A 3-D integrated macro and microcellular propagation model, based on the use of photogrammetric terrain and building data

Abstract

This paper describes a fully three-dimensional deterministic propagation model based on a radar crosssection analysis of terrain pixels and building walls. The model utilises a variable resolution terrain database as well as a buildings database to predict signal strength, time dispersion and fading information[, in addition to providing spatial information (e.g. arrival angles) for the propagation channel. It considers scattering from illuminated terrain pixels and building walls as well as considering off-axis terrain and rooftop diffraction contributions.The model can be particularly useful for integrating macrocells and microcells e.g. predicting interference in a microcell due to a nearby macrocell or vice versa. Signal strength predictions from the model show good agreement with narrowband measurements for a rural macrocell. The effects of buildings and foliage in the prolpagation channel are investigated, and reveal that large errors can result if these effects are ignored. The accuracy improvement of the 3-D analysis over the simpler 2-D approach is also demonstrated. 0-7803-3659-3/97 $1 0.00 0 1 997 IEEE 1957

MIMO–OFDM WLAN Architectures, Area Coverage, and Link Adaptation for Urban Hotspots

“…Within the RTD model, electromagnetic waves are traced in 3-D space from the transmitter to the receiver, together with building, edge, corner, and terrain interactions. It requires geographic data in the form of terrain, building, foliage, and ground cover type and was previously validated using measurement data collected in mixed urban and rural environments [26].…”

A mixed-cell propagation model for interference prediction in a UMTS network

“…It shows the ray paths for the dominant rays between the prediction points. This propagation model has been validated using measurement data collected in mixed urban and rural environments [3], [4]. Figures 4 and 5 show example comparisons between measurement and prediction in two very different environments, both showing very good agreements between measured and predicted signal levels (<7.5dB RMS error).…”

“…The model is an extension of that described in [3] and [4]. The previous model was optimised for macrocellular environments with high-mounted BS antennas, and also for inter-cellular (both micro and macro) propagation, where rooftop diffraction is the dominant propagation mechanism.…”

“…In addition, the previous model only considered prediction areas up to lOkm by IOkm. The use of a novel variable terrain resolution technique has produced a significant speed-up in the model execution time for large areas [3], [4]. Basically, the terrain resolution is progressively dropped in elliptical zones around the BS and MS, with increasing distance away from the BS and MS.…”

“…Figures 4 and 5 show example comparisons between measurement and prediction in two very different environments, both showing very good agreements between measured and predicted signal levels (<7.5dB RMS error). The profiles in figure 4 are for a rural area with numerous of hedges and trees, a low building density, and with a high mounted BS antenna (15m above ground) [3]. The profiles shown in figure 5 on the other hand are for an area in central Bristol with high building density, and with the BS antenna at a height of 3m above ground.…”