Research On Spectrum And Interference Sensing In ISM Band

With the rapid development of wireless technology,the problem of scarcity of spectrum resources is becoming increasingly serious.Cognitive radio which is an effective technology to improve the utilization of spectrum resources is getting more and more attention.Spectrum sensing is a key technology in cognitive radio.This paper mainly considers the application of spectrum sensing technology in ISM band.Due to the large number of devices communicating in ISM band and the diversity of signals with different SNRs and bandwidths in the frequency spectrum,the detection performance of the conventional energy detection algorithm under these conditions is not satisfactory.Based on this,the main research contents and innovations of this paper are as follows:1.It has been proved that conventional energy detection has poor performance under low SNR environment.The derivation and simulation shows that increasing the time domain observation time can improve the detection rate of the algorithm for low SNR signals.If the total sampling time is fixed,the frequency resolution of energy detection is proportional to the time domain observation time.In this paper,an adaptive frequency resolution energy detection algorithm is proposed.The algorithm can detect the perceptual frequency band through two different frequency resolutions,which can reduce the complexity of the algorithm and improve the detection performance.2.In the adaptive frequency resolution energy detection,the detection rate of fine resolution detection starts to decline in low SNR condition.When the SNR is very low,the probability of the signal frequency point's power higher than estimated noise power is too low,which results in decreased signal detection rate.As a result of this,a multi-relevance window energy detection algorithm is proposed in this paper to improve the relevance-based energy detection which is used in fine resolution detection.By combining the advantages of different relevance window,the proposed algorithm can improve the detection rate of low SNR signals without increasing the false alarm rate.The simulation results show that the lowest SNR of signals which can be detected by the multiple relevance-based windows energy detection is 5dB lower than that of the original detection by making sure that the detection rate is above 95%.3.Communications in the ISM band may suffer a lot of interference signals of this band.By analyzing the communication systems of various signals of this band,WiFi signals are determined to be the main interference.In this paper,an interference suppression technology for WiFi signal is designed.By detection of multiple channels and perceptual analysis of WiFi interference before and after the suppressing of each channel,the target suppressed channel is found and periodical suppression frames will be sent on this channel to achieve the purpose of continuous suppression and better communication.