The aim of this chapter is to summarize and present recent findings in the field of wireless channel modeling that provide a new method for the reliable calculation of the statistical parameters of large-scale variations of the average received signal (shadow fading). This algorithm is theoretically based on a path loss estimation model that incorporates losses due to walls and floors. This has been confirmed to be the most precise mathematical tool for average signal strength prediction for various frequencies of interest and propagation environments. The total path loss is estimated as a sum of two independent attenuation processes: free space loss and losses due to obstacles. This solution allows for a direct and reliable calculation of the deviation of the fluctuations of the average received signal in an obstacle-dense environment.
TopWireless Channel Characterization: Open Issues
Many published works have raised the issue of path loss modeling in an outdoor propagation environment for the GSM/UMTS frequencies (Lee & Miller, 1998; Seybold, 2005). Various empirical and semi-empirical (deterministic) path loss models have been developed and validated in terms of mean error (%) in their predictions of average received power at any given distance from the transmitter throughout a propagation environment (Parsons, 2000; Rappaport, 1999). Intrinsic topology characteristics have been incorporated in the mathematical expressions of these models and various extensions of these models have been provided in terms of distance coverage and carrier frequency shifting (Iskander, Yun, & Zhang, 2001).
Over the years, many published works have dealt with finding the appropriate small-scale fading distribution to describe an indoor propagation topology (Cheung, Sau, & Murch, 1998; Henderson, Durkin, & Durkin, 2008; MacLeod, Loadman, & Chen, 2005; Walker, Zepernick, & Wysocki, 1998). However, there was not, until recently, a comparative validation of indoor path loss models for the estimation of the large-scale attenuation of an RF signal propagated in an indoor environment. Even more so, there had been no validation of path loss modeling for the 2.4 GHz frequency, which holds a dominant role in indoor wireless networks (802.11b/g/n) and will continue to be of importance as next-generation networks come into the forefront.