Resource allocation in the next generation of wireless networks: vehicular and energy harvesting systems

Abstract

The fifth generation (5G) of wireless communication networks is expected to enable advanced network services that usually come with stringent quality-of-service (QoS) requirements, such as high reliability, ultra-high speed, low latency, and user fairness. Given such sophisticated QoS constraints and the ever-increasing number of connected devices in 5G networks, the need for an optimal management of network resources is indispensable. In this thesis, we mainly focus on designing novel resource allocation algorithms considering the intrinsic characteristics of vehicular networks, i.e. one of the most advanced 5G-enabled networks. On the other hand, with the large-scale deployment of future wireless networks, energy issues, such as the increase in CO2 and electromagnetic emissions incurred from the operation of battery-powered devices, are emerging and causing enormous concerns for network planners. Consequently, energy efficiency and sustainability have quickly become crucial criteria for 5G systems. To achieve these criteria, energy harvesting techniques that allow wireless devices to harness energy from the ambient environment have been proposed. The integration of this concept into the 5G-enabled systems is considered as a key-enabler for green and sustainable future networks. The advent of energy harvesting systems is set to introduce energy constraints in the network resource management, creating new challenges in designing resource allocation algorithms. Therefore, addressing these new challenges in energy harvesting networks is also a main topic in this dissertation. In this regard, chapters 2 and 3 provides advanced energy harvesting frameworks that tackle energy concerns in future wireless networks, while chapters 4, 5, and 6 focus on designing new access strategies for vehicular networks that enhance the network performance in terms of latency and reliability. Numerical results are provided to verify the efficiency and advantages of our proposed schemes over other benchmark schemes.

Date	2 Feb 2022
Original language	American English
Awarding Institution	École de technologie supérieure
Supervisor	Georges Kaddoum (Supervisor)