Further Validation of an Electromagnetic Macro Model for Analysis of Propagation Path Loss in Cellular Networks Using Measured Driving-Test Data

Received signal level measurements are frequently used to check the performance and the quality of service (QOS) inside the coverage area in cellular networks. These expensive, time-consuming measurements are carried out using actual driving tests to assess the coverage area of a base station for a given cell, and to thus evaluate the quality of service. In a driving-test measurement system, a receiving antenna is placed on top of a vehicle. The vehicle is then driven along radial and circular lines around the base station, to measure the received power and thus assess the quality of service. These driving-test measurements are also used to tune the empirical models in the radio-planning tools that have to be employed for various types of environments. This model tuning is a lengthy procedure. In this paper, it is shown that an electromagnetic macro modeling of the environment can provide simulation results comparable to the data one would obtain in an actual driving-test measurement for a cellular environment. The input parameters for the electromagnetic macro model can be generated using only the physical parameters of the environment, such as the height of the transmitting and receiving antennas over the ground, their tilts towards the ground, and the electrical parameters of the ground. Such analysis can provide realistic plots for the received power as functions of the separation distance between the receiving and the transmitting base-station antennas. The novelty of the electromagnetic-analysis technique proposed in this paper lies in its ability to match the macro-model-based simulation results and the driving-test measurements without any statistical or empirical curve fitting or an ad hoc choice of a reference distance. In addition, a new concept, called the proper route, is introduced to enhance the analysis of the measured data. A Method-of-Moments-based integral-equation-solver code has been used to simulate the effects of the macro parameters of the environment on the propagation-path loss of the signals emanating from a base-station antenna. The perfect match between the simulation results and the driving-test data was illustrated by monitoring the signal levels from some cellular base stations in western India and Sri Lanka, and then comparing the observed results with the simulated results. The goal here is to illustrate that these numerical simulation tools can accurately predict the propagation path loss in a cellular environment without tweaking some non-physical models based on statistical modeling or heuristic assumptions.

[1]  M. Renfors,et al.  Path loss measurements for a non-line-of-sight mobile-to-mobile environment , 2008, 2008 8th International Conference on ITS Telecommunications.

[2]  Hamid Sharif,et al.  A Deterministic approach to evaluate path loss exponents in large-scale outdoor 802.11 WLANs , 2009, 2009 IEEE 34th Conference on Local Computer Networks.

[3]  T. K. Sarkar,et al.  Electromagnetic macro modeling of propagation in mobile wireless communication: theory and experiment , 2012, 2012 IEEE International Conference on Wireless Information Technology and Systems (ICWITS).

[4]  Jinghui Lu,et al.  Fading Characteristics in the Railway Terrain Cuttings , 2011, 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring).

[5]  Larry J. Greenstein,et al.  An empirically based path loss model for wireless channels in suburban environments , 1999, IEEE J. Sel. Areas Commun..

[6]  D.J.Y. Lee,et al.  The propagation characteristics in a cell coverage area , 1997, 1997 IEEE 47th Vehicular Technology Conference. Technology in Motion.

[7]  Ran Giladi,et al.  Characteristics' prediction in urban and suburban environments , 1998 .

[8]  Preben E. Mogensen,et al.  A Geometrical-Based Vertical Gain Correction for Signal Strength Prediction of Downtilted Base Station Antennas in Urban Areas , 2012, 2012 IEEE Vehicular Technology Conference (VTC Fall).

[9]  A. Sommerfeld.  Über die Ausbreitung der Wellen in der drahtlosen Telegraphie , 1909 .

[10]  F. Anwar,et al.  Prediction of received signal power and propagation path loss in open/rural environments using modified Free-Space loss and Hata models , 2008, 2008 IEEE International RF and Microwave Conference.

[11]  Bo Ai,et al.  The effect of reference distance on path loss prediction based on the measurements in high-speed railway viaduct scenarios , 2011, 2011 6th International ICST Conference on Communications and Networking in China (CHINACOM).

[12]  Hadi Alasti,et al.  Efficient experimental path loss exponent measurement for uniformly attenuated indoor radio channels , 2009, IEEE Southeastcon 2009.

[13]  R. W. McMillan,et al.  TERAHERTZ IMAGING, MILLIMETER-WAVE RADAR , 2006 .

[14]  Mitchell Lazarus,et al.  The Great Spectrum Famine , 2010 .

[15]  A De,et al.  Characterization of the Far-Field Environment of Antennas Located Over a Ground Plane and Implications for Cellular Communication Systems , 2010, IEEE Antennas and Propagation Magazine.