Spatial-temporal spectrum hole discovery: a hybrid spectrum sensing and geolocation database framework

Science China Press., Co. Ltd. - Tập 59 - Trang 1896-1902 - 2014
Jinlong Wang1, Guoru Ding1, Qihui Wu1, Liang Shen1, Fei Song1
1College of Communications Engineering, PLA University of Science and Technology, Nanjing, China

Tóm tắt

A hybrid spectrum sensing and geolocation database framework is proposed to tackle the discovery of spatial-temporal spectrum hole in cognitive radio networks. We first analyze the advantages and disadvantages of spectrum sensing-based and geolocation database-based approaches respectively, which motivate us to further propose a hybrid protocol framework by effectively integrating the benefits of both spectrum sensing and geolocation database. Specifically, in the proposed hybrid approach, the goal is to maximize the utilization of spatial-temporal spectrum hole while satisfying the protection constraints for the primary users. Analytical and numerical results demonstrate the superior performance of the proposed hybrid approach over the existing spectrum sensing only and geolocation database only approaches, in terms of interference-free throughput. This article serves as a fundamental framework for advancing the design of hybrid approaches for spatial-temporal spectrum hole discovery.

Tài liệu tham khảo

Haykin S (2005) Cognitive radio: brain-empowered wireless communications. IEEE J Sel Areas Commun 23:201–220 Zhang P (2012) In the development of wireless cognitive science. Chin Sci Bull 57:3661–3739 Wu QH, Ding GR, Wang JL et al (2012) Consensus-based decentralized clustering for cooperative spectrum sensing in cognitive radio networks. Chin Sci Bull 57:3677–3683 Tandra R, Mishra SM, Sahai A (2009) What is a spectrum hole and what does it take to recognize one. Proc IEEE 97:824–848 Yucek T, Arslan H (2009) A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Commun Surveys Tut 11:116–130 Ding GR, Wu QH, Song F et al (2012) Decentralized sensor selection for cooperative spectrum sensing using unsupervised learning. Paper presented at 2012 International Conference on Communications (ICC), Ottawa, 6–10 June 2012 Ding GR, Wu QH, Yao YD et al (2013) Kernel-based learning for statistical signal processing in cognitive radio networks: Theoretical foundations, example applications, and future directions. IEEE Signal Process Mag 30:126–136 Murty R, Chandra R, Moscibroda T et al (2012) SenseLess: a database-driven white spaces network. IEEE Trans Mobile Comput 11:189–203 Karimi HR (2012) Geolocation databases for white space devices in the UHF TV bands: specification of maximum permitted emission levels. Paper presented at 2011 IEEE Symposium on new frontiers in dynamic spectrum access networks (DySPAN), Aachen, 3–6 May 2011 Dimitris M, Georgios G, Anastasios K (2012) Quantifying TV white space capacity: a geolocation-based approach. IEEE Commun Mag 50:145–152 Wang JF, Monisha G, Kiran C (2011) Emerging cognitive radio applications: a survey. IEEE Commun Mag 49:74–81 Kang KM, Park JC, Cho SI et al (2012) Deployment and coverage of cognitive radio networks in TV white space. IEEE Commun Mag 50:88–94 Shellhammer SJ (2009) A comparison of geo-location and spectrum sensing in cognitive radio. Paper presented at 18th internatonal conference on computer communications and networks (ICCCN), San Francisco, 2–6 Aug 2009 Goncalves V, Pollin S (2011) The value of sensing for TV white spaces. Paper presented at 2011 IEEE symposium on new frontiers in dynamic spectrum access networks (DySPAN), Aachen, 3–6 May 2011 FCC (2011) Unlicensed operation in the TV broadcast bands and additional spectrum for unlicensed devices below 900 MHz and in the 3 GHz band. http://www.fcc.gov/document/unlicensed-operation-tv-broadcast-bands-additional-spectrum-unlicensed-devices-below-900-mh. Accessed 28 Aug 2013 Ofcom (2010) Implementing geolocation-ofcom proposals on how to successfully launch white space technology and how new devices will be made available to consumers without the need for a license. http://stakeholders.ofcom.org.uk/consultations/geolocation/. Accessed 28 Aug 2013 Stevenson C, Chouinard G, Lei Z et al (2009) IEEE 802.22: the first cognitive radio wireless aerial area network standard. IEEE Commun Mag 47:130–138 Tandra R, Sahai A (2008) SNR walls for signal detection. IEEE J Sel Topics Signal Process 2:4–17 Quan Z, Cui S, Sayed AH (2008) Optimal linear cooperation for spectrum sensing in cognitive radio networks. IEEE J Sel Topics Signal Process 2:28–40 Lin Y, Liu K, Hsieh H (2012) On using interference-aware spectrum sensing for dynamic spectrum access in cognitive radio networks. IEEE Trans Mobile Comput 12:461–474 Tandra R, Sahai A, Veeravalli VV (2011) Unified space-time metrics to evaluate spectrum sensing. IEEE Commun Mag 49:54–61 Han WJ, Li JD, Liu Q et al (2011) Spatial false alarms in cognitive radio. IEEE Commun Lett 15:518–520 Wu QH, Ding GR, Wang JL et al (2013) Spatial-temporal opportunity detection in spectrum-heterogeneous cognitive radio networks: two dimensional sensing. IEEE Trans Wireless Commun 12:516–526 Zou YL, Yao YD, Zheng BY (2010) Outage probability analysis of cognitive transmissions: impact of spectrum sensing overhead. IEEE Trans Wireless Commun 9:2676–2688 Harrison K, Mishra S M, Sahai A (2010) How much white-space capacity is there. Paper presented at 2010 IEEE symposium on new frontiers in dynamic spectrum access networks (DySPAN), Singapore, 6–9 April 2010