2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC) 2014
DOI: 10.1109/pimrc.2014.7136164
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A novel dual-slope mm-Wave channel model based on 3D ray-tracing in urban environments

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Cited by 29 publications
(26 citation statements)
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“…The relatively small mm-wave propagation environment allows easy and fast RT prediction, thus overcoming its traditional drawback: high computation time. Moreover, due to its accuracy and versatility RT can be used to derive simpler path-loss models [61] [62] or to directly perform multidimensional channel characterization, often in combination with measurements [34], [63]- [65]. Since RT models by definition simulate multipath propagation, they can be used to evaluate and/or compare the performance of MIMO solutions (e.g.…”
Section: A Deterministic and Semi-deterministic Modelsmentioning
confidence: 99%
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“…The relatively small mm-wave propagation environment allows easy and fast RT prediction, thus overcoming its traditional drawback: high computation time. Moreover, due to its accuracy and versatility RT can be used to derive simpler path-loss models [61] [62] or to directly perform multidimensional channel characterization, often in combination with measurements [34], [63]- [65]. Since RT models by definition simulate multipath propagation, they can be used to evaluate and/or compare the performance of MIMO solutions (e.g.…”
Section: A Deterministic and Semi-deterministic Modelsmentioning
confidence: 99%
“…Instead of an extensive measurement campaign, ray tracing simulations in downtown Ottawa have been used recently to derive a dual-slope path loss model for 28 GHz outdoor links [61]. This dual-slope characteristic is probably related to the lower degree of through-wall penetration and DMC of mm-wave frequencies with respect to UHF.…”
Section: B Other Propagation and Channel Modelsmentioning
confidence: 99%
“…Direct use of the collected distance-total power pair (d, PL(d)) in the ray-tracing simulation gives bias from the different number of samples over distance because the number of samples with longer distance is greater than shorter distance. To solve the problem, we use the local mean path loss [8]. From the distance-local mean path loss pair (d a , PL a ), we calculate PLE n which minimizes the least square error [17].…”
Section: B Path Lossmentioning
confidence: 99%
“…In NLoS case, we also calculate dual-slope path loss equation to reduce the root mean square (RMS) error bewteen the local mean path loss and path loss equation [8]. In the dual-slope path loss, two different linear path loss equations are used.…”
Section: B Path Lossmentioning
confidence: 99%
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