Research On Optimization Of Spectrum Sensing Model Based On Energy Harvesting

To solve the problem of spectrum scarcity,Professor Joseph mitola proposed the cognitive radio theory to deal with the problem of spectrum underutilization in the way of opportunity access.However,with the increase of cognitive wireless devices,the demand for energy of devices is increasing day by day,and the endurance of devices is affected,so energy harvesting has attracted the attention of researchers.Many schemes have been proposed to combine cognitive radio with energy harvesting.However,in the existing cognitive radio energy harvesting model,the spectrum sensing part involves less,most of them only use the energy detection scheme or directly set the detection probability.Therefore,in this paper,the spectrum sensing algorithm is actually added to the model,and the improved model is refined into the spectrum sensing energy harvesting model.At the same time,aiming at the problem that the energy detection scheme is greatly affected by the noise uncertainty,this paper uses the Double Threshold Energy Detection as the first step to reduce the detection error caused by the noise uncertainty,and adds the Power Spectral Ratio Averaging algorithm to reprocess the value between the double threshold.Compared with the original spectrum sensing algorithm,the improved DTED-PSRA algorithm has better robustness and detection rate.According to the different ways of energy harvesting,the harvesting mode can be divided into time division and power division.By using the multi-channel harvesting model,the power splitting model can be simplified without adding energy separation equipment.However,the multi-channel energy harvesting model has the problem of insufficient energy opportunity utilization.In the transmission time slot,the model only transmits data,and does not harvest energy when the primary user exists,which wastes these energy opportunities.In this paper,the hybrid energy harvesting model is used to supplement the energy opportunity of the data transmission timeslot of the model.In view of the energy waste of spectrum sensing under high SNR,the allocation ratio ? is added again,and the Saving-Sensing-Transmitting model is used to replace the power allocation model to avoid adding the energy separation equipment,which makes the structure too complex and maintains the advantages of the original multi-channel energy harvesting model.After improvement,this model can collect more energy for data transmission,and the maximum transmission throughput of current frame is increased by 3.51% on average.In the spectrum sensing energy harvesting model,resource allocation is one of the most important issues.Reasonable configuration of secondary users' perception time,energy harvesting time,data transmission time and transmission channel can effectively guarantee the communication quality of the secondary user and reduce the conflict with the primary user.However,with the increase of optimization parameters,the complexity of solution increases dramatically.This paper proposes an improved joint optimization algorithm: alternating direction optimization-half search-golden section search algorithm.Compared with the exhaustive method or the original alternating direction optimization algorithm,the algorithm reduces the number of operations,greatly improves the efficiency of operation,ensures that the detection rate and false alarm rate meet the constraints,reduces the conflict rate of the main user,and is a reasonable sub optimal solution search algorithm.