Improving Spectrum Sensing as a Method for White Space Identification through Design Principles
DOI:
https://doi.org/10.13052/jicts2245-800X.331Keywords:
White-Fi, cooperative spectrum sensing, detection threshold, spectrum sensing principlesAbstract
Spectrum sensing’s inability to provide maximum protection to primary users operating in television white spaces summarizes the technical challenges associated with it. Building upon “WhiteNet”, a white space network management platform for campus connectivity, this paper proposes design principles that can be incorporated in a white space identification system based on a cooperative spectrum sensing model that both minimizes the probability of causing interference to primary users due to false negatives and reduces false positives thereby increasing the amount of white spaces identified. Real-world indoor measurements of a TV transmitter signal were used to evaluate the proposed principles. The results reveal the relevance of using these design principles in white space networking using the emerging White-Fi protocol.
Downloads
References
V. Gonçalves and S. Pollin. The value of sensing for TV white spaces. New Frontiers in Dynamic Spectrum Access Networks (DySPAN), 2011 IEEE Symposium on, 231–241, 2011.
L. Zhu and V. Chen and J. Malyar and S. Das and P. McCann. Protocol to Access White-Space (PAWS) Databases. 2015.
IEEE Standards Association. 802.11af – IEEE Standard for Information technology – Telecommunications and information exchange between systems – Local and metropolitan area networks - Specific requirements – Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 5: Television White Spaces (TVWS). IEEE, 2013, http://standards.ieee.org/getieee802/download/ 802.11af-2013.pdf.
IEEE Standards Association. 802.22-2011 – IEEE Standard for Information technology – Local and metropolitan area networks – Specific requirements – Part 22: Cognitive Wireless RAN Medium Access Control (MAC) and Physical Layer (PHY) specifications: Policies and procedures for operation in the TV Bands. IEEE, 2011, http://standards.ieee.org/getieee802/download/802.22-2011.pdf.
E. Pietrosemoli and M. Zennaro. TV White Spaces. A pragmatic approach. ISTB, 35–40, 2013.
Federal Communications Commission and others. Second memorandum opinion and order in the matter of unlicensed operation in the tv broadcast bands and additional spectrum for unlicensed devices below 900 Mhz and in the 3 Ghz band. 2010.
H. Urkowitz. Energy detection of unknown deterministic signals. Proceedings of the IEEE 55(4):523–531, 1967.
M. A. Abdulsattar and Z. A. Hussein. Energy Detector with Baseband Sampling for Cognitive Radio: Real-Time Implementation. Wireless Engineering and Technology, 3(04):229, 2012. Scientific Research Publishing.
T. Yücek and H. Arslan A survey of spectrum sensing algorithms for cognitive radio applications. Communications Surveys & Tutorials, IEEE, 11(1):16–130, 2009.
P. Lingeswari and K. J. Prasanna Venkatesan and V. Vijayarangan. Legacy User Detection in OFDM based Cognitive Radio. International Conference on Recent Trends in Computational Methods, Communication and Controls (ICON3C 2012), 2012. http://research.ijcaonline.org/icon3c/number7/icon3c1053.pdf.
N. Yadav and S. Rathi. A comprehensive study of spectrum sensing techniques in cognitive radio. International Journal of Advances in Engineering & Technology, 1(3):85, 2011. IAET Publishing Company.
Z. Sun. Design and Implementation of Sequence Detection Algorithms for Dynamic Spectrum Access Networks. University of Notre Dame, 2010.
L. Yin and K. Wu and S. Yin and J. Li and S. Li and L. M. Ni. Digital dividend capacity in China: A developing country’s case study. Dynamic Spectrum Access Networks (DYSPAN), 2012 IEEE International Symposium on, 121–130, 2012.
T. Zhang and N. Leng and S. Banerjee. A vehicle-based measurement framework for enhancing white space spectrum databases. Proceedings of the 20th annual international conference on Mobile computing and networking, 17–28, 2014. ACM.
G. Naik and S. Singhal and A. Kumar and A. Karandikar. Quantitative assessment of TV white space in India. Communications (NCC), 2014 Twentieth National Conference on, 1–6, 2014. IEEE.
S. M. Mishra and A. Sahai. How much white space has the FCC opened up? IEEE Communication Letters, 2010.
Y. Zeng and Y. C. Liang and A. T. Hoang and R. Zhang. A review on spectrum sensing for cognitive radio: challenges and solutions. EURASIP Journal on Advances in Signal Processing 2, 2010. Hindawi Publishing Corp.
P. G. Scholar. An overview of cognitive radio architecture. Journal of Theoretical and Applied Information Technology 41(1):2012.
J. Milanović and S. Rimac-Drlje and I. Majerski. Radio wave propagation mechanisms and empirical models for fixed wireless access systems. Tehnički vjesnik: znanstveno-stručni časopis tehničkih fakulteta Sveučilišta u Osijeku 17(1):43–52, 2010. Hrvatska znanstvena bibliografija i MZOS-Svibor.
X. Ying and J. Zhang and L. Yan and G. Zhang and M. Chen and R. Chandra. Exploring indoor white spaces in metropolises. Proceedings of the 19th Annual International Conference on Mobile Computing & Networking, 255–266, 2013. ACM.
RF Explorer: Handheld Spectrum Analyser. RF Explorer Combo Devices Specification Chart. Nuts About Nets, http://rfexplorer.com/combo-specs/.
ICASA. Draft Terestrial Broadcasting Frequency Plan 2013. Independent Communications Authority of South Africa (ICASA).
M. Lopez-Benitez and F. Casadevall Spectrum usage in cognitive radio networks: from field measurements to empirical models. IEICE Transactions on Communications 97(2):242–250, 2014. The Institute of Electronics, Information and Communication Engineers.
A. B. Bagula. Hybrid routing in next generation IP networks. Computer Communications 29(7):879–892, 2006. Elsevier.
A. B. Bagula. On Achieveing Bandwidth-Aware LSP//spl lambda/SP Multiplexing/Separation in Multi-layer Networks. Selected Areas in Communications, IEEE Journal on 25(5):987–1000, 2007.
A. B. Bagula and A. E. Krzesinski. Traffic engineering label switched paths in IP networks using a pre-planned flow optimization model. Modeling, Analysis, and Simulation of Computer and Telecommuni- cation Systems, 2001. Proceedings. Ninth International Symposium on, 70–77, 2001. IEEE.
A. B. Bagula. Modelling and implementation of QoS in wireless sensor networks: a multiconstrained traffic engineering model. EURASIP Journal on Wireless Communications and Networking, 2010. Hindawi Publishing Corp.
M. Zennaro and A. Bagula and D. Gascon and A. B. Noveleta. Planning and deploying long distance wireless sensor networks: The integration of simulation and experimentation. Ad-Hoc, Mobile and Wireless Networks 191–204, 2010. Springer.
M. Zennaro and A. Bagula and D. Gascon and A.B. Noveleta. Long distance wireless sensor networks: simulation vs reality. Proceedings of the 4th ACM Workshop on Networked Systems for Developing Regions, 2010. ACM.
M. Zennaro and A. B. Bagula. Design of a flexible and robust gateway to collect sensor data in intermittent power environments. International Journal of Sensor Networks 8(3–4):172–181, 2010. Inderscience Publishers.
A. Arcia-Moret and E. Pietrosemoli and M. Zennaro. WhispPi: White Space Monitoring with Raspberry Pi Global Information Infrastructure Symposium, 2013, 1–6, 2013. IEEE.
