Spectrum Sensing Of DVB-T Signals Under High Mobility

With the rapid development and wide application of wireless communications,on the one hand, the radio spectrum becomes increasingly tense, on the other hand,the use efficiency of spectrum resource is very low, the use of exclusive wireless cannot adapt to the development of wireless communications, so cognitive radio is thedevelopment direction of future civil and military wireless communications.One of the important task of cognitive radio is spectrum sensing, becauseterrestrial wireless video broadcasting band has been used as a test band of cognitiveradio, the spectrum sensing of digital video broadcasting-terrestrial (DVB-T) hasbecame the hot research field of cognitive radio. There have been some spectrumsensing methods, such as energy detection, matching filter method and cyclostationarymethod, the detection performance of these methods are not high under high mobilityand low signal to noise ratio (SNR), it is difficult to meet the applicationrequirements under high mobility (such as vehicle communications).DVB-T signals have some unique signal characteristics, such as cyclic prefix(CP) and pilot (Pilot), we can take advantage of these features to improve thespectrum sensing performance of DVB-T signals. Firstly, this paper introduce thetime domain auto correlation method of DVB-T signals base on CP feature, thedetection performance of this method work well at high SNR, but at low SNR it isnot significantly improved. Then we introduce two algorithms base on the feature ofpilot symbols, Neyman-Pearson (NP) detection method and the maximal ratiocombining (MRC) detection method, the two methods use the feature of pilot tocalculate the accumulated distribution function, and then have spectrum sensing ofthe DVB-T signals. This algorithm based on pilot symbols improve the detectionperformance of the DVB-T signals at some extent, but not very obvious. Then, bycombining the cyclic prefix method and the pilot method to improve the algorithmfurther, we can see that the detection performance of this method work well thanthose two algorithms, and its performance is further improved at low SNR(-13dB).In order to improve the detection performance of DVB-T signals under highmobility (now the channel has a rapidly varying communication), in the end of thispaper discusses the spectrum sensing algorithm of DVB-T signals by data smoothing.Firstly we find that the correlation with the pilot sequences can be performed in thetime domain, so we introduce the time domain cross-correlation algorithm. On the basis of this algorithm, it can be observed that the correlation output contains a noiseterm (contributions from data subcarriers and white Gaussian noise). The variance ofthe noise term can be reduced by averaging the received symbols. The simulationresults show that this method of data smoothing diminish the impact of noise, andimprove the detection performance under high mobility and low SNR (-16dB).