Reseach On Cognitive Radio Spectrum Sensing And Access Technology Based On ECM

At the end of the 1990s,Dr.Jeseph Mitola added the function of software radio to interact with the surrounding electromagnetic environment,thus proposed the concept of "cognitive radio",which has attracted the attention of many experts and scholars all over the world.We have continued to conduct in-depth research on cognitive radio spectrum sensing,spectrum allocation,spectrum access and power control,and achieved fruitful results.However,most of these results are concentrated in the civilian sector,with the aim of improving the utilization of spectrum,while military research and application are lagging behind.This paper focuses on the spectrum sensing and spectrum allocation technology of military cognitive radios.By analyzing the characteristics and requirements of wireless communications in the confrontation mode scenario,we study the spectrum sensing technology in the complex and changing electromagnetic environment,and combine the machine learning algorithm with the spectrum.The use of regular learning,and the use of the channel to predict the state of the new spectum sensing access mechanism.Through the above technologies,we can maximize the efficient use of information in the time domain,frequency domain,and airspace,and provide strong communication guarantees for military operations on the battlefield.The main work of this article and the innovations that have been made are as follows.The innovations in spectrum sensing of military cognitive radio systems are as follows:(1)The traditional energy detection algorithm is sensitive to noise in the low signal-to-noise ratio(SNR)condition,and cyclostationary detection method have high computational complexity.In order to improve the efficiency and correctness of the perception in the battlefield environment,the algorithm based on wavelet transform and energy detection of the double threshold is proposed.The algorithm is used to determine outside of the region of double threshold by energy detection,uncertain region by wavelet detection,and adaptive adjust threshold value according to the noise uncertainty,when the channel quality is better,reduce the distance between the two threshold,otherwise increase the distance,so as to control the probability of wavelet detection.The validity of the simulation is verified,so as to ensure the availability and anti-interference of the military cognitive network spectrum.(2)The single user spectrum sensing is susceptible to the shadow effect,the multipath fading and the hidden terminal and other adverse factors,resulting in the misjudgement of the sensing result.In order to improve the performance of the system and reduce the cost of sensing,a multi-user intelligent cooperative spectrum sensing algorithm is proposed.The cognitive users according to the estimation of signal-to-noise ratio(SNR)adaptive select different sensing strategy,when the estimated SNR is higher than the selection threshold using double threshold energy detector,otherwise using cyclostationary feature detector,due to the fact that only a better perceptual strategy is implemented in a sensing period,the detection accuracy is improved under the condition of low SNR with low complexity.Finally,the distributed sensing information is processed centrally to obtain the sensing result,so that the robustness of the military wireless network can be effectively improved.(3)The battlefield information is changing rapidly.In order to improve the detection efficiency of the perceptron,a multi-user cooperative perception mechanism is proposed.This mechanism is based on geographic information to classify cognitive users(CRs)with high SNR near a CR base station into N groups according to spectrum sensing requirements.Since the reporting channel is not ideal in a real wireless environment,the transmission of local sensing results is likely to result in bit errors.Therefore,each group selects the cognitive user with the best SNR in the group as the cluster head,and the cluster head first performs the decision in the group,and then sends the judgment result to the fusion center for the final decision between the groups.For the whole sensing system,the group cooperative sensing mechanism not only reduces the perceived time of a single sensor,but also improves the decision efficiency of the fusion center,thereby improving the working efficiency of the entire sensing system and providing a reliable guarantee for the link maintenance of the communication system.(4)The frequency spectrum of strategic and tactical communication systems covers very low-frequency to ultra-high frequencies.The spectrum bandwidth perceived by a single antenna is very limited.When multi-band wide-spectrum sensing is performed,CR users can significantly increase handover delay and synchronization overhead.Therefore,a MIMO-based wideband cooperative sensing method is proposed in this paper.The related technology of MIMO is applied to the perceptron,and multiple antennas are used to sense different frequency bands in the same time slot.Using the cooperative sensing methods in(2)and(3),the switching delay and synchronization overhead in the broadband sensing are reduced,which ensures the fast acquisition of the available frequency band when the communication system is maliciously interfered.At the same time,in order to solve the coverage problem of the battlefield communication system,based on the multi-antenna sensing system,this paper proposes a multi-antenna sensing bidirectional relay limited feedback system beamforming algorithm.The algorithm is based on the statistical characteristics of the quantization error and is designed based on the minimum mean square error optimization criterion to reduce the adverse effects of quantization errors.The innovations in cognitive radio access to spectrum are as follows:According to the feasibility analysis of the actual channel environment,it can be seen that the cnahners use status will exmbit a certam regurarity.For this feature,this paper proposes a new spectrum prediction algorithm and access mechanism.The algorithm firstly uses neural network to predict the occupancy and idleness of cognitive wireless network spectrum,and then optimizes the prediction model of neural network by adopting genetic algorithm,so that the prediction accuracy rate is greatly improved and overcome the system instability caused by the use of random weights and thresholds.The cognitive user uses the optimized spectrum prediction model to learn and analyze historical spectrum sensing data,and predicts the state of the spectrum in the future.In addition,spectrum shift decisions can be made before the spectrum is interfered,thereby effectively avoiding signal interference and guaranteeing high-quality communication requirements,providing a new solution for smart spectrum access of future military communications.