhance the Bit Error Rate (BER) performance for a fixed data rate in the fifth generation of mobile communications. The first technique that we suggest is the embedded switching technique. It consists of switching between spatial multiplexing and diversity for small groups of data streams according to the instantaneous channel state, then combining them to obtain an adaptable and scalable diversity/multiplexing trade-off. We study the feedback optimization of this technique and its usability in a multi-user context. Moreover, we investigate its performance in a realistic environment. In this context, we offer a new Adaptive Pilot Pattern (APP) that ensures a channel estimation within the coherence time and bandwidth along with an APP-based channel estimation. The second adaptation technique is the optimized Spatial Multiplexing-Adaptive Beamforming (SMBF) modes adaptation. In this context, we propose the optimized SMBF technique that aims to enhance the BER performance of linear spatial multiplexing decoders while having a low complexity. Then, we suggest a Precoder Modes Adaptation (PMA) technique that aims to switch between the optimized SMBF modes according to the instantaneous channel state. Finally, we propose a non-uniform data mapping algorithm that ensures an optimal BER performance of the PMA technique.
mobile communication, 5G, massive MIMO, adaptation, BER, channel estimation, beamforming.