Self-organized Clustering for Improved Interference Mitigation in White Spaces
DOI:
https://doi.org/10.26636/jtit.2017.110517Keywords:
interference mitigation, self-coexistence, self-organized, white spaces, wirelessAbstract
In this paper a collaborative coexistence mechanism for white space base stations is proposed. We look at the case where these base stations operate in geographical areas where the density of used TV channels is such that only one channel is left for broadband access. We show how with cooperative closed loop control and a clustering strategy, it is possible to find feasible power assignments that provide a flexible and stable coverage solution. The framework under which we study our proposal is based on the IEEE 802.22 standard, which provides white space guidelines for applications in broadband access or machine-to-machine communications. We propose and evaluate a self-organized, collaborative power control and design strategy to enable effective coexistence of base stations under extreme bandwidth constraints. Finally, we also portray how proposed approach positively compares against others from different wireless access technologies.
Downloads
References
[1] FCC, “Federal Communications Commission, Part 15 TV Bands Devices, Second Report and Order and Memorandum Opinion and Order”, FCC 08-260, ET Docket No. 04-186, 2008.
View in Google Scholar
[2] C. Stevenson et al., “IEEE 802.22: The first cognitive radio wireless regional area network standard”, IEEE Commun. Mag., vol. 47, no. 1, pp. 130–138, 2009.
View in Google Scholar
[3] Weightless Special Interest Working Group, “Weightless System Specification”, 2012 [Online]. Available: http://weightless.org
View in Google Scholar
[4] K. Harrison, S. Mishra, and A. Sahai, “How much white-space capacity is there?”, in Proc. IEEE Int. Symp. on New Front. in Dynam. Spectrum Access Netw. IEEE DySPAN 2010, Singapore, Singapore, 2010 (doi: 10.1109/DYSPAN.2010.5457914).
View in Google Scholar
[5] J. Aráuz and Z. Miller, “Self-coexistence in the dense case for white spaces”, in Proc. of IFIP Wireless Days WD 2012, Dublin, Ireland, 2012 (doi: 10.1109/WD.2012.6402844).
View in Google Scholar
[6] Z. Miller and J. Aráuz, “Self-coexistence with autonomous target variable selection for white space devices”, in Proc. of Inform. and Telecommun. Education and Res. Assoc. Conf. ITERA 2013, Cincinnati, OH, USA, 2013.
View in Google Scholar
[7] White Space database [Online]. Available: http://whitespaces.spectrumbridge.com/whitespaces/home.aspx (accessed: March 10, 2017).
View in Google Scholar
[8] R. Madan, S. Boyd, and S. Lall, “Fast algorithms for resource allocation in wireless cellular networks”, IEEE/ACM Trans. on Netw., vol. 18, no. 3, pp. 973–984, 2010.
View in Google Scholar
[9] S. Pillai, T. Suel, and S. Cha, “The Perron-Frobenius theorem: some of its applications”, IEEE Sig. Proces. Mag., vol. 22, no. 2, pp. 62–75, 2005.
View in Google Scholar
[10] 3GPP, “Considerations on interference coordination in heterogeneous networks”, LG Electronics, TSG RAN WG1 R1-101369, 2010.
View in Google Scholar
[11] 3GPP, “Summary of the description of candidate eICIC solutions”, CMCC, TSG-WG1 R1-104968, 2010.
View in Google Scholar
[12] M. Bennis and D. Niyato, “A Q-learning-based approach to interference avoidance in self-organized femtocell networks”, in IEEE GLOBECOM Workshops (GC Wkshps), Miami, FL, USA, 2010, pp. 706–710 (doi: 10.1109/GLOCOMW.2010.5700414).
View in Google Scholar
[13] A. Galindo-Serrano and L. Giupponi, “Distributed Q-learning for interference control in OFDMA-based femtocell networks”, in Proc. 71st IEEE Veh. Technol. Conf. VTC 2010-Spring, Taipei, Taiwan, 2010 (doi: 10.1109/VETECS.2010.5493950).
