Impact of Mobility on the Behavior of Interference in Cellular Wireless Networks

In this study, the impact of mobility is investigated in low-speed environments such as femtocells and picocells for wireless networks. Given that there is interference on the uplink of a FDD system, this study solely focuses on how interference evolves with respect to mobility of terminals which move in a random fashion. Wiener-Levy process is used as a stochastic tool for characterizing the impact of mobility on the future behavior of interference. The results show that there is a trade-off between short and long interference observation (measurement) interval. On the one hand, choosing a short interval leads to a waste of processing power, since the interference level to be observed is not expected to deviate drastically from the previous observations. Choosing a long interval, on the other hand, increases the variance of the density of future interference level. In addition, results show that if there is more than one interference source in motion, the interference level observed has a tendency to increase in the future in low mobility environments. It is also shown that mean value of the interference level density to be observed in the future increases, whereas its standard deviation decreases with respect to the number of interference sources in motion.

[1]  Marc Necker,et al.  Local Interference Coordination in Cellular OFDMA Networks , 2007, 2007 IEEE 66th Vehicular Technology Conference.

[2]  Mahmoud Naghshineh,et al.  Channel assignment schemes for cellular mobile telecommunication systems: A comprehensive survey , 1996 .

[3]  Marc Necker.  Towards frequency reuse 1 cellular FDM/TDM systems , 2006, MSWiM '06.

[4]  Hui Liu,et al.  Downlink dynamic resource allocation for multi-cell OFDMA system , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[5]  I. Miller.  Probability, Random Variables, and Stochastic Processes , 1966 .

[6]  Jingxian Wu,et al.  Flexible lognormal sum approximation method , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[7]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[8]  Suman Das,et al.  The long term evolution towards a new 3GPP∗ air interface standard , 2007, Bell Labs Technical Journal.

[9]  Bruno O. Shubert,et al.  Random variables and stochastic processes , 1979 .

[10]  Tommy Svensson,et al.  Towards Systems Beyond 3G Based on Adaptive OFDMA Transmission , 2007, Proceedings of the IEEE.

[11]  Joachim Sachs,et al.  Radio resource management distribution in a beyond 3G multi-radio access architecture , 2004, IEEE Global Telecommunications Conference, 2004. GLOBECOM '04..

[12]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..