Research On Cognitive User Cooperation Based Spectrum Sensing Algorithm

Cognitive radio is a wireless communication concept which can implement self-cognition and historical study strategies. It can search and use free spectrum resources in real time by a serious of spectrum sensing methods to relieve the increasingly scarce status of spectrum resource in current radio environment. Among all the cognitive radio technologies, spectrum sensing is the premise and foundation of dynamic spectrum access, spectrum coexistence and other key technologies. With the rapid development of wireless communication and services, more and more spectrum is needed to meet the increasing transmission speed requirements of users. However the spectrum gain brought by the current narrowband spectrum sensing is far from enough, potential new sensing methods such as multi-user cooperative sensing and wideband spectrum sensing attract more researchers because they can acquire the usage of a large scale spectrum to bring more access opportunities for cognitive users.This article summarizes the cognitive radio spectrum sensing technologies in category firstly, and then researches the eigenvalue algorithm based cooperative spectrum and cooperative compressed spectrum sensing in wideband scenario separately. Detailed work and innovations are as follows:1. For the situation that there may be spectrum occupied by more than one primary user, this article proposes a sensing method that firstly estimates the size of the primary user signal space according to random matrix theory, and then executes maximum likelihood estimator for other parameters basing on this estimated value, thus the likelihood function is achieved, and the prior decision threshold also can be acquired according to the false alarm probability. By comparing the likelihood function and the decision threshold, it can be analyzed that how many primary users exist in that spectrum. Simulation results show that with the same channel and noise condition, the proposed eigenvalue based cooperative spectrum sensing algorithm can reach the optimal sensing performance with one or more primary users.2. This article introduces cognitive cooperation and sparse estimation theory of compressed sensing into wideband spectrum sensing, and proposes a novel user cooperation based wideband compress spectrum sensing algorithm. Firstly, it caculates the minimum sampling number and user number of cooperative sensing according to the maximum possible sparsity which is a prior information, and estimates the actual spectrum sparsity. the sampling rate which can fully restore the signal can be defined based on the estimated sparsity. the optimal detection performance can be achieved with the least overhead. Simulation results reveal that the proposed algorithm can guarantee a relatively high detection performance and decrease the doubling increased sampling cost generated by cooperative sensing at the same time. Comparing with traditional spectrum sensing method, the proposed algorithm can reach the highest detection probability with the same sampling cost.