Research On Neighbor Discovery For Cognitive Radio

Cognitive radio (CR) is such a promising technology that provides a new solution to the shortage of spectrum resource for wireless communications. However, it is still facing lots of technical challenges to make it widespread deployed. Neighbor discovery is one of them in the distributed cognitive systems. Usually, the spectrum for cognitive radio is dynamic, so there is no fixed access channel for the CR users. If there is also no a pre-settled control center, neighbor discovery becomes more complicated. This dissertation discusses the neighbor discovery problem under two different conditions.In the first condition, the primary users act regularly, and the spectrum occupancy do not vary for a long time. A typical instance, UHF band, is studied in the dissertation. Then the time complexity in neighbor discovery and a common-channel-seeking based neighbor discovery algorithm are figured out under the condition. For that the adjacent nodes’ channel sets have strong relevancy with each other in most cases, an optimization is proposed, with which the neighbor discovery process shortened.In the other situation, the primary users act frequently. The channel occupancy follows no pattern, and it changes fast. A typical example, GSM band, is analyzed, and the channel characteristics are summarized from statistical view. Under this situation, a channel-grouping based neighbor discovery algorithm is proposed. From the simulation result, the grouping strategy reduces the time complexity effectively in neighbor discovery.