2009 International Conference on Ultra Modern Telecommunications &Amp; Workshops 2009
DOI: 10.1109/icumt.2009.5345510
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Empirical calculation of shadowing deviation for complex indoor propagation topologies at 2.4 GHz

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Cited by 18 publications
(18 citation statements)
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“…At the same time, the obstacle-constrained topology will have a severe impact on the signal attenuation, both large-scale (shadowing from obstructing materials) and small-scale (multipath propagation, scattering from small obstacles). As it has been confirmed in [34], an obstacle-dense topology produces a dynamic shadowing throughout the topology. In that case, a mathematical description of large-scale fading with an area-mean value of shadowing deviation does not provide reliable results and a more thorough methodology on localmean scale can describe the phenomenon adequately.…”
Section: Average Snr Values For All Moving Nodesmentioning
confidence: 56%
“…At the same time, the obstacle-constrained topology will have a severe impact on the signal attenuation, both large-scale (shadowing from obstructing materials) and small-scale (multipath propagation, scattering from small obstacles). As it has been confirmed in [34], an obstacle-dense topology produces a dynamic shadowing throughout the topology. In that case, a mathematical description of large-scale fading with an area-mean value of shadowing deviation does not provide reliable results and a more thorough methodology on localmean scale can describe the phenomenon adequately.…”
Section: Average Snr Values For All Moving Nodesmentioning
confidence: 56%
“…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.…”
Section: Discussionmentioning
confidence: 99%
“…Measurements were performed extensively at Athens International Airport "Eleftherios Venizelos" throughout the airport's 802.11g network consisting of various Access Points (APs) [16]. The results provided a numerical adjustment to the ITU indoor path loss model with radically smaller values of the slope factor (path loss exponent), whereas coverage for each AP ranged up to 70 meters, marking a departure from the more limited range of APs in obstacle-dense propagation locations as in [14], [15].…”
Section: Introductionmentioning
confidence: 99%
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“…This allowed for a wireless channel characterization for home and office topologies, providing also a numerical adjustment to the original ITU specifications in [15]. In [16], an empirical method for a site-specific calculation of shadowing deviation was developed, based on the Multi-Wall-Floor (MWF) model [17].…”
Section: Introductionmentioning
confidence: 99%