Spectrum occupancy measurements and analysis methods on the 2.45 GHz ISM band

We performed spectrum occupancy measurements on the 2.45 GHz Industrial, Scientific and Medical (ISM) band in the area of Oulu, Finland. The comprehensive measurement campaign consisted of eight different locations and ten different measurement occasions, each with approximately one week of continuous spectrum monitoring. The measurement data is analyzed from the viewpoint of fitting new systems on 2.45 GHz ISM band, rather than pure duty cycle analysis. To aid accurate analysis, we propose Transmission Encapsulation based on the Connected Component Labeling (TECCL). This novel method searches for the clusters of connected signal components in the time-frequency grid and provides the extreme dimensions of each cluster for the subsequent analysis. It is shown that the TECCL does not cause a significant increase in the false alarm probability. Our results indicate that new systems with cognitive radio capabilities could be introduced to 2.45 GHz ISM band.

[1]  Dominique Noguet,et al.  A hardware demonstrator of a cognitive Radio system using temporal opportunities , 2009, 2009 4th International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[2]  Hiroyuki Morikawa,et al.  Distributed spectrum sensing utilizing heterogeneous wireless devices and measurement equipment , 2011, 2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

[3]  Rafael Cepeda,et al.  Long-term measurements of spectrum occupancy characteristics , 2011, 2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

[4]  Luigi di Stefano,et al.  A simple and efficient connected components labeling algorithm , 1999, Proceedings 10th International Conference on Image Analysis and Processing.

[5]  Barbara van Schewick,et al.  A Real Time Cognitive Radio Testbed for Physical and Network level Experiments , 2005 .

[6]  Tanim M. Taher,et al.  Long-term spectral occupancy findings in Chicago , 2011, 2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

[7]  T. Clarkson,et al.  Occupancy analysis of the 2.4GHz ISM band : WLAN systems and interworking , 2004 .

[8]  Fernando Casadevall,et al.  On the spectrum occupancy perception of cognitive radio terminals in realistic scenarios , 2010, 2010 2nd International Workshop on Cognitive Information Processing.

[9]  Luca Stabellini Quantifying and Modeling Spectrum Opportunities in a Real Wireless Environment , 2010, 2010 IEEE Wireless Communication and Networking Conference.

[10]  Janne J. Lehtomäki,et al.  Adaptive FCME-based threshold setting for energy detectors , 2011, CogART '11.

[11]  Xianming Qing,et al.  Spectrum Survey in Singapore: Occupancy Measurements and Analyses , 2008, 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008).

[12]  Janne J. Lehtomäki,et al.  Energy Detection Based Estimation of Channel Occupancy Rate with Adaptive Noise Estimation , 2012, IEICE Trans. Commun..

[13]  H. Saarnisaari,et al.  Double-threshold based narrowband signal extraction , 2005, 2005 IEEE 61st Vehicular Technology Conference.

[14]  Mohamed-Slim Alouini,et al.  Empirical results for wideband multidimensional spectrum usage , 2009, 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications.