Cognitive radios have been proposed as a new technology to counteract the spectrum scarcity issue and increase the spectral efficiency. In cognitive radios, the sparse assigned frequency bands are opened to secondary users, provided that interference induced on the primary licensees is negligible. Cognitive radios are established in two steps: the radios firstly sense the available frequency bands by detecting the presence of primary users and secondly communicate using the bands that have been identified as not in use by the primary users.<p><p>In this thesis we investigate how to improve the efficiency of cognitive radio networks when multiple cognitive radios cooperate to sense the spectrum or control their interferences. A major challenge in the design of cooperating devices lays in the need for exchange of information between these devices. Therefore, in this thesis we identify three specific types of control information exchange whose efficiency can be improved. Specifically, we first study how cognitive radios can efficiently exchange sensing information with a coordinator node when the reporting channels are noisy. Then, we propose distributed learning algorithms allowing to allocate the primary network sensing times and the secondary transmission powers within the secondary network. Both distributed allocation algorithms minimize the need for information exchange compared to centralized allocation algorithms. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished