ATSC DTV Signal Structure Based Spectrum Sensing Algorithm

As we all known, radio spectrum is a kind of sparse resource and it has limitedexpansibility. Traditional fixed allocation policy leads to low utility of radio spectrum.With the rapid development of telecommunication technique, people use morewireless devices in their lives and these devices play an important role than everbefore. Lots of applications cannot work if there has no network. If people want thesedevices and applications to work correctly, people need to allocate enough radiospectrum to them. In order to solve the low utility of radio spectrum and providewireless services to more devices, cognitive radio gets lots of attention since it waspresented.The definition of cognitive radio tells us that spectrum sensing which is used todetect the presence of the primary user is a fundamental task in cognitive radio. If theprimary user is present, secondary user needs to detect the presence of a primary userwith a high enough probability of detection. If the primary user is absent, secondaryuser should have a low enough probability of false alarm. So in order to make primaryusers get adequate protection and in order to enable the secondary users have morechance to access to a wireless network, spectrum sensing technique is very important.Based on this reason, this article focuses attention on spectrum sensing technique.In the second chapter, this article summarizes the advantages and disadvantagesof some existing spectrum sensing algorithm. Specially, this article presents energydetection, cyclostationary feature detection, covariance absolute value detection,covariance Frobenius norm detection, maximum-minimum eigenvalue detection andenergy minimum eigenvalue detection. These methods are all used to detect thetransmitter of primary user. Local oscillator power leakage detection is used to detectthe receiver of the primary user. In order to overcome the drawbacks of single notelocal detection, the fourth chapter introduces some cooperative spectrum sensingmethods and also analyze the advantages and disadvantages of and rule, or rule,k-out-of-m rule.This article presents a new signature based spectrum sensing method. Thismethod uses the signature of ATSC DTV. The third chapter gives the method toconduct threshold and analyze the affection of correlation operation to the probabilityof false alarm. Simulation result is presented in the end of the third chapter. Thisarticle also proves the efficiency of the threshold. Existing cooperative spectrum sensing algorithms does not consider that not alldecisions are independent. This article analyses some special cases of correlated localdecisions in cognitive radio network. This article also presents a new cooperativestrategy. If there are ample secondary users, they can be separated according to thecorrelated decisions. Then, we can limit the affection of malicious users, becausethere are plenty normal users can make the correct decisions.In conclusion, the sixth chapter summarizes this article and points out someaspects that need to overcome in the future.