Research On Spectrum Sensing Performance Optimization In Cognitive Radio

Wireless spectrum resource utilization is low and increasingly scarce, one of the effective solutions is cognitive radio. Spectrum sensing is a key task in cognitive radio, so the optimization problem of spectrum sensing performance is studied in this paper.First of all, the background, concept and crucial technology of cognitive radio are summarized, and the spectrum sensing technology is researched, and the current research situation at home and abroad is analyzed. The spectrum sensing methods are classified, the advantages and disadvantages are compared. The energy aware method is most widely used, because of its small amount of calculation and simple structure.Secondly, in the spectrum sensing based on the energy aware of the test, in order to achieve the best compromise between the perceived accuracy and perceived speed. Perceptual agility based on continuous sensing model can be characterized by the perceived time of the target. The optimization problem of single user sensing, multi users sharing sensing and multi users sharing sensing is discussed. Through the simulation, the visual simulation results are consistent with the theory. Under the constant missed detection criterion, we can minimize the average continuous perception of time by selecting an optimal sampling points, so as to realize the perception in dexterity maximization.Thirdly, the interference probability of relay algorithm for distributed network is analyzed optimized and simulated; a more generalized relay model of the distributed network with more users is built based on the relay model of the distributed network with two users; moreover, in order to measure how much the relay algorithm can reduce the system interference compared with the non-relay algorithm, a new index is defined and optimized, the results of simulation show that, under a certain condition, the relay algorithm can almost completely eliminate the interference generated by the non-relay algorithm.Finally, the throughput of the distributed cognitive network is optimized and compared. According to the frame structure in the sensing model, three sensing methods including the non-relay algorithm, the relay algorithm and the extended transmission algorithm are built. The final throughput expression of each algorithm is deduced under the constant missed detection criterion. Then the throughput gain of the relay algorithm to the non-relay algorithm is optimized. In addition, the throughputs of the three algorithms are compared.