Abstract
Opportunistic access to the radio spectrum, enabled by cognitive radios, seems to be the solution to the voracious demand for the statically assigned but highly underutilized radio spectrum. Cognitive radios, benefiting from their advanced features including adaptability and spectrum sensing, can coexist and share the spectrum with licensed radios, under the constraint that their interference remains below a manageable level. In this chapter, using tools from theory of point processes, statistical models are obtained for interference and power control strategies are proposed for interference avoidance. In addition, a cooperative framework is proposed where cognitive radios are assigned the spectrum for a portion of time as remuneration for their assistance in modifying their interference statistics and improving the capacity of primary links. Simulation and analytical results are provided to confirm the accuracy of the analytical derivations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The formal definition of the Poisson point process in a general space requires some background from measure Theory [24].
- 2.
The decision to cooperate or not to cooperate, can be either jointly made by other secondary nodes or by a centralized authority in the secondary network.
References
Schwartz M (2005) Mobile wireless communications. Cambridge University Press, Cambridge
Rappaport TS (2002) Wireless communications: principles and practice, 2nd edn. Prentice Hall, Upper Saddle River
Haykin S (2005) Cognitive radio: brain-empowered wireless communications. IEEE J Sel Areas Commun 32(2):201–220
Zhao Q, Sadler BM (2007) A survey of dynamic spectrum access. IEEE Signal Process Mag 24(3):79–89
Jabbari B, Pickholtz R, Norton M (2010) Dynamic spectrum access and management. IEEE Wirel Commun Mag 17(4):6–15
Cabric D, Mishra SM, Brodersen RW (2004) Implementation issues in spectrum sensing for cognitive radios. In: Proceedings of the Asilomar conference on signals, systems, and computers, Nov 2004, pp 772–776
Hulbert AP (2005) Spectrum sharing through beacons. In: Proceedings of the 16th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’05), Berlin, pp 989–993, Sep 2005
Ghasemi A, Sousa ES (2008) Interference aggregation in spectrum-sensing cognitive wireless networks. IEEE J Sel Top Signal Process 2(1):41–56
Babaei A, Jabbari B (2010) Interference modeling and avoidance in spectrum underlay cognitive wireless networks. In: Proceedings of ICC, May 2010, pp 1–5
Babaei A, Jabbari B (2008) Internodal distance distribution and power control for coexisting radio networks. In: Proceedings of Globecom, Dec 2008, pp 1–5
Sousa ES, Silvester JA (1990) Optimum transmission ranges in a direct-sequence spread-spectrum multihop packet radio network. IEEE J Sel Areas Commun 8(5):762–771
Haenggi M, Andrews JG, Baccelli F, Dousse O, Franceschetti M (2009) Stochastic geometry and random graphs for the analysis and design of wireless networks. IEEE J Sel Areas Commun 27(7):1029–1046
Gulati K, Evans BL, Andrews JG, Tinsley KR (2010) Statistics of co-channel interference in a field of Poisson and Poisson–Poisson clustered interferers. IEEE Trans Signal Process 58(12):6207–6222
Wang C, Wong X, Chen H, Thompson J (2009) On capacity of cognitive radio networks with average interference power constraints. IEEE Trans Wirel Commun 8(4):1620–1625
Babaei A, Agrawal P, Jabbari B (2011) Cooperative spectrum sharing for a primary network with capacity constraint. In: Proceedings of IEEE VTC-Spring
Babaei A, Agrawal P, Jabbari B (2010) Statistical shaping of interference to maximize capacity in cognitive random wireless networks. In: Proceedings of Milcom, Oct 2010, pp 714–718
Gupta P, Kumar PR (2000) The capacity of wireless networks. IEEE Trans Inf Theory 46(2):388–404
Tang J, Misra S, Xue G (2008) Joint spectrum allocation and scheduling for fair spectrum sharing in cognitive radio wireless networks. Comput Netw 52(11):2148–2158
Ilow J, Hatzinakos D (1998) Analytical alpha-stable noise modeling in a poisson field of interferers or scatterers. IEEE Trans Signal Process 46(6):1601–1611
Cox D (1970) Renewal theory. Methuen & Co., London
Diggle PJ (2003) Statistical analysis of spatial point patterns, 2nd edn. Arnold, London
Ludwig JA, Reynolds JF (1988) Statistical ecology: a primer on methods and computing. Wiley, New York
Ohser J, Mucklich F (2000) Statistical analysis of microstructures in materials science. Wiley, Chichester
Fremlin DH (2001) Measure theory. Torres Fremlin, Colchester
Daley DJ, Vere-Jones D (2003) An introduction to the theory of point processes: elementary theory and methods, vol 1. Springer, New York
Baddeley A (2007) Spatial point processes and their applications. Lecture notes in mathematics, vol 1892. Springer, Berlin, pp 1–75
Brown TC, Silverman BW, Milne RK (1981) A class of two-type point processes. Zeitschrift fur Wahrscheinlichkeitstheorie und verwandte Gebiete 58:299–308
Paloheimo JE (1972) A spatial bivariate Poisson distribution. Biometrika 59(2):489–492
Babaei A, Jabbari B (2010) Distance distribution of bivariate poisson network nodes. IEEE Commun Lett 14(9):848–850
Haenggi M (2005) On distances in uniformly random networks. IEEE Trans Inf Theory 51(10):3584–3586
Campbell N (1909) The study of discontinuous phenomena. In: Mathematica proceedings of the Cambridge Philosophy Society, vol 15, pp 117–136
Kingman J (1993) Poisson processes. Oxford University Press, Oxford
Middleton D (1976) Statistical–physical models of electromagnetic interference. U.S. Department of Commerce, Office of Telecommunications, Technical Reports
Papoulis A, Pillai SU (2002) Probability, random variables and stochastic processes, 4th edn. McGraw Hill, New York
Ihara S (1978) On the capacity of channels with additive non-Gaussian noise. Inf Control 37:34–39
Ungerboeck G (1982) Channel coding with multilevel/phase signals. IEEE Trans Inf Theory 28(1):55–67
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Babaei, A., Agrawal, P., Jabbari, B. (2012). Interference Modeling, Shaping and Avoidance in Cognitive Wireless Networks. In: Venkataraman, H., Muntean, GM. (eds) Cognitive Radio and its Application for Next Generation Cellular and Wireless Networks. Lecture Notes in Electrical Engineering, vol 116. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1827-2_14
Download citation
DOI: https://doi.org/10.1007/978-94-007-1827-2_14
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-1826-5
Online ISBN: 978-94-007-1827-2
eBook Packages: EngineeringEngineering (R0)