Resource allocation consists in allocating spectrum and power on every link of a network, possibly under power and rate requirements. In the context of cognitive radios, almost 15 years of research produced an impressive amount of theoretical contributions, exploring a wide range of possibilities. However, despite the ever-growing list of imaginable scenarios, we observe in Chapter 2 that most of these studies are based on similar working hypotheses. Our first contribution is to challenge some of these hypotheses, and propose a novel resource allocation scheme. Sticking to realistic assumptions, we show how our scheme reduces both computational complexity and control traffic, compared to other state-of-the-art techniques.<p><p>Due to a majority of the abovementioned studies making some constraining assumptions, realistic system designs and experimental demonstrations are much more quiet and unharvested fields. In an effort to help this transition from theory to practice, our second contribution is a four-nodes cognitive network demonstrator, presented in Chapter 3. In particular, we aim at providing a modular platform available for further open collaboration: different options for spectrum sensing, resource allocation, synchronisation and others can be experimented on this demonstrator. As an example, we develop a simple protocol to show that our proposed resource allocation scheme is fully implementable, and that primary users can be avoided using our approach.<p><p>Chapter 4 aims at removing another working hypothesis made when developping our resource allocation scheme. Indeed, resource alloca- tion is traditionally a Media Access Control (MAC) layer problem. This means that when solving a resource allocation problem in a network, the routing paths are usually assumed to be known. Conversely, the routing problem, which is a network layer issue, usually assumes that the available capacities on each link of the network (which depend on resource allocation) are known. Nevertheless, these two problems are mathematically entangled, and a cross-layer allocation strategy can best decoupled approaches in several ways, as we discuss in Chapter 4. Accordingly, our third and last contribution is to develop such a cross-layer allocation scheme for the scenario proposed in previous chapters.<p><p>All conclusions are summarised in Chapter 5, which also points to a few tracks for future research. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished
| Identifer | oai:union.ndltd.org:ulb.ac.be/oai:dipot.ulb.ac.be:2013/209352 |
| Date | 20 January 2014 |
| Creators | Lessinnes, Mathieu |
| Contributors | Horlin, François, De Doncker, Philippe, Emplit, Philippe, De Doncker, Philippe, Sakaguchi, Kei, Vandendorpe, Luc, Dricot, Jean-Michel |
| Publisher | Universite Libre de Bruxelles, Université libre de Bruxelles, Ecole polytechnique de Bruxelles – Electricien, Bruxelles |
| Source Sets | Université libre de Bruxelles |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis, info:ulb-repo/semantics/doctoralThesis, info:ulb-repo/semantics/openurl/vlink-dissertation |
| Format | No full-text files |
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