On the Spatial Predictability of Communication Channels

In this paper, we are interested in fundamentally understanding the spatial predictability of wireless channels. We propose a probabilistic channel prediction framework for predicting the spatial variations of a wireless channel, based on a small number of measurements. By using this framework, we then develop a mathematical foundation for understanding the spatial predictability of wireless channels. More specifically, we characterize the impact of different environments, in terms of their underlying parameters, on wireless channel predictability. We furthermore show how sampling positions can be optimized to improve the prediction quality. Finally, we show the performance of the proposed framework in predicting (and justifying the predictability of) the spatial variations of real channels, using several measurements in our building.

[1]  Jie Lin,et al.  Coordination of groups of mobile autonomous agents using nearest neighbor rules , 2003, IEEE Trans. Autom. Control..

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

[3]  N. Cressie.  Kriging Nonstationary Data , 1986 .

[4]  Wei Wang,et al.  Coverage for target localization in wireless sensor networks , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[5]  Mike Rees,et al.  5. Statistics for Spatial Data , 1993 .

[6]  Tatsuya Suda,et al.  Differentiated Surveillance for Static and Random Mobile Sensor Networks , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[7]  A. Urie.  Errors in estimating local average power of multipath signals , 1991 .

[8]  Yasamin Mostofi,et al.  A Comprehensive Overview and Characterization of Wireless Channels for Networked Robotic and Control Systems , 2011, J. Robotics.

[9]  Mehrzad Malmirchegini,et al.  Estimation of communication signal strength in robotic networks , 2010, 2010 IEEE International Conference on Robotics and Automation.

[10]  Yasamin Mostofi,et al.  Communication-Aware Motion Planning in Mobile Networks , 2011, IEEE Transactions on Automatic Control.

[11]  Clifford A. Shaffer,et al.  In-building wideband multipath characteristics at 2.5 and 60 GHz , 2002, Proceedings IEEE 56th Vehicular Technology Conference.

[12]  Kate A. Remley,et al.  Improving the accuracy of ray-tracing techniques for indoor propagation modeling , 2000, IEEE Trans. Veh. Technol..

[13]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[14]  Abbas Jamalipour,et al.  Wireless communications , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[15]  Claude Oestges,et al.  Experimental Characterization and Modeling of Outdoor-to-Indoor and Indoor-to-Indoor Distributed Channels , 2010, IEEE Transactions on Vehicular Technology.

[16]  D. Akerberg,et al.  Properties of a TDMA pico cellular office communication system , 1989, IEEE 39th Vehicular Technology Conference.

[17]  I. J. Schoenberg,et al.  Metric spaces and positive definite functions , 1938 .

[18]  H. Hashemi,et al.  The indoor radio propagation channel , 1993, Proc. IEEE.

[19]  E. Kreyszig.  Introductory Functional Analysis With Applications , 1978 .

[20]  J.E. Mazo,et al.  Digital communications , 1985, Proceedings of the IEEE.

[21]  Yasamin Mostofi,et al.  Characterization and modeling of wireless channels for networked robotic and control systems - a comprehensive overview , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[22]  W. Scanlon,et al.  Higher Order Statistics for Lognormal Small-Scale Fading in Mobile Radio Channels , 2007, IEEE Antennas and Wireless Propagation Letters.

[23]  W. C. Jakes,et al.  Microwave Mobile Communications , 1974 .

[24]  Jon C. Dattorro,et al.  Convex Optimization & Euclidean Distance Geometry , 2004 .

[25]  William M Smith,et al.  Urban propagation modeling for wireless systems , 2004 .

[26]  Ainslie,et al.  CORRELATION MODEL FOR SHADOW FADING IN MOBILE RADIO SYSTEMS , 2004 .

[27]  Robert Haining,et al.  Statistics for spatial data: by Noel Cressie, 1991, John Wiley & Sons, New York, 900 p., ISBN 0-471-84336-9, US $89.95 , 1993 .