Research On Spectrum Sensing And Resource Allocation Strategy For Energy-Harvesting-Based Cognitive Radio Sensor Networks

The emergence of cognitive radio sensor network(CRSN)has changed the current situation of spectrum resource shortage and increasingly serious interference problems in traditional wireless sensor network(WSN).However,the introduction of cognitive radio(CR)technology increased the energy consumption of the nodes,which greatly shortened the service life of the energy-constrained nodes.In order to keep the node running,this thesis considers introducing the energy harvesting(EH)technology into CRSN,thus producing one new type of network: energy-harvesting-based CRSN(EH-CRSN).In this thesis,the energy efficient spectrum sensing strategy in EH-CRSN is mainly studied,and based on the results of spectrum sensing,the channel allocation mechanism is designed to minimize the transmission delay of network nodes in the phase of data transmission.Firstly,according to the idea of cross entropy algorithm,this thesis proposes an algorithm aiming at optimizing the energy utilization efficiency of nodes: EESS.The EESS algorithm is based on the spectrum sensing scheduling problem in EH-CRSN under multi-channel environment.It can maximize the energy efficiency of the network while ensuring spectrum sensing performance and meeting the data node time requirements.Compared with the traditional algorithm that does not consider energy efficiency optimization when optimizing the available channel time of the network,EESS algorithm considers more network performance indicators when optimizing energy efficiency.On the one hand,the channel available time detected by the node satisfies the transmission time constraint required by the data node;On the other hand,the algorithm controls the false alarm rate of the nodes and improves the utilization rate of available channels.Meanwhile,EESS algorithm takes into account the deployment cost of nodes and solves the problem that existing algorithms are difficult to be applied in practice.Simulation results show that the EESS algorithm can maximize the network energy efficiency under the premise of ensuring the energy sustainability of the nodes.Secondly,this thesis studies the channel allocation strategy in EH-CRSN under the multi-channel environment,and proposes an ordered channel assignment algorithm based on time delay minimization: OSA.Based on the available channels detected in the spectrum sensing phase,the OSA algorithm minimizes the average transmission delay of the data nodes in the network by optimizing the channel allocation problem in the data transmission phase.This algorithm takes the channel availability probability and the number of nodes waiting on the channel as the criteria of channel evaluation.Channels with higher availability probability and fewer waiting nodes are easier to be selected by nodes.The simulation results show that the OSA algorithm proposed in this thesis greatly reduces the time complexity of the algorithm under the premise of ensuring good transmission performance.Meanwhile,this algorithm effectively improves the real-time performance of data transmission,which promotes the application of the Internet of Things in the field of instant messaging.