Research On Spectrum Sensing Algorithms In Cognitive Radio

Over the past years, we have witnessed a dramatic development of wireless communication technologies. The demand for radio spectrum resource increases ceaselessly. Because radio spectrum is a nature resource, it is limited on its utilization. Recent static spectrum allocation scheme cannot meet people's needs. However, the radio spectrum is rarely utilized continuously across time and space. In order to solve the predicament of spectrum scarcity and spectrum underutilization, cognitive radio (CR) has been put forward as a promising technology for future wireless communication. Cognitive radio is an intelligent wireless communication system, it can adapt to the environment and dynamically identify unoccupied licensed spectrum, and then operate on those idle spectrum holes without causing harmful interference to licensed users. Therefore, using this technology not only improves spectrum utilization efficiency but also solves the contradictions between the demand of wireless communication and finite spectrum resources.Firstly, this thesis gives out the definition and the function of the CR, as well as the key technologies and the current research situations at home and abroad in detail, which offers a research clue for the author.Secondly, this thesis describes the existing spectrum sensing technology in cognitive radio and divides the spectrum sensing technology into four kinds, i.e., transmitter detection, receiver detection and cooperative detection. By means of analysis and comparison, cooperative spectrum sensing becomes the basis of the research of the thesis. This chapter also introduces the cooperative spectrum sensing technology making use of various data fusion rules.When cognitive users experience multipath or shadowing effects, sensing results of cognitive users have great uncertainty. Therefore, this thesis proposes the fusion rule making use of evidence theory, which solves the uncertainty problem in cooperative spectrum sensing. This fusion rule can obtain more preferable detection performance than other "and","or","majority" fusion rules.At last, this thesis presents the proposed cooperative spectrum sensing scheme based on improved evidence theory. This scheme first selects second users with enough information to take part in combining at fusion center, which can save the bandwidth for reporting cognitive users' local observations. Furthermore, we use improved evidence theory to combine the selected sensing information, which can effectively reduce the computational complexity. The proposed scheme accomplishes excellent detection performance comparing with traditional evidence theory fusion rule.