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Doctorate thesis defense of Imen Sahnoun

Doctorate thesis defense on February 24th 2017 at 09H00 AM ,in Amphi I, Sup’Com.


Presented by :  Imen Sahnoun 



Ridha Bouallegue

Professor at Sup'Com, Tunisia




Reviewers :

Mohamed Slim Alouini

Professor at KAUST, Saudi Arabia


Noura Sellami

Professor at ENIS, Tunisia


Examiner :

Leila Najjar Atallah

Associate Professor at Sup'Com, Tunisia


Supervisor :

Mohamed Siala

Professor at Sup'Com, Tunisia


Co-Supervisor :

Ines Kammoun Jemal

Associate Professor at ENIS, Tunisia



Cognitive radio is an exciting emerging technology that has the potential of dealing with the stringent requirement and scarcity of the radio spectrum and offers the ability of radio sensing, self adaptation and dynamic spectrum sharing. In this thesis, we are interested in the case where secondary users are allowed to communicate concurrently with primary users provided that they do not create harmful interference to the licensed users. More precisely, the secondary transmission depends on a variable cost that reliably quantifies the interference power generated by the secondary user at the primary base stations. Here, we aim to improve the cognitive system performance in terms of throughput. For this aim, we first propose to use an adaptive modulation technique at the unlicensed user in order to maximize its data rate. We study the system behavior as a function of several parame-ters such as the maximum allowed cost, the number of base stations in the primary network, the secondary user location and its transmission power.

Then, we propose to use cooperative techniques only if the resulting average interference power at the primary receiver is above a certain threshold. For relaying scenario, we adopt a space-time coding protocol based on Alamouti Space Time (ST) code as well as an Amplify and Forward (AF) protocol. Through simulations, we show that, these adaptive co-operative protocols have better performance compared with the classical cognitive system.

To further enhance the performance of the cognitive radio system, we propose, next, novel energy allocation schemes for the secondary users, considering the cooperative multi-hop transmission. Our optimization problem is formulated as a maximization of the instantaneous received signal to noise ratio, under interference power constraints that are im-posed to protect the primary network. In other words, we must maintain the interferences generated by the secondary transmissions to the primary network below an acceptable threshold level. We start by resolving geometrically our optimization problem for two and three hops. A variety of simulation results shows that our proposed energy allocation ap-proach, combined with adaptive modulation, gives a better performance compared to the classical cooperative scheme with uniform energy distribution. Then, we propose an ana-lytical optimal solution to the problem for the 2-hop case. We, also, show that the analytical resolution leads to the same results as the geometrical one.

Afterwards, we consider the case of multi-antenna secondary base station (BS-S) that does not have any prior information about the channel from the primary users. Hence, in order to maintain a limited interference during the downlink transmissions to the secondary users, the BS-S needs to get a perfect or partial knowledge of the primary users chan-nels. For this aim, we investigate the identification problem of the primary active users and propose two solutions. We start by proposing an efficient and reliable method for a blind active primary users identification, without any energy or radio resource losses, based on randomly rotated constellations for each transmitted symbol at the primary users. Then, we consider the realistic non-line-of-sight (NLOS) environment, and propose a novel and efficient primary users identification, using compressive sensing (CS). Our focus is on the angular sparsity of the received signal at the BS-S, given an unknown number of primary user source signals impinging upon the antenna array from different directions of arrival (DOA). Given multiple snapshots, multiple measurement vectors (MMV) are available at the secondary base station and considered for primary channel detection over the angular domain using the regularized MMV-FOCal Underdetermined System Solver (M-FOCUSS) algorithm. Next, we develop novel methods for paths separation and primary channels estimation based on their autocorrelation matrix properties. Finally, we focus on the downlink transmissions and propose to design a beamforming vector at the BS-S, based on the estimated channels, that maximizes the desired signal power to each secondary receiver while minimizing the total interference towards all primary receivers.