Research On Optimization Model Of Energy Comsumption Of Spectrum Sensing In IoT

With the development of information technology,the existing spectrum resource has been unable to meet the spectrum needs of massive networked equipments.There are two main reasons for this result.On the one hand,the spectrum resources are limited;on the other hand,the low efficiency of spectrum resources is caused by improper utilization of spectrum resources.The Internet of Things(IoT)is a major change in the history of the development of information and communication.The number of devices in the IoT is increasing rapidly,so the situation of spectrum shortage is more serious.Cognitive radio is an intelligent spectrum sharing technology.It can dynamically sense and learn the surrounding radio spectrum,find the idle spectrum,and adjust the system parameters accordingly so that the idle spectrum can be utilized.Thus,the limited spectrum resources are used more efficiently.Cognitive IoT is a new concept which combines cognitive radio technology with the function of IoT devices.The application of cognitive radio technology in the IoT to improve the efficiency of spectrum utilization is currently a major research hotspot.Spectrum sensing is the key foundation and core technology of cognitive radio.In this thesis,the optimization of multi-user cooperative spectrum sensing technology and the use of spectrum sensing technology in the IoT are deeply studied.In order to solve the problem of error code in transmission channel,this thesis proposes a method combining deletion strategy to avoid unnecessary information transmission,which can also improve the detection probability.In view of the difference and reliability of cognitive devices in cooperative spectrum sensing,the algorithm introduces a scheme based on trustworthiness to assign different weights to cognitive devices.A cooperative spectrum sensing algorithm for cognitive IoT is proposed,which uses radio environment map to endow cognitive devices with different degrees of trustworthiness.This method can avoid the difficulty of calculation caused by the complexity of SNR in real-time detection.Simulation results show that the proposed algorithm can improve the detection performance.The energy consumption optimization model for spectrum sensing process in cognitive IoT is also studied in this thesis.Using Matlab as programming simulation tool,the multi-objective optimization calculation of the model is carried out on the premise of satisfying the reasonable spectrum sensing effect.Then the number of secondary users to optimize the energy efficiency of the system is calculated.The simulation results of Matlab show that within the parameters set in this thesis,there is an optimal number of secondary users to achieve the highest energy efficiency of the system.When the constraint conditions are more and more strict,the number of optimal subusers is larger.The model can effectively reduce energy consumption and have high performance-price ratio under the premise of satisfying the detection probability and false-alarm probability of the system.