Email this article 
Open Access
Subscription or Fee Access
Mathematical Analysis of Interference Issues and Study of Path Loss, Fading and Shadowing Effects on Cognitive Radio Networks
Abstract
Handling interference in wireless communication system is a challenging task. This paper aims about mathematical analysis of interference in general and also in cognitive radio networks. This paper concentrates on various sources of interferences such as path loss, fading and shadowing. Interference system model was created by considering spatial distribution of nodes, wave propagation characteristics and mobility of the interferers. Interference from active set of nodes and aggregate interference was analysed mathematically. Finally, interference in cognitive radio network was analysed under different circumstances. Simulation results showed that the outage probability of secondary user to sense the transmission between primary transmitter and receiver with respect to path loss, fading and shadowing.
Keywords
References
A. J. Viterbi and I. M. Jacobs, advances in coding and modulation for non-coherent channels affected by fading, partial band, and multiple-access interference in Advances in Communication Systems: Theory and Applications, vol. 4. New York: Academic, 1975, 279–308.
I. M. I. Habbab, M. Kavehrad, and C. E. W. Sundberg, ALOHA with capture over slow and fast fading radio channels with coding and diversity,[ IEEE J. Sel. Areas Commun., vol. 7, pp. 79–88, Jan. 1989.
D. Middleton, Non-Gaussian noise models in signal processing for telecommunications: New methods and results for class A and class B noise models,[ IEEE Trans. Inf. Theory, vol. 45, no. 4, pp. 1129–1149, May 1999.
G. V. Trunk and S. F. George, detection of targets in non-Gaussian sea clutter,[ IEEE Trans. Aerosp. Electron. Syst., vol. 6, no. 5, pp. 620–628, Sep. 1970.
G. V. Trunk, Further results on the detection of targets in non-Gaussian sea clutter,[ IEEE Trans. Aerosp. Electron. Syst., vol. 7, pp. 553–556, May 1971.
M. Shao and C. Nikias, Signal processing with fractional lower order moments: Stable processes and their applications, Proc. IEEE, vol. 81, no. 7, pp. 986–1010, 1993.
C. L. Nikias and M. Shao, Signal Processing With Alpha-Stable Distributions and Applications. New York: Wiley-Interscience, 1995.
W. Feller, An Introduction to Probability Theory and Its Applications, vol. 2. New York: Wiley, 1971.
S. A. Kassam, Signal Detection in Non-Gaussian Noise. New York: Springer, 1988.
E. J. Wegman, S. C. Schwartz, and J. B. Thomas, Topics in Non-Gaussian Signal Processing. New York: Springer, 1989.
M. Chiani, BAnalytical distribution of linearly modulated cochannel interferers,[ IEEE Trans. Commun., vol. 45, pp. 73–79, Jan. 1997.
A. Giorgetti and M. Chiani, Binfluence of fading on the Gaussian approximation for BPSK and QPSK with asynchronous cochannel interference,[ IEEE Trans. Wireless Commun., vol. 4, pp. 384–389, 2005.
B. Hu and N. C. Beaulieu, Baccurate evaluation of multiple access performance in TH-PPM and TH-BPSK UWB systems,[ IEEE Trans. Commun., vol. 52,pp. 1758–1766, Oct. 2004.
P. C. Pinto, A. Giorgetti, and M. Z. Win, BA stochastic geometry approach to coexistence in heterogeneous wireless networks,[ IEEE J. Sel. Areas Commun., 2008, submitted for publication.
G. Samoradnitsky and M. Taqqu, Stable Non-Gaussian Random Processes. London, U.K.: Chapman and Hall, 1994.
M. McHenry, BNSF Spectrum Occupancy Measurements Project Summary,[ Shared Spectrum Company, 2005.
J. I. Mitola and G. Q. J. Maguire, Bcognitive radio: Making software radios more personal,[ IEEE Pers. Commun., vol. 6, pp. 13–18, Aug. 1999.
S. E. Heath, BApplications of the Poisson model to wireless telephony and to cosmology,[ Ph.D. dissertation, Rutgers Univ., New Brunswick, NJ, Mar. 2004.
J. Abate and W. Whitt, BThe Fourier-series method for inverting transforms of probability distributions,[ Queueing Syst., vol. 10, pp. 5 88, 1992.
M. Abramowitz and I. A. Stegun, Handbook of Mathematical Functions. New York: Dover, 1970.
P. C. Pinto and M. Z. Win, Bthroughput in wireless packet networks: A unifying framework, Massachusetts Institute of Technology, Laboratory for Information & Decision Systems (LIDS) Internal Report, Feb. 2009.
W. Suwansantisuk, M. Z. Win, and L. A. Shepp, BOn the performance of wide-bandwidth signal acquisition in dense multipath channels,[ IEEE Trans. Veh. Technol. (Special Section on Ultra-Wideband Wireless CommunicationsVA New Horizon), vol. 54, pp. 1584–1594, Sep. 2005.
S. Haykin, BCognitive radio: Brain-empowered wireless communications,[ IEEE J. Sel. Areas Commun., vol. 23, pp. 201–220, Feb. 2005.
M. Chiani, A. Giorgetti, and G. Liva, Bultra wide bandwidth communications towards cognitive radio,[ in Proc. EMC Eur. Workshop 2005VElectromagn. Comp. Wireless Syst., Rome, Italy, Sep. 2005, pp. 114–117.
A. Giorgetti, M. Chiani, and D. Dardari, BCoexistence issues in cognitive radios based on ultra-wide bandwidth systems,[ in Proc. IEEE Int. Conf. on Cognitive Radio Oriented Wireless Networks and Commun., Mykonos, Greece, Jun. 2006.
Seetaiah Kilaru, Y Ashwini Prasad, K Sai kiran, N V Sarath Chandra published “Design and Analysis of Heterogenious networks” International Journal of Applied Engineering Research (IJAER), ISSN 0973-4562 Volume 9, Number 17 (2014) pp. 3197-3204
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.