Title :
Separating the wheat from the chaff: Sensing wireless microphones in TVWS
Author :
Huanhuan Sun ; TaoTao Zhang ; Wenyi Zhang
Author_Institution :
Univ. of Sci. & Technol. of China, Hefei, China
Abstract :
The inability for most existing detection methods to effectively distinguish between a wireless microphone signal and a sinusoidal continuous wave (CW) interference has led to an excessively high false alarm rate and thus severely limited the utility of sensing-based cognitive transmission in the TV white space (TVWS) spectrum. Two potential solutions are proposed, in which the first solution focuses on signal´s periodogram and formulates the decision model as an one-sided test based on Kullback-Leibler distance statistics, and the second solution proposes an augmented spectral correlation function (SCF) and exploits the fact that wireless microphone signal and CW exhibit different augmented SCFs. Both solutions are validated by simulation and experimental tests, shown to be capable of reliably sensing wireless microphone signals in the presence of strong noise and excessive CW interference.
Keywords :
cognitive radio; correlation theory; digital television; interference suppression; microphones; radio equipment; radio spectrum management; signal detection; spectral analysis; statistical analysis; CW interference; Kullback-Leibler distance statistics; TV white space; TVWS spectrum; augmented SCF; decision model; false alarm rate; sensing-based cognitive transmission; signal periodogram; sinusoidal continuous wave; spectral correlation function; wireless microphone signal detection; Ad hoc networks; Frequency modulation; Interference; Microphones; Sensors; Wireless communication; Wireless sensor networks;
Conference_Titel :
Dynamic Spectrum Access Networks (DYSPAN), 2012 IEEE International Symposium on
Conference_Location :
Bellevue, WA
Print_ISBN :
978-1-4673-4447-0
Electronic_ISBN :
978-1-4673-4446-3
DOI :
10.1109/DYSPAN.2012.6478145