The cognitive radio (CR) concept is expected to be adopted along with many technologies to meet the requirements of the next generation of wireless and mobile systems, the 5G. Consequently, it is important to determine the performance of the CR systems with respect to these requirements. In this thesis, after briefly describing the 5G requirements, we present three main directions in which we aim to enhance the CR performance. The first direction is the 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). We propose special linear precoding schemes that enable the secondary user (SU) to take advantage of the primary-free channel eigenmodes. We study the SU rate sensitivity to the relay power, the relay gain, the UAV altitude, the number of antennas and the line of sight availability. The second direction is the scalability. We first study a multiple access channel (MAC) with multiple SUs scenario. We propose a particular linear precoding and SUs selection scheme maximizing their sum-rate. We show that the proposed scheme provides a significant sum-rate improvement as the number of SUs increases. 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. We show that our proposed algorithms achieve performance close to those obtained with the exhaustive search method. The third direction is the 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. When the instantaneous channel is not available, we present a simple sub-optimal power that achieves a near-optimal EE. The simulations show that the sub-optimal solution is very close to the optimal one. In the MIMO case, we show that adopting more antennas is more energy efficient.

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015. / Submitted by Fernanda Percia França (fernandafranca@bce.unb.br) on 2015-12-01T17:09:19Z No. of bitstreams: 1 2015_SamirKolawoléAkanniLandou.pdf: 2034280 bytes, checksum: e8c84ed0e5485fb56994f5d26d16cb7b (MD5) / Approved for entry into archive by Raquel Viana(raquelviana@bce.unb.br) on 2016-05-13T18:15:09Z (GMT) No. of bitstreams: 1 2015_SamirKolawoléAkanniLandou.pdf: 2034280 bytes, checksum: e8c84ed0e5485fb56994f5d26d16cb7b (MD5) / Made available in DSpace on 2016-05-13T18:15:09Z (GMT). No. of bitstreams: 1 2015_SamirKolawoléAkanniLandou.pdf: 2034280 bytes, checksum: e8c84ed0e5485fb56994f5d26d16cb7b (MD5) / Com o crescimento das redes celulares e com o surgimento de novas tecnologias, o consumo de energia e a eficiência energética das redes celulares se tornaram mais importantes. Recentemente, as comunicações verdes têm recebido muita atenção, a fim de reduzir o consumo de energia e minimizar as emissões de dióxido de carbono (CO2). Neste trabalho, estamos interessados em métodos de eficiência energética que otimizam a redução do consumo de energia das redes celulares, especialmente alterando a potência transmitida de estações de base. Investigamos algumas soluções encontradas na literatura, a saber, o sleep mode e o cell zooming. Nós investigamos também o uso do Coordinated Multi-Point (CoMP), uma tecnologia de rádio de transmissão coordenada, a fim de melhorar a qualidade da rede. _______________________________________________________________________________________________ ABSTRACT / With the growth of cellular networks and emergence of new technologies, the power consumption and energy efficiency of cellular networks have become more important. Recently, green communications have received much attention in order to reduce the energy consumption and minimize the carbon dioxide (CO2) emission. In this work, we are interested in power efficiency methods which optimize the energy saving of the cellular networks especially altering the transmitted power of base stations. We investigate some solutions found in the literature, namely sleep mode and cell zooming techniques. We also investigate the use of Coordinated Multi-Point (CoMP) transmission radio technology in order to improve the quality of the network. _______________________________________________________________________________________________ RÉSUMÉ / Avec la croissance des réseaux cellulaires et l'émergence de nouvelles technologies, la consommation d'énergie et l'efficacité énergétique des réseaux cellulaires sont devenues plus importantes. Récemment, les communications vertes ont reçu beaucoup d'attention dans le but de réduire la consommation d'énergie et de réduire les émissions de dioxyde de carbone (CO2). Dans ce travail, nous nous intéressons à des méthodes d'efficacité de puissance qui optimisent l’économie d'énergie des réseaux cellulaires en altérant particulièrement la puissance transmise des stations de base. Nous avons étudié des solutions trouvées dans la littérature, à savoir le sleep mode et le cell zooming. Nous avons étudié également l'utilisation de Coordinated Multi-Point (COMP), une technologie de radio de transmission coordonnée, afin d'améliorer la qualité du réseau.

Nous vivons une révolution numérique où l’Internet est devenu un élément essentiel de notre vie quotidienne. Avec plus de 750 millions de foyers connectés et plus de 6,8 milliards d'abonnés à la téléphonie mobile, les réseaux cellulaires dominent le secteur des Technologies de l'Information et de la Communication (TIC) avec plus de 75%. La tendance est à la hausse et ne semble pas avoir de signe de ralentissement dans un avenir proche en raison des nouveaux services et applications en cours. Cependant, cette augmentation radicale des appareils et services TIC a poussé la consommation d'énergie correspondante et son impact sur l'environnement à croître à un rythme effarant, consommant plus de 5% de l'énergie électrique mondiale et libérant dans l'atmosphère environ 2% des émissions de CO2. Étant donné que les stations de base, éléments essentiels de la fourniture d’accès à l’Internet, consomment la plus grande partie de l’énergie des réseaux cellulaires, il est essentiel d’étudier de nouvelles stratégies et architectures afin de prévenir cette pénurie d’énergie. Cette thèse porte sur le rôle essentiel de l'énergie dans la conception et l'exploitation de futurs réseaux cellulaires. Nous considérons des approches différentes et complémentaires, y compris des techniques d'efficacité énergétique (gestion des ressources radio et systèmes de sommeil), des sources d'énergie renouvelables, le Smart Grid et des outils d'apprentissage basés sur l’intelligence artificiel pour réduire la consommation d'énergie de ces réseaux complexes tout en garantissant une certaine qualité de service adapté aux cas d'utilisation 5G. / We live in the digital era where the Internet has become an essential part of our daily lives. With more than 750 million connected households and over 6.8 billion mobile subscribers, mobile networks are dominating the Information and Communication Technology (ICT) sector with more than 75%. The trend is of further increase and appears to have no signs of slowing down in the near future due to the ongoing new services and applications. However, this radical surge of ICT devices and services has pushed corresponding energy consumption and its footprint on the environment to grow at a staggering rate consuming more than 5% of the world’s electrical energy and releasing into the atmosphere about 2% of the global CO2 emissions. Since base stations, the core elements to provide internet access, consume most of the energy in cellular networks, it is essential to study new strategies and architectures in order to deter this energy crunch. This thesis focuses on the crucial role of energy in the design and operation of future cellular networks. We consider different and complementary approaches and parameters, including energy efficiency techniques (i.e., radio resource management and sleep schemes), renewable energy sources, Smart Grid and tools from machine learning to bring down the energy consumption of these complex networks while guaranteeing a certain quality of service adapted to 5G use cases.