The Community for Technology Leaders
RSS Icon
Issue No.12 - Dec. (2012 vol.11)
pp: 2109-2120
Udo Schilcher , University of Klagenfurt, Klagenfurt
Christian Bettstetter , University of Klagenfurt Lakeside Labs, Klagenfurt Klagenfurt
Günther Brandner , University of Klagenfurt, Klagenfurt
The temporal correlation of interference is a key performance factor of several technologies and protocols for wireless communications. A comprehensive understanding of interference correlation is especially important in the design of diversity schemes, whose performance can severely degrade in case of highly correlated interference. Taking into account three sources of correlation—node locations, channel, and traffic—and using common modeling assumptions—random homogeneous node positions, Rayleigh block fading, and slotted ALOHA traffic—we derive closed-form expressions and calculation rules for the correlation coefficient of the overall interference power received at a certain point in space. Plots give an intuitive understanding as to how model parameters influence the interference correlation.
Fading channels, Interference, Rayleigh channels, Wireless networks, Random variables, Wireless communication, time diversity, Wireless networks, interference, correlation, Rayleigh fading, spatial stochastics
Udo Schilcher, Christian Bettstetter, Günther Brandner, "Temporal Correlation of Interference in Wireless Networks with Rayleigh Block Fading", IEEE Transactions on Mobile Computing, vol.11, no. 12, pp. 2109-2120, Dec. 2012, doi:10.1109/TMC.2011.244
[1] M. Zorzi, R. Rao, and L. Milstein, “ARQ Error Control for Fading Mobile Radio Channels,” IEEE Trans. Vehicular Technology, vol. 46, no. 2, pp. 445-455, May 1997.
[2] D. Costello, J. Hagenauer, H. Imai, and S. Wicker, “Applications of Error-Control Coding,” IEEE Trans. Information Theory, vol. 44, no. 6, pp. 2531-2560, Oct. 1998.
[3] S. Alamouti, “A Simple Transmit Diversity Technique for Wireless Communications,” IEEE J. Selected Areas Comm., vol. 16, no. 8, pp. 1451-1458, Oct. 1998.
[4] J. Laneman, D. Tse, and G. Wornell, “Cooperative Diversity in Wireless Networks: Efficient Protocols and Outage Behavior,” IEEE Trans. Information Theory, vol. 50, no. 12, pp. 3062-3080, Dec. 2004.
[5] X. Liu, E. Chong, and N. Shroff, “Opportunistic Transmission Scheduling with Resource-Sharing Constraints in Wireless Networks,” IEEE J. Selected Areas Comm., vol. 19, no. 10, pp. 2053-2064, Oct. 2001.
[6] G. Stüber, Principles of Mobile Communication, second ed. Springer, 2000.
[7] T. Feng and T. Field, “Statistical Analysis of Mobile Radio Reception: An Extension of Clarke's Model,” IEEE Trans. Comm., vol. 56, no. 12, pp. 2007-2012, Dec. 2008.
[8] L. Ahumada, R. Feick, R. Valenzuela, and C. Morales, “Measurement and Characterization of the Temporal Behavior of Fixed Wireless Links,” IEEE Trans. Vehicular Technology, vol. 54, no. 6, pp. 1913-1922, Nov. 2005.
[9] M. Haenggi, “Outage, Local Throughput, and Capacity of Random Wireless Networks,” IEEE Trans. Wireless Comm., vol. 8, no. 8, pp. 4350-4359, Aug. 2009.
[10] R. Ganti and M. Haenggi, “Spatial and Temporal Correlation of the Interference in ALOHA Ad Hoc Networks,” IEEE Comm. Letters, vol. 13, no. 9, pp. 631-633, Sept. 2009.
[11] M. Haenggi and R. Ganti, Interference in Large Wireless Networks, 2009.
[12] A. Papoulis and S. Pillai, Probability, Random Variables and Stochastic Processes, fourth ed. McGraw-Hill, 2002.
[13] M. Schwartz, Mobile Wireless Communications. Cambridge Univ., 2005.
[14] A. Goldsmith, Wireless Communications. Cambridge Univ., 2005.
[15] L. Ozarow, S. Shamai, and A. Wyner, “Information Theoretic Considerations for Cellular Mobile Radio,” IEEE Trans. Vehicular Technology, vol. 43, no. 2, pp. 359-378, May 1994.
[16] R. Knopp and P. Humblet, “On Coding for Block Fading Channels,” IEEE Trans. Information Theory, vol. 46, no. 1, pp. 189-205, Jan. 2000.
[17] N. Abramson, “The ALOHA System: Another Alternative for Computer Communication,” Proc. Fall Joint Comput. Conf. (AFIPS), vol. 37, pp. 281-285, Nov. 1970.
[18] P. Rickenbach, S. Schmid, R. Wattenhofer, and A. Zollinger, “A Robust Interference Model for Wireless Ad-Hoc Networks,” Proc. IEEE 19th Int'l Parallel Distribution Processing Symp., Apr. 2005.
[19] O. Dousse, F. Baccelli, and P. Thiran, “Impact of Interferences on Connectivity in Ad Hoc Networks,” IEEE/ACM Trans. Networking, vol. 13, no. 2, pp. 425-436, Apr. 2005.
[20] K. Jain, J. Padhye, V. Padmanabhan, and L. Qiu, “Impact of Interference on Multihop Wireless Network Performance,” Proc. ACM MobiCom, Sept. 2003.
[21] M. Win, P. Pinto, and L. Shepp, “A Mathematical Theory of Network Interference and Its Applications,” Proc. IEEE, vol. 97, no. 2, pp. 205-230, Feb. 2009.
[22] P. Pinto, A. Giorgetti, M. Win, and M. Chiani, “A Stochastic Geometry Approach to Coexistence in Heterogeneous Wireless Networks,” IEEE J. Selected Areas Comm., vol. 27, no. 7, pp. 1268-1282, Sept. 2009.
[23] T. Zhu, Z. Zhong, T. He, and Z.-L. Zhang, “Exploring Link Correlation for Efficient Flooding in Wireless Sensor Networks,” Proc. USENIX Symp. Networked System Design Implementation, Apr. 2010.
[24] K. Srinivasan, M. Jain, J.I. Choi, T. Azim, E.S. Kim, P. Levis, and B. Krishnamachari, “The $\kappa$ Factor: Inferring Protocol Performance Using Inter-Link Reception Correlation,” Proc. ACM MobiCom, Sept. 2010.
152 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool