Research On Key Technologies Of Cooperative Spectrum Sensing In Cognitive Radio Sensor Networks

Traditional wireless sensor networks usually work in Industrial Scientific Medical(ISM)band with limited resource,where plenty of industrial communication devices coexist and cause interference with each other easily.The deterioration of surrounding environment will impact the bandwidth and quality of service adversely,and the increasing shortage of spectrum resources has become one of the bottlenecks restricting the development of wireless sensor networks.The introduction of cognitive radio(CR)technology is considered to be an effective way for wireless sensor networks to alleviate the impact of those impairments.Comparatively,cognitive radio sensor networks(CRSNs)can change transmission parameters and employ the capability of spectrum sensing to enhance radio operating behavior and detect available channels in a wireless spectrum.However,it should be noted that the inherent energy and hardware limitations of sensor nodes impose challenges for the realization of potential advantages of incorporating CR capability in CRSNs.Hence,it is not suitable to apply the traditional CR technology with high complexity to spectrum sensing for CRSN directly,and the energy efficiency and multi-node cooperation should be considered fully.Therefore,it is of great theoretical and practical significance to conduct research work and propose suitable technology of spectrum sensing so as to promote the practical applications for wireless sensor networks.In actual wireless environment,the performance of cooperative spectrum sensing will be easily affected by many factors,which includes multipath effects and shadowing,hidden terminal problem,low signal noise ratio(SNR)and even noise variance fluctuation.The research in cooperative sensing is primarily concerned with how CR users cooperate to perform spectrum sensing,achieve the optimal detection performance and improve the reliability of sensing results.It faces many challenges and motivates more research works.To tackle those points of noise uncertainty,low SNR conditions,and data forgery attacks,the purpose of this paper is to improve the performance of cooperative spectrum sensing and the main contributes of our work include:(1)Dynamic dual threshold spectrum sensing method based on noise uncertainty.(2)Spatial correlation cooperative spectrum sensing scheme based on clustering in CRSNs.(3)Mitigation strategy against spectrum sensing data falsification attack in CRSNs.Aiming at the problem of threshold mismatch of energy detectors under noise power uncertainty,a cooperative spectrum sensing method with dynamic dual threshold is proposed.Firstly,the utility function is defined with the objective of minimizing the error probability of spectrum sensing,and the optimum threshold of energy detector is derived.Secondly,in order to mitigate the influence derived from noise uncertainty,an effective dynamic dual threshold adjustment mechanism is presented,and the optimizing combinative fusion rule is discussed with the prerequisite of the minimum global error probability.In addition,in view of insufficient number of cognitive users whose sensing results lie in decision zones,the parameter of credibility is defined to choose the secondary users with reliable local detection for final fusion.Simulation results show that our proposed method can mitigate the influence of noise uncertainty and increase the spectrum sensing accuracy compared with other existing methods.In view of the tradeoff between the performance improvement and the system resource consumption under different redundancy of cooperative sensing nodes,we propose an energy-efficient cooperative spectrum sensing scheme based on spatial correlation for cognitive radio sensor networks.To mitigate the communication overhead and ensure sufficient sensing accuracy,the cognitive sensor nodes can be grouped into several clusters.The member nodes undertake cooperative spectrum sensing tasks in turn by rotating,and send the local test statistic to their cluster head nearby.Then,by exploiting the spatial correlation of the members,the cluster head combines the sensing results and make use of likelihood ratio test to obtain the cluster decision.After receiving the decisions from all clusters,the fusion center employs hard scheme to make the final decision about spectrum occupancy.By analyzing the influence of spatial correlation on the performance of cooperative spectrum sensing,the optimal cluster threshold algorithm and the uncorrelated cooperative nodes selection algorithm are proposed.The simulation results show that our scheme not only provides the better sensing performance,but also improve the energy efficiency.To detect the primary user’s activity accurately in cognitive radio sensor networks,we conduct the analysis of cooperative spectrum sensing to mitigate the negative effect of spectrum sensing data falsification attack and even eliminate those attackers from the network.Firstly,we discuss the randomly false attack model and analyze the effects of two classes of attacks,individual and collaborative,on the global sensing performance at the fusion center.Afterwards,a linear weighted combination scheme is designed to eliminate the effects of the attacks on the final sensing decision.By evaluating the received sensing result,each sensor node can be assigned a weight related to impact factors,which includes result consistency degree and data deviation degree.Furthermore,an adaptive reputation evaluation mechanism is introduced to discriminate malicious and honest node.The evaluation is conducted through simulations,and the results reveal the benefits of the proposed in aspect of mitigation of spectrum-sensing data falsification attack.