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Telfor Journal
2016, vol. 8, br. 2, str. 93-97
jezik rada: engleski
vrsta rada: neklasifikovan

Interference estimation in wireless mobile random waypoint networks
(naslov ne postoji na srpskom)
Instituto de Telecomunicações - IT, Av. Rovisco Pais, Lisboa - Portugal + CTS, UNINOVA, Dep.º de Eng.ª Electrotécnica, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, Caparica, Portugal



This work was partially supported by the Portuguese Science and Technology Foundation (FCT/MEC) under the grantSFRH/BD/108525/2015


(ne postoji na srpskom)
It is well known that the stochastic nature of the interference deeply impacts the performance of emerging and future wireless communication systems. In this work we consider an ad hoc network where the nodes move according to the Random Waypoint mobility model. Assuming a timevarying wireless channel due to slow and fast fading and, considering the dynamic path loss due to the mobility of the nodes, we start by characterizing the interference distribution caused to a receiver by the moving interferers located in a ring. For this purpose, we consider a receiver located at the center of the simulated region. Based on the distribution of the interference's power, we evaluate different methodologies to estimate the power of the interference in real-time. Results achieved with a Maximum Log-likelihood estimator (MLE) and a Probability Weighted Moments (PWM) estimator are compared. The accuracy of the results achieved with the proposed methodologies in several simulations show that they may used as an effective tool of interference power estimation in future wireless communication systems, exhibiting high accuracy even when the number of samples is low.

Ključne reči

interference estimation; ad hoc networks; mobility


Abdi, A., Kaveh, M. (1999) On the utility of gamma PDF in modeling shadow fading (slow fading). u: IEEE Vehicular Technology Conference, Houston, pp. 2308-2312
Al-Ahmadi, S., Yanikomeroglu, H. (2010) On the approximation of the generalized-Κ distribution by a gamma distribution for modeling composite fading channels. IEEE Transactions on Wireless Communications, 9(2): 706-713
Bai, Z., i dr. (2012) Interference estimation for multi-layer MU-MIMO transmission in LTE-advanced systems. u: IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC), Sydney, NSW, pp. 1622-1626
Bettstetter, C., Resta, G., Santi, P. (2003) The node distribution of the random waypoint mobility model for wireless ad hoc networks. IEEE Transactions on Mobile Computing, 2(3): 257-269
Chiani, M. (1997) Analytical distribution of linearly modulated cochannel interferers. IEEE Transactions on Communications, 45(1): 73-79
Goel, S., Negi, R. (2008) Guaranteeing Secrecy using Artificial Noise. IEEE Transactions on Wireless Communications, 7(6): 2180-2189
Gong, Z., Haenggi, M. (2014) Interference and Outage in Mobile Random Networks: Expectation, Distribution, and Correlation. IEEE Transactions on Mobile Computing, 13(2): 337-349
Greenwood, J. A., Landwehr, J. M., Matalas, N. C., Wallis, J. R. (1979) Probability weighted moments: Definition and relation to parameters of several distributions expressable in inverse form. Water Resources Research, 15(5): 1049-1054
Hosking, J. R. M., Wallis, J. R., Wood, E. F. (1985) Estimation of the Generalized Extreme-Value Distribution by the Method of Probability-Weighted Moments. Technometrics, 27(3): 251-261
Irio, L., Oliveira, R. (2015) Interference estimation in wireless mobile random waypoint networks. u: Telecommunications Forum Telfor (TELFOR), 2015 23rd, Belgrade, pp. 161-164
Irio, L., Oliveira, R., Bernardo, L. (2015) Aggregate Interference in Random Waypoint Mobile Networks. IEEE Communications Letters, 19(6): 1021-1024
Johnson, D.B., Maltz, D.A. (1996) Dynamic source routing in Ad Hoc wireless networks. u: Mobile Computing, Springer, pp. 153-181
Landwehr, J. M., Matalas, N. C., Wallis, J. R. (1979) Probability weighted moments compared with some traditional techniques in estimating Gumbel Parameters and quantiles. Water Resources Research, 15(5): 1055-1064
Lee, W., Cho, D.H. (2012) Adaptive interference estimation for directional transmission. u: IEEE Consumer Communications and Networking Conference (CCNC), Las Vegas, NV, pp. 350-351
Pahlavan, K., Li, X., Makela, J.P. (2002) Indoor geolocation science and technology. IEEE Communications Magazine, 40(2): 112-118
Rabbachin, A., Quek, T.Q.S., Shin, H., Win, M.Z. (2011) Cognitive Network Interference. IEEE Journal on Selected Areas in Communications, 29(2): 480-493
Shikh-Bahaei, M.R., Aghvami, A.H. (1997) An interference estimation method for interference cancellation in CDMA systems. u: CDMA Techniques and Applications for Third Generation Mobile Systems (Digest No. 1997/129), IEE Colloquium on, London, pp. 4/1-4/6
Win, M.Z., Pinto, P.C., Shepp, L.A. (2009) A Mathematical Theory of Network Interference and Its Applications. Proceedings of the IEEE, 97(2): 205-230
Yarkan, S., Maaref, A., Teo, K.H., Arslan, H. (2008) Impact of mobility on the behavior of interference in cellular wireless networks. u: IEEE GLOBECOM 2008, New Orleans, pp. 1-5
Zhang, X.M., Wu, L., Zhang, Y., Sung, D.K. (2013) Interference dynamics in MANETs with a random direction node mobility model. u: IEEE Wireless Communications and Networking Conference (WCNC), Shanghai, pp. 3788-3793