Analysis and Optimization of Massive MIMO Systems via Random Matrix Theory Approaches Ikram Boukhedimi, Ph.D., Electrical and Computer Engineering Jun 24, 12:00 - 14:00 B1 L3 R3119 Random Matrix Theory wireless communication systems Ultra-massive MIMO systems 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.
Non-Orthogonal Multiple Access for 5G and Beyond Prof. Daniel Costa , Federal University of Ceará May 26, 14:00 - 15:00 B1 L2 R2202 Federal University of Ceará 5th generation cellular Non-orthogonal multiple access (NOMA) has recently emerged not only as a new design of multiple access techniques in cellular networks, but also as a general principle of network architecture for applications beyond cellular systems. This talk will present and discuss the fundamentals of NOMA, and examine how it can be combined with other emerging communication technologies. Some new research trends and challenges will also be discussed.
Applications of random matrix theory for wireless communication and big data processing Abla Kammoun, Senior Research Scientist, Electrical and Computer Engineering Apr 25, 12:00 - 13:00 B9 L2 H1 Since the pioneer works of Telatar, random matrix theory has found a variety of applications in engineering disciplines that, to name a few, include wireless communication and signal processing. Its scope is now going far beyond the field of mathematics, being recognized as an indispensable tool for advanced research in engineering disciplines as can be evidenced by the dramatic increase in related publications. Recently, random matrix theory has found its way into the field of big data processing, allowing accurate characterization of the performance of many algorithms met in the field of machine learning.
Network Engineering as Distinct Academic Discipline Beyond the TEE Movement Professor Tarek Al-bawab, Jackson State University Dec 19, 14:00 - 16:00 B1 B3 R3119 Network Engineering communications Abstract: Network Engineering as Distinct Academic Discipline Beyond the TEE Movement Network Engineering is now recognized as distinct education discipline in the USA and in many other countries. This development came about with ABET’s1 2015 (current) Criteria for Electrical, Computer, Communications, Telecommunication(s) and Similarly Named Engineering Programs. Few academic programs focused on this area of study in the past. More programs are expected to emerge now with progress in this field and with ABET recognition of it. Such programs have a great potential to prepare a new generation
