Ultra-massive MIMO systems

Analysis and Optimization of Massive MIMO Systems via Random Matrix Theory Approaches

-

B1 L3 R3119

Massive multiple-input multiple-output (MIMO) is a key enabling technology to achieve the required spectral and energy efficiency of the next generation of wireless networks. By endowing the base station (BS) with hundreds of antennas and relying on spatial multiplexing, massive MIMO allows impressive advantages in many fronts. To reduce this promising technology to reality, thorough performance analysis has to be conducted. Along this line, this work is focused on the convenient high-dimensionality of massive MIMO’s corresponding model. Indeed, the large number of antennas allows us to harness asymptotic results from Random Matrix Theory to provide accurate approximations of the main performance metrics. The derivations yield simple closed-form expressions that can be easily interpreted and manipulated in contrast to their alternative random equivalents. Accordingly, in this dissertation, we investigate massive MIMO in different contexts.

Ikram Boukhedimi

Ikram Boukhedimi was born in Blida, Algeria. She received an Electrical Engineering degree from the Ecole Polytechnique d'Alger, Algeria, in 2013 and an M.S. in Mathematics, Control and Electrical Engineering from Universite de Poitiers, France in 2014. and she earned a Ph.D. in Electrical Engineering at King Abdullah University of Science and Technology in June 2019, Saudi Arabia in Professor Mohamed Slim Alouini’s Communication Theory Lab in Electrical Engineering research group. Her research interests include random matrix theory approaches applied to wireless communication systems

Alice Faisal

Visiting Student (former), Electrical and Computer Engineering
Visiting Student at King Abdullah University of Science and Technology (KAUST), chair of IEEE women in engineering affinity group at Effat University student branch.