On November 26, 2017, Lokman Sboui successfully defended his Ph.D. thesis on "Towards Reliable, Scalable, and Energy Efficient Cognitive Radio Systems" under the supervision of Prof. Mohamed-Slim Alouini.
We congratulate Dr. Sboui for his achievement! Everyone at CTL wishes him all the best for the future.
Committee Chairperson: Prof. Mohamed-Slim Alouini.
Committee Members:
- Prof. Georgios Giannakis (University of Minnesota)
- Prof. Ahmed Kamal Sultan (KAUST)
- Prof. Basem Shihada (KAUST)
- Prof. Tareq Al-Naffouri (KAUST)
- Prof. Zouheir Rezki (University of Idaho).
Thesis Abstract:
The current global data traffic is increasing exponentially. For instance, the global mobile data traffic is expected to grow seven folds between 2016 and 2021, which will cause scarcity in terms of the frequency spectrum. As a response, telecommunication researchers and industrials are working to define a suitable framework, named the 5G, to handle the expected colossal data exchange in the future. One of the concepts aiming to avoid the spectrum shortage is the cognitive radio (CR) in which unlicensed users are introduced in existing networks and are expected to share the spectrum of existent users without harming their Quality of Service (QoS). In this thesis, we present three main directions in which we aim to enhance the CR performances. The first direction is reliability. We study the achievable rate of a multiple input multiple output (MIMO) relay-assisted CR under two scenarios; an unmanned aerial vehicle (UAV) one way relaying (OWR) and a fixed two-way relaying (TWR). The second direction is scalability. We first study a multiple access channel (MAC) with multiple secondary users scenario. Secondly, we expand our scalability study to cognitive cellular networks. We propose a low-complexity algorithm for base station activation/deactivation and dynamic spectrum management maximizing the profits of primary and secondary networks subject to green constraints. The third direction is energy efficiency (EE). We present a novel power allocation scheme based on maximizing the EE of both single-input and single-output (SISO) and MIMO systems. We solve a non-convex problem and derive explicit expressions of the corresponding optimal power.