Research On Spectrum Sensing And Detection Technology Over Cognitive Radio

The electromagnetic spectrum is a scarce natural resource.With the development of wireless communication technologies,the fifth and sixth generation mobile communication technologies,the contradiction of the shortage of wireless spectrum resources is increasing,and the mechanism of fixed allocation of wireless spectrum further aggravates the shortage of spectrum resources.This allocation mechanism using command mode is the root cause of low spectrum utilization in time and space.The relatively low utilization of the licensed wireless spectrum indicates that the current spectrum shortage is mainly due to the underutilization of the licensed wireless spectrum,rather than the real physical shortage of the wireless spectrum.In the context of serious wireless spectrum shortages and the urgent need for a new technology to solve the current shortage of wireless spectrum resources,cognitive radio technology has emerged.Spectrum sensing is the basic function of cognitive radio to realize its function.Based on the previous research,the cognitive radio spectrum sensing and detection method is further explored.The main research contents and innovations are as follows:1)The multi-antenna cooperative spectrum sensing and detection under generalized fading channels is studied.The closed-form expression of the average detection probability of single-antenna over k-? fading channels is derived by MGF method.The spectrum sensing performance of single-antenna over the k-?.fading channels is analyzed.On this basis,the closed-form expressions of the average detection probability of multi-antenna cooperation over generalized fading channel are derived,and the multi-antenna cooperative spectrum sensing performance under generalized fading channel is analyzed.Specifically,the spectrum sensing performance of MRC(maximum ratio combining)multi-antenna diversity over the k-? fading channels is analyzed,and the spectrum sensing performance of SLC(square law combining)multi-antenna diversity under the k-? fading channels is analyzed.The spectrum sensing performance of EGC(equal gain combining)multi-antenna diversity under ?-? fading channel is analyzed.The theoretical analysis and simulation results show that the MRC multi-antenna diversity method exhibits better detection performance than the SLC multi-antenna diversity method at the cost of high computational complexity.2)The spectrum sensing and detection of multi-user and multi-antenna cooperation is investigated,and a two-step composite cooperative spectrum sensing and detection technology is proposed.The two-step composite cooperative spectrum sensing and detection technology is based on the two-step composite design idea.The first step is to overcome the shortcomings of the classic soft data collaboration heavey network load.The cognitive users independently perform soft data cooperative spectrum sensing and obtains a one-bit local decision for the existence of the primary user.The second step is based on the first step of soft data collaboration.The cognitive users performs classical hard decision cooperative spectrum sensing.Which can achieve a compromise between hard decision collaboration and soft data collaboration,reducing network load and improving spectrum detection performance.Under Nakagami-m channel,using SLC multi-antenna soft cooperation,we derive the average detection probability expression of the two-step composite cooperative spectrum sensing,and analyze the spectrum sensing performance of the two-step composite cooperative spectrum sensing.The simulation results show that the spectrum sensing performance of the two-step composite cooperative spectrum sensing is significantly improved compared with the classical hard decision cooperative spectrum sensing performance.Furthermore,under the generalized fading channel,using MRC and SLC multi-antenna soft cooperation,we also derive the average detection probability expressions of the two-step composite cooperative spectrum sensing,and analyze the two-step composite cooperative spectrum sensing over the k-? fading channel.Simulation results also show that the spectrum sensing performance of the two-step composite cooperative spectrum sensing over the k-? fading channel is significantly improved compared with the classical hard decision cooperative spectrum sensing performance.In summary,the two-step composite cooperative spectrum sensing scheme exhibits good detection performance regardless of whether it is under the special Nakagami-m channel or the generalized k-? fading channel,which embodies the unification of the special and the general.The two-step composite cooperative spectrum sensing scheme has the advantages of hard decision fusion and soft data fusion,and is a cost-effective practical spectrum sensing scheme.3)The cognitive radio spectrum sensing and detection based on wavelet analysis and compressed sensing is researched.First,a wavelet entropy cognitive radio spectrum sensing and detection technology is proposed.The calculation expression of wavelet entropy is derived.According to the wavelet transform and wavelet packet transform theory,the wavelet entropy spectrum sensing has lower algorithm complexity than the wavelet packet entropy spectrum sensing.According to the principle of information non-aggregation,the wavelet entropy spectrum sensing has a lower detection probability than the wavelet packet entropy spectrum sensing.The theoretical analysis and simulation results show that the wavelet entropy spectrum sensing is also a cost-effective solution for practical spectrum sensing.Then,a sparse order estimation technique of sparse signal based on Kalman filtering is proposed.The sparse order of the sparse signals is an important parameter of unknown and time-varying.In the theory of compressed sensing,the sparse order of sparse signals is generally considered to be known,and the statistical maximum is taken,which is not realistic.The simulation results show that the sparse-order estimation technique of sparse signals based on Kalman filter can reliably estimate the sparse order of sparse signals.With the sparse order of the sparse signal,the reconstruction error of sparse signals can be reduced,which is to lay the foundation for further improvement of spectrum sensing performance.