Wireless channel characterization for a home indoor propagation topology at 2.4 GHz

Characterization of propagation mechanisms for the 2.4 GHz channel at Athens International Airport

“…Both models' fit for AP1 is less accurate than in the other two cases, due to the increased OLOS schemes appearing in that scenario. Overall, the Goodness-of-Fit for this topology is a significant departure from the respective Goodness-of-Fit conducted for an indoor obstacle-dense (residential) propagation topology [19], where the Gaussian distribution was employed to fit the logarithmic (dBm) values of the received signal power, confirming the log-normal nature of shadow fading. In order to further investigate the large-scale statistical properties of the received signal, the empirical cumulative distribution function (CDF) is derived out of the measured values of the local mean power and compared to the respective Gaussian CDF that corresponds to the Log-normal large-scale channel assumption (Gaussian distribution of logarithmic values of received signal power).…”

“…Contrary, however, to the obstacle-dense indoor propagation topologies studied in [18] and [19], Athens International Airport, with the exception of a few locations, does not constitute such a case: Line-of-Sight is a dominant scheme, and even when obstruction occurs, it corresponds to measurement locations chosen in specific locations (corners of walls) in order to examine the behavior of reflection phenomena and their impact on the received signal strength (i.e. experimental calculation of Rice factor, as an indication of LOS component to diffuse component Power ratio).…”

“…Moving past an already published comparison of the reliability of indoor path loss models, the large-scale variations of the received signal power were investigated in relation to the intrinsic characteristics of the specific environment, where the coverage area of each Access Point is significantly larger compared to standard coverage distances of 802.11g networks for indoor propagation topologies as provided in literature and also in recent published works such as [14], [15], [18], [19]. In addition, the large-scale signal fluctuation manifested a deviation from obstacle-dense indoor topologies where shadowing is a significant attenuation factor alongside (and independent from) free space, distance-dependent attenuation.…”

Impact of shadowing on wireless channel characterization for a public indoor commercial topology at 2.4 GHz

“…In addition, the MultiWall-Floor model takes into account the decreasing penetration loss of walls and floors of the same material as their number increases. As proven in [14] the MWF model is by far the most reliable indoor RF model for home and office topologies with remarkably lower mean error values (%) compared to all other path loss models, including the Motley-Keenan model [20], another empirical model that incorporates losses caused by walls and floor but fails to predict in reliable manner.…”

“…In [14] a comparison of 6 major indoor RF models was performed, based on extensive measurements in residents and offices featuring operating Wi-Fi systems (802.11g protocol). This allowed for a wireless channel characterization for home and office topologies, providing also a numerical adjustment to the original ITU specifications in [15].…”