Reduce The Handoff Latency In Cognitive Radio Network
Due to the enormous development in communication technology, demand for the spectrum is expected to grow even more tremendously in the coming years. To cope up with the ongoing demand, one of the most promising concepts to facilitate the flexible usage of the radio environment is knows as Cognitive Radio. Disaster scenario is the most amazing usage case of cognitive radio networks, where CR node can use the best available spectrum to establish an ad-hoc network through its cognition capability and reconfigurability. However, with most of the spectrum being already allocated, it is becoming exceedingly hard to find unoccupied bands either to deploy new services or to enhance the existing one due to the lack of frequency bands in radio spectrum. In this case, the most important challenge is to share the licensed spectrum without interfering with transmission of other licensed users.
Hence, CR node should immediately vacate the spectrum upon detection of licensed user on the particular frequency band, which known as spectrum handoff or spectrum mobility. In order to manage the spectrum handoff, current researches are mainly focus to stay in licensed spectrum. In addition, there are some other proposals that take in consideration of both licensed and unlicensed frequency band. However, most of the cases they manages the channel state information in static manner which it is very much impractical due to dynamic nature of the spectrum allocation.
The idea of my work is to manage the information about the availability of spectrum in such a way that CR users can reduce the spectrum handoff. To achieve that, my focus is to develop an algorithm to discover the spectrum opportunities as fast as possible to incorporate with DSA. The benefits and drawbacks of such strategies will be compared with more conventional approaches.Â A mixture of simulation and analysis will be used to assess performance of the algorithm. Game theory and Markov analysis will be particularly important analytical tools for the spectrum selection process among the secondary users.Table of Contents
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