Research On Energy-Efficient Cooperative Spectrum Sensing In Cognitive Radio

With the advent of the Internet of Everything era,the number of communication services and mobile devices has exploded,and the contradiction between the huge demand for spectrum resources and the scarcity of spectrum resources has became increasingly acute,so cognitive radio technology has been proposed as an effective solution.Cognitive radio technology can allow the primary user and the secondary user to share the authorized frequency band under the premise of ensuring the normal communication of the primary user,which greatly improves the spectrum utilization rate.In order to improve the sensing performance of the system,the cooperative spectrum sensing technology is the most commonly used technology.During the sensing process,multiple nodes jointly determine whether the primary user is using the target frequency band,which can greatly improve the detection performance of the system.However,operative sensing of multiple nodes will also greatly increase system energy consumption.Hence,energy saving and green communication have became the current development direction.Aiming at the energy conservation in cooperative spectrum sensing,this thesis studies user-selected cooperative spectrum sensing algorithm based on energy consumption and the improved fusion algorithm in the fusion center.The main work and innovations are as follows:The first is the research on user selection in cooperative spectrum sensing.This thesis mainly aims at the phenomenon that all sensing users participating in the cooperative spectrum sensing process during the cooperative spectrum sensing process may does nothing to improve the sensing performance but must greatly increase the system's sensing energy consumption.Hence,the user-selected cooperative spectrum sensing algorithm based on energy consumption is proposed.First,based on the constraints of maximizing the detection probability and the false alarm probability of the system,we can iteratively find the detection threshold that maximizes the detection performance of the sensing user;then,based on the predetermined detection threshold,the energy consumption problem is transformed into a 0-1 linear programming problem,and a preference degree factor is introduced to make dynamic adjustments to achieve the purpose of saving energy as much as possible while ensuring overall performance,considered system perceived energy consumption and sensing performance Synthetically.The second is the research on fusion algorithms in cooperative spectrum sensing.Traditional hard fusion algorithms have smaller data transmission bandwidth but lower sensing performance,and soft fusion algorithms have higher sensing performance but larger data transmission bandwidth.In order to achieve a compromise in these two algorithma,this thesis proposes an improved fusion algorithm based on three thresholds.Sensing users need to make a local decision based on the three thresholds and upload the 1-bit or 2-bit decision result to the fusion center.After receiving the judgment results of each perceived user,the fusion center needs to use an improved fusion algorithm for data recovery and data fusion.Then,it is necessary to compare the fused data value with a preset threshold.Simulation and theoretical analysis show that the sensing performance of the algorithm is similar to the soft fusion algorithm,and the overall system bandwidth is up to 2Nbit(N is the number of perceived users),which is much smaller than the soft fusion algorithm and achieves the purpose of saving bandwidth.