Researches On Spectrum Sensing And Balance Of Energy Consumption In Cognitive Wireless Sensor Networks

The technologies of Cognitive Radio are introduced into Cognitive Wireless Sensor Networks(CWSN), so the nodes have the ability of spectrum cognition. The bottlenecks which restrict the development of Wireless Sensor Networks can be overcome because CWSN can make full use of the idle licensed spectrum resources. Based on the traditional Wireless Sensor Networks, the nodes of CWSN have limited energy, so traditional technologies of Cognitive Radio Networks can not apply to CWSN. More efficient detection algorithm is needed.An improved cooperative spectrum sensing scheme in cognitive radio networks is proposed. The Existing methods either need more data of credibility, or need to greatly increase the SU computation in order to reduce the transmission data volume of SU, but they cannot apply to CWSN. In the local sensing period, double threshold decision is introduced to remove the cognitive users with low reliability so as to reduce the transmission data volume of SUs. Compared with classical detection scheme based on credibility, this scheme significantly reduces the transmission data. Compared with the scheme based on complex operations to reduce transmission of data, this scheme also reduce the transmission data without extra amount of calculation. The simulation results show that the novel scheme can keep high detection performance and reduce the transmission data volume of SUs with a low calculation of cooperative system.The nodes near convergence center can consume too much energy in the Large-scale CWSN, because they need to take more tasks of data forwarding. The double clustering algorithm is proposed in this paper to solve this problem. First, the forwarding cluster heads are voted according to the residual energy of nodes and the distance to the convergence center. Then, the sensing cluster heads are voted according to LEACH agreement. Next, the forwarding clusters are established between the forwarding cluster heads and the sensing cluster heads, and the sensing clusters are established between the sensing cluster heads and the sensing nodes. At the same time, the algorithm adopts the spectrum sensing technology to reduce interference and channel conflict. The simulation results show that the novel algorithm can reduce energy consumption of the nodes near convergence center in the Large-scale CWSN, so as to prolong the life cycle of the network.