Abstract
The majority of currently available wireless devices' localization systems are based on received signal strength (RSS) measurements. The input to the localization technique is configured by the average of a number of N instantaneous RSS samples; thereupon, during simulation of such techniques, it is necessary to generate N RSS samples and calculate the corresponding average, which results to increased computational cost and run time. A new technique for reducing computational cost and run time of localization techniques simulators is proposed based on directly sampling a probability distribution function (PDF) corresponding to the average RSS of N samples. However, PDFs of the average RSS cannot be readily calculated and often there is no analytical solution. A study based on goodness-of-fit tests and localization precision is presented herein in order to numerically evaluate the replacement of unknown average RSS PDFs with empirically yielded ones. Furthermore, an indoor propagation and localization techniques simulator has been developed employing the proposed technique. Numerical results demonstrate the applicability of the proposed approach in achieving fast simulation of average small-scale fading and its application to RSS-based localization techniques simulation.
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