Research On Clustering Routing Algorithm For Cognitive Radio Sensor Network

The integration of wireless sensor network(WSN) and cognitive radio(CR) technology enables a new paradigm of communication: cognitive radio sensor networks(CRSN). The existing WSN and CRN routing protocol is no longer fit for this new pattern network. Thus, it's necessary to combine these features to re-design a routing protocol for CRSN. With the features of easier topology management and high-efficiency energy saving, clustering routing protocol is advantageous for data fusion and transmission processing. As a result, clustering routing protocol becomes a research hotspot. The main research work and innovative achievements of the thesis are as follows:Firstly, new applications in various fields of CRSN are outlined and the existing clustering routing algorithm in CRSN is analyzed and summarized.Secondly, considering the lack of the advantage of channel resource brought by CR function in the existing clustering algorithm in WSN and the CR network(CRN) clustering algorithm is designed based on the infinite energy nodes, thus both algorithms cannot operate with energy efficiency in CRSN. Thus a low-energy adaptive uneven clustering hierarchy for CRSN is proposed in this thesis which not only considers the advantage of the channel resource in reducing the energy consumption but also employs uneven clustering method for balancing the energy consumption among the cluster heads under multiple hops transmission means. Simulation results show that the proposed algorithm can not only balance the energy consumption among cluster heads and network load in CRSN efficiently but also prolong the network lifetime remarkably compared with the existing several typical clustering algorithms in WSN and CRSN.Thirdly, taking into consideration of extra energy consumption, higher processing requirements and implementation cost brought by CRSN, a new type of CRSN named Heterogeneous nodes CRSN(H-CRSN) is proposed where the source sensing function and spectrum sensing function are undertaken by different nodes respectively. Then a workable clustering routing algorithm named as EECH is proposed, in which the cognitive nodes with the maximum number of available channels and the residual energy over certain energy threshold are chosen as cluster heads, the sensor nodes and other cognitive nodes choose to join the clusters according to the rule of minimum communication cost. Separate the cognitive nodes and sensor nodes can not only mitigate the energy resources insufficiency of sensor nodes but also reduce the cost of deploying cognitive sensor nodes which equipped with cognitive function. The simulation results show that the proposed clustering algorithm can efficiently operate in the H-CRSN and prolong the network lifetime significantly.Deep studies on MAC protocol and relative key techniques of CRSN are carried out in this thesis, and a number of results are obtained, which have some theoretical value and practical significance for future research of CRSN.