Research On Joint Radio Resource Management In Cognitive Radio Network

Cognitive radio is a new paradigm of designing wireless communications systems.It realizes more reliable and more efficient communication with enhancing theutilization of the radio frequency (RF) spectrum. Cognitive radio is an intelligentwireless communications technology which has the capability of sensing the ambientradio environment. It is able to autonomously adjust its radio operating parameters tothe changing and complex communication environment.Cognitive radio technology can realize real-time, flexible access to spectrum holesby using dynamic spectrum access strategy to optimize wireless transmissionperformance. Dynamic spectrum resource management analysis and exploits themeasurement information of spectrum holes, then makes decision on spectrum access. Ithas high requirement on the stability and adaptive capacity of decision algorithm. In thispaper, we conduct a systematic research on cognitive radio and dynamic spectrumaccess strategy in terms of learning complex environment, obtaining long-term rewardsand considering multi-objective variables.The key theory and implementation technique in cognitive radio are investigated.First, the paper discusses the pro and cons of existing algorithms and techniques fromthe aspects of effectiveness, fairness and complexity, clearing the direction for furtherresearch. Then we study the major technologies required by the analysis, design andoptimization of dynamic spectrum access and management, such as game theory andmachine learning.A dynamic spectrum decision algorithm based on reinforcement learning and fuzzylogic theory is introduced in this paper. We apply this decision algorithm to differentspectrum model and network architecture. Through simulation, we analyze theeffectiveness of the algorithm, compare the performance of the proposed dynamicspectrum decision strategy with the exiting access algorithms, and discuss the otherfactors affecting the performance of the proposed algorithm.