View in Google Scholar
[14] A. Serrano, L. Giupponi, and M. Dohler, “BeFEMTO’s self-organized and docitive femtocells”, in Proc. Future Network and Mobile Summit 2010 Conf., Florence, Italy, 2010, pp. 1–8.
View in Google Scholar
[15] G. P. Villardi, H. Harada, F. Kojima, and H. Yano, “Multilevel protection to broadcaster contour and its impact on TV white space availability”, IEEE Trans. on Veh. Technol., vol. 66, no. 2, pp. 1393–1407, 2017 (doi: 10.1109/TVT.2016.2566675).
View in Google Scholar
[16] S. Biswas, S. Biswas, A. Mukherjee, and M. K. Naskar, “Cooperative sensing and allocation scheme using IEEE 802.22-Standard”, in Proc. of IEEE Int. Conf. on Adv. Networks and Telecommun. Syst. ANTS 2014, New Delhi, India, 2014 (doi: 10.1109/ANTS.2014.7057246).
View in Google Scholar
[17] IEEE, “IEEE Standard for Information technology – Telecommunications and information exchange between systems, Local and metropolitan area networks, Specific requirements, Part 19: TV White Space Coexistence Methods”, IEEE Std 802.19.1-2014, 2014.
View in Google Scholar
[18] S. Filin, K. Ishizu, F. Kojima, and H. Harada, “Implementation of TV white space coexistence system based on IEEE 802.19.1 Standard”, in Proc. IEEE Conf. on Stand. for Commun. and Netw. CSCN 2015, Tokyo, Japan, 2015, pp. 206–211 (doi: 10.1109/CSCN.2015.7390445).
View in Google Scholar
[19] W. Hu, M. Gerla, G. A. Vlantis, and G. J. Pottie, “Efficient, flexible, and scalable inter-network spectrum sharing and communications in cognitive IEEE 802.22 networks”, in Proc. 1st Int. Worksh. on Cognit. Radio and Adv. Spectrum Manag., Aalborg, Denmark, 2008 (doi: 10.1109/COGART.2008.4509981).
View in Google Scholar
[20] K. Ezirim, L. Liu, P. Ji, and S. Sengupta, “Distributed and cheat-proof spectrum contention scheme for IEEE 802.22 WRAN networks”, in Proc. IEEE Wirel. Commun. and Netw. Conf. WCNC 2015, New Orleans, LA, USA, 2015, pp. 1095–1100 (doi: 10.1109/WCNC.2015.7127622).
View in Google Scholar
[21] IEEE, “IEEE Standard for Information Technology – Cognitive Wireless RAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Policies and Procedures for Operation in the TV Bands”, IEEE Std 802.22-2011, pp. 1–680, 2011.
View in Google Scholar
[22] J. MacQueen, “Some methods for classification and analysis of multivariate observations”, in Proc. 5th Berkeley Symp. on Math. Statistics and Probability, Berkeley, CA, USA, 1967, vol. 1, pp. 281–290.
View in Google Scholar
[23] R. Tibshirani, G. Walther, and T. Hastie, “Estimating the number of clusters in a dataset via the Gap statistic”, J. of the Royal Statis. Soc., vol. 63, no. 2, pp. 411–423, 2001.
View in Google Scholar
[24] J. Egli, “Radio propagation above 40 MC over irregular terrain”, Proceedings of the IRE, vol. 45, no. 10, pp. 1383–1391, 1957.
View in Google Scholar
[25] J. Seybold, Introduction to RF Propagation. Hoboken, New Jersey: Wiley, 2005, pp. 141–143.
View in Google Scholar
[26] C. Lee and H. Kang, “Cell planning with capacity expansion in mobile communications: a tabu search approach”, IEEE Trans. on Veh. Technol., vol. 49, no. 5, pp. 1678–1691, 2000.
View in Google Scholar
Downloads
Submitted
Published
Issue
Section
License
Copyright (c) 2017 Journal of Telecommunications and Information Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.
