Abstract
This paper investigates the performance boundaries of a calibrated deterministic indoor channel model. From a propagation modeling point of view, this process allows to assess the weakness of ray tracing and sets the boundary conditions for a such modeling method. The principle of the deterministic model calibration used in this work focuses upon the estimation of optimal material parameters by means of a few pilot measurements and a simulated annealing method. This technique improves the accuracy of the prediction model for all measurement positions including those not considered by the calibration. The performance of the calibrated ray tracing model and the sensitivity of the calibration to the number of pilot measurements have been investigated. For this investigation, a measurement campaign has been conducted within an indoor office building at 2.45 GHz with 100 MHz bandwidth. Furthermore, the model performance has been compared to empirical indoor models.
Highlights
The calibration consists in extracting relevant multipath components (MPCs), for instance once reflected paths, simultaneously from the model and measurement
This paper addresses the subject of a new deterministic model calibration technique based on simulated annealing, which improves the model performance by means of a few pilot measurements
The basic facts that emerge from this paper are mainly the model performance improvement and the performance limit reached with more measurements
Summary
The blind prediction, based on a priori approximate knowledge of material parameters, often shows an obvious mismatch with the measurements. Ray tracing-based conventional deterministic modeling methods use geometrically accurate data and rely on tabulated values for the electrical parameters of the building materials. A calibration of these material parameters, reducing the mismatch between the model and the measurements, is required. Using the gradient method in conjunction with this tuning provides generally a local minimum and does not necessarily provide the optimal solution. As the relation between power taps and material parameters is a nonlinear combinatorial relationship, the simulated annealing approach used in this paper provides the general optimal solution by simultaneously changing the dielectric constant and loss tangent of all material parameters with a changing step at each range of iterations. The performance and robustness of this calibration procedure is analyzed in this paper by means of an indoor measurement campaign within an office building.
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