Energy-efficient Distributed Cooperative Spectrum Sensing And Resource Allocation

Nowadays, there are many research works solving the problem of scarce spec-trum resource with cognitive radio technique. Cooperative Spectrum Sensing (CSS)is a method for improving the sensing accuracy in Cognitive Radio Networks (CRNs).With the limited energy of wireless devices, the energy-efciency of CSS attracts moreand more attention.The energy-efciency of CSS is using less energy consumption for more availabletime of spectrum. Much of energy and time is used for exchanging sensing informationbetween Secondary Users (SUs), algorithms with faster convergence rate for cooper-ation should be studied in CSS. If an SU senses more channels, the probability of ac-cessing a channel is improved, but the resource allocation limits the SUs’ cooperation.Forsolvingthesetwoproblems, adistributedCSSconsensusalgorithmwithafastconvergencerateandaheuristicmethodformulti-channelsCSSandresourceallocationare proposed in this thesis. The main contribution of this article is:1. A consensus algorithm using contextual information is proposed in this article.Consensus method is a kind of typical distributed CSS methods. However, using thismethod, much of the energy consumption for cooperation is used for repeatedly recir-culating redundant information. Using contextual information, the proposed methoddivided all the SUs into two groups: the SUs in the same group has a same sensing de-cision, two SUs can exchange information when they are in diferent groups. With thisalgorithm, SUs will not repeatedly exchange redundant information, the convergencerate is improved.2. An heuristic algorithm is proposed in this article to optimize the system utilityin multi-channels cooperative spectrum sensing. An SU will access only one channel, though it will sense more than one channel, however, the selfsh actions of SUs willcut down the sensing accuracy of some channels, other SUs’ utilities are infuenced.Using the method in this article, all SUs will choose their access channels reasonably.The sensing accuracy of all the sensed channels is improved, the utility of the systemis optimized.Theoretical analysis and simulations are used for verifying the proposed methods.Alltheseresultsshowsthattheproposedmethodsinthisarticleshowgoodperformancefor solve the two problems.