Cognitive Radio Spectrum Perception Of Technology Research

The relative scarcity and waste made the situation of the limited wireless spectrum resource more tense. How to improve wireless spectrum efficiency to the maximum has become a technical problem that needed to be solved urgently. Cognitive radio technology, an intelligent radio technology which possesses the capability of autonomously searching and using idle wireless spectrum resource, is proposed to solve the problem motioned above and it can greatly improve wireless spectrum efficiency.Spectrum sensing technology is a key implementation technology of Cognitive Radio. It reflects the most essential characteristic of Cognitive Radio, that is, able to sense and analyze the frequency band in a specific region and find the suitable spectrum holes. According to the number of cognitive users, spectrum sensing technology can be divided into single-user spectrum sensing technology and multi-users cooperative spectrum sensing technology.Firstly, several existing single-user spectrum sensing techniques were summed up and analyzed, such as matched-filter detection, waveform detection, energy detection, wavelet detection, cyclostationary detection, entropy-based detection and maximum eigenvalue detection. Especially, the capability analysis of energy detection was emphasized, which would be used in the following chapters.Secondly, the optimal design of discontinuous spectrum sensing scheme was studied, which aimed at minimizing the spectrum opportunities discovery time while satisfying the sensing overhead constraint. We employed a continuous-time Markov process with two states, i.e. ON (the licensed channel is occupied) and OFF (the licensed channel is idle), to describe the behavior of the primary user. Based on the investigation of the probability density function of the sensing number, we firstly derived an expression for the average spectrum opportunities discovery time in the single channel case. Subsequently, we expanded the analysis to the scenario of multiple channels. Finally, the simulation results were presented.Thirdly, the multi-users cooperative spectrum sensing problem was studied. Through analyzing advantages and disadvantages of the hard-decision fusion method and the soft-decision fusion method as well as by using Equal-Probability Quantization Equal-Length Coding method and Equan-Interval Quantization Variant-Length Coding method respectively, we proposed a cooperative spectrum sensing algorithm based on quantization and encoding to reduce the reporting channel overhead. The simulation results showed that cooperative spectrum sensing algorithm based on quantization and encoding could effectively reduce the reporting overhead under constrained sensing performance loss.Finally, the power control problem which occurred when the base station distributed sensing messages to cognitive users was studied. MIMO (multiple input multiple output) technology was introduced into cognitive radio system to enhance system capacity. The interference to primary user was not taken into account by traditional capacity analysis on MIMO technologies. To avoid causing significant interference to the primary user, a power allocation algorithm was proposed based on interference temperature. Theoretical analysis and simulation results showed that higher channel capacity could be achieved with no significant interference to primary user.