Optimization Sensing Algorithm And MAC Protocol Design In Cognitive Radio

With the rapid growth of Mobile Internet, accessing to wireless networks at any time and any where is becoming necessities of daily life. Wireless data communication service grow exponentially, however, spectrum resources is running out with the traditional fixed spectrum allocation strategy, which will become a main bottleneck for the development in wireless network. As a solution, researchers come up with a novel spectrum allocation scheme, which is known as cognitive radio. It allows the unauthorized wireless devices to access the spectrum dynamically when the authorized ones do not with the permission of government, which meets the unauthorized devices'transmission needs and ensures the Qos of them. Meanwhile, with the effective scheduling strategy, interference to the authorized users is expected to be minimum, which will increase the channel utilization remarkablely.This dissertation studies about the optimal spectrum detection algorithm when channel occupancy and channel vacancy duration are exponentially distributed. First, we analyzed the channel usage pattern prediction by parameter estimation, then, based on the pattern we got, an optimazied MAC protocol is designed in an efficiency prioritied way, that is, to maximize profit in every sensing, spectrum detection accuracy and sensing overheads are properly balanced.First, the author first summarizes the mainstream spectrum sensing algorithms, including PHY-sensing and MAC-sensing, compares their strengths and weaknesss, concludes the existing challenges in the current spectrum sensing schemes, and sums up the defects in the current works. Furthermore, based on the historical statistics, the author works on the parameter estimation and hypothesis testing for the channel usage model, analyzes a most common case based on negative exponential distribution network service time, including parameter estimation and hypothesis testing for both busy and idle period.On the other hand, the author studies the scheduling algorithm based on the channel usage probability model of the authorized users, calculates the optimal detection interval when authorized spectrum usage is exponentially distributed, comes up with a novel scheduing algorithm based on the channel usage probability model of licensed spectrum. By calculating the optimal sensing interval based on the primary users'service time and idle period probability distribution, the new algorithm balances and optimizes the wasted accessing opportunities and the sensing overheads. The novel algorithm overcomes the drawbacks of the traditional algorithms, that is, sense channels to acquire the most access opportunities without consideration of sensing overheads, or great complexity introduced when avoid sensing overheads, which will bring down the performance remarkablely in mean radio environments.At last, the author concludes this dissertation, presents further advices for the future research on some related issues.