Two-dimensional Spectrum Sensing Method For Spectrum-Heterogeneous Wireless Sensor Networks

Wireless sensor network(WSN)is the distributed self-organizing Network that composed of a large number of sensor nodes.It can sense the surrounding environment awareness intelligently and implement specific functions.Due to the advantages of low cost,low energy consumption and large scale,it has been widely used in ecological environment monitoring,healthcare,industrial production,smart home,and many other areas.However,due to the complex electromagnetic environment,the research on effective utilization of spectrum resources in WSN technology gradually causes the attention of many researchers,and this research has important theoretical significance and application.Because the main communication frequency of WSN is ISM 2.4 GHz frequency band and no application acquired before,it is widely used in short-range wireless communication technologies such as Wi-Fi,Bluetooth,and Zig-Bee.Much use of this spectrum causes serious spectrum resource shortage and channel congestion which would affect the reliability and timeliness of signal transmission.To solve the problems above,cognitive radio(CR)is introduced into the research of WSN.Spectrum sensing,as a basic function of CR,can detect the existence of the main signal on the ISM frequency band and allocate the use of channel reasonably.How to sense the spectrum information effectively is the main research of CWSN.Considering the problems existed in present nodes sensing methods,this paper proposed a two-dimensional sensing nodes selective fusion(TDSNSF)scheme which is based on the CWSN structure.To verify the validity and practicability of the scheme,we built a more realistic two-dimensional sensing model of wireless sensors network in which the position of the main signal transmitter is selected randomly in each iteration calculation process.In the sensing process,the acquisition and manipulation of the signal data are mainly divided into three steps: firstly,all nodes sense the spectrum locally and obtain the sensing results of every single node.Then the position of each sensor is estimated based on the local decision fusion algorithm,and the sensing nodes will be filtered on the space domain,so the nodes located within the transmission radius of the primary signal transmitter can be selected to sense the spectrum collaboratively.Finally,we adopt the OR fusion rule and establish the optimization model to minimize energy consumption in which way the specific sensing nodes can be selected by ensuring the high detection performance at the same time.The simulation results show that the proposed scheme solves the high false-alarm problem in the spatial domain under the sensing process of two-dimensional cognitive wireless sensors network.Moreover,this scheme can reduce the number of collaborative sensing nodes greatly and guarantee the detection performance at the same time,which in turn,can reduce the total energy consumption of the whole network and extend the life of the network.