Les progrès technologiques ont permis le développement d’applications de capteurs sans fil. Ces capteurs sont généralement déployés avec des ressources énergétiques réduites où le remplacement d’une batte rie peut être coûteux. L’efficacité énergétique est une contrainte importante pour assurer une grande autonomie. La tendance actuelle vers des applications à haut débit demande non seulement une grande efficacité spectrale mais aussi une consommation réduite de l’énergie. Étudier le compromis entre l’efficacité spectrale et l’efficacité énergétique pour les réseaux de capteurs sans fil (RCSFs) est donc primordial. Nous nous concentrons dans cette thèse sur l’étude des techniques adoptées au niveau de la couche physique. D’abord, les différents aspects caractérisant les RCSFs sont introduits. Puis les approches courantes pour réduire l’énergie dans ces réseaux sont rappe- lés tout en soulignant le lien entre la consommation d’énergie et l’amélioration de l’efficacité spectrale. Des modèles courants de consommation d’énergie sont introduits et classés afin d’étudier l’évolution de l’énergie consommée en fonction de l’efficacité spectrale. En second lieu, nous nous sommes focalisés sur le choix de la modulation du point de vue énergétique et spectrale afin de trouver le schéma de modulation optimal qui minimise l’énergie. Nous avons étudié ensuite le com- promis entre l’efficacité énergétique et spectrale en tenant compte des contraintes imposées par le système. Enfin, nous nous sommes intéressés à l’intégration du codage et du protocole de contrôle d’erreurs dont nous avons étudié l’impact sur le compromis efficacité énergétique et efficacité spectrale. / Technological advances have led to the develop- ment of wireless sensor applications. These sensors are generally deployed with reduced energy resources where replacing a battery can be costly. Energy ef ficiency is an important constraint to ensure a high level of autonomy. The current trend towards high- throughput applications requires not only high spectral efficiency but also reduced energy consumption. It is therefore essential to study the trade-off between spec tral efficiency and energy efficiency for wireless sensor networks (WSNs). In this thesis we concentrate on the different techniques adopted at the level of the phys- ical layer. At first, the various aspects characterizing the WSNs are introduced. Then, the efforts made to optimize the conservation of energy in these networks are summarized while highlighting the link between the energy consumption and the spectral efficiency. Then, different energy models are introduced and classified in order to study the evolution of the consumed energy as a function of the spectral efficiency. Secondly, we focus on the choice of modulation in order to find the optimal scheme that minimizes energy. We then studied the tradeoff between energy and spectral efficiency, taking into account the constraints imposed by the sys- tem. Finally, we are interested in coding strategy and error control protocol to study their impact on the energy efficiency and spectral efficiency tradeoff.

Wireless Sensor Network (WSN) is a widely researched technology that has applications in a broad variety of fields ranging from medical, industrial, automotive and pharmaceutical to even office and home environments. It is composed of a network of self-organizing sensor nodes that operate in complex environments without human intervention for long periods of time. The energy available to these nodes, usually in the form of a battery, is very limited. Consequently, energy saving algorithms that maximize the network lifetime are sought-after. Link adaptation polices can significantly increase the data rate and effectively reduce energy consumption. In this sense, they have been studied for power optimization in WSNs in recent research proposals. In this thesis, we first examine the Adaptive Modulation (AM) schemes for flat-fading channels, with data rate and transmit power varied to achieve minimum energy consumption. Its variant, Adaptive Modulation with Idle mode (AMI), is also investigated. An Adaptive Sleep with Adaptive Modulation (ASAM) algorithm is then proposed to dynamically adjust the operating durations of both the transmission and sleep stages based on channel conditions in order to minimize energy consumption. Furthermore, adaptive power allocation schemes are developed to improve energy efficiency for multi-hop relay networks. Experiments indicate that a notable reduction in energy consumption can be achieved by jointly considering the data rate and the transmit power in WSNs. The proposed ASAM algorithm considerably improves node lifetime relative to AM and AMI. Channel conditions play an important role in energy consumption for both AM and ASAM protocols. In addition, the number of modulation stages is also found to substantially affect energy consumption for ASAM. Node lifetime under different profiles of traffic intensity is also investigated. The optimal power control values and optimal power allocation factors are further derived for single-hop networks and multi-hop relay networks, respectively. Results suggest that both policies are more suitable for ASAM than for AM. Finally, the link adaptation techniques are evaluated based on the power levels of commercial IEEE 802.15.4-compliant transceivers, and ASAM consistently outperforms AM and AMI in terms of energy saving, resulting in substantially longer node lifetime. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2011-02-08 18:26:29.222