Research On Spectrum Sensing Technology In Cognitive Radio

Cognitive radio technology is an effective method to solve the spectrum resourceconstraints. Multiple cognitive users in cognitive network perform cooperative spectrum sensingcan solve the problem of hidden terminal and shadow fading as well as improve the performanceof spectrum sensing. Cooperative spectrum sensing (CSS) has centralized or distributedcollaborative ways. The main research direction of this paper is the cooperative spectrum sensingtechnology, so centralized and distributed spectrum sensing schemes were both studied.In traditional centralized spectrum sensing algorithm, there has two different thresholdselection methods—single threshold or dual-threshold. Single threshold detection algorithm issensitive to noise and other interference and dual-threshold detection algorithm has lesssensitivity to noise. But the sensing information between the double thresholds has not been fullyapplied, the spectrum detection efficiency need to be improved. To address this problem, wepropose a Dynamic Dual-threshold CSS method Based on DS Evidence Theory (DDDS). Inlocal sensing, dual-threshold is set dynamically. The primary user’s signal energy what eachcognitive user received is been comprised to dual-threshold. The cognitive user will send thesensing result0or1to the base station if the received signal is beyond dual-threshold; thecognitive user will calculate trust function based on DS evidence theory, and then transmit it tothe cognitive base station if the received signal is between two thresholds. Cognitive base stationmakes the final decision according to the K rank criteria. This can effectively make use of theinformation between the double thresholds, and thus improve the perceived performance of thewhole system. Finally, the performance analysis and simulation results show that under the samefalse alarm probability, the algorithm’s detective probability is higher than ordinarydual-threshold sensing algorithm and fixed dual-threshold sensing algorithm based on D-Sevidence.Traditional distributed spectrum sensing algorithm use the average consensus theory tomake each CR exchange sensing information with its neighbor users, then through solving theiterative spectral estimation and optimization problem to make all the CR’s spectrum sensinginformation to a consensus. But the channel between the CR is generally assumed ideal, whichmeans the user at each iteration step received neighbor information directly, and assuming thatthey are not affected by noise. It is clear that this approach could be improved. This paper will be proposed A New Distributed CSS Method Based on Average Consensus. First of all cognitiveusers do local energy sensing, and put the sensing result as the initial value of the averageconsensus iterative algorithm, the detect value of each cognitive user will reach a consensusalmost after P times iterations, finally detect value were compared with the threshold. If it isabove the threshold primary user will be judgment exists, if it is below the threshold primaryuser will be judgment not exist. The simulation analysis the best parameter, and proves the newmethod have the higher detective probability then ordinary sensing algorithm based on averageconsensus.