Adaptive propagation prediction models in land mobile systems

Sanches, Mário A. R.; Cavalcante, Gervásio P. S.

doi:10.1109/aps.2000.873859

Cited by 1 publication

(2 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a comparison, a literature review of reported propagation model assessments revealed a standard deviation of 3-15 dB for the Okumura-Hata and COST231-Hata models [4], [12] and [13], 4-8 dB for COST231-Walfisch-Ikegami [6], [14] and 3-6 dB for the ray-tracing methods [15], [16] and [17]. Signal level interpolation is quite simple and cheap to implement although it requires more measurement data than most other propagation models.…”

Section: A Results For Moving Least Squares and Triangulationmentioning

confidence: 99%

See 1 more Smart Citation

Signal level interpolation for coverage area prediction

Backman

IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004

View full text Add to dashboard Cite

Predicting the received signal level is important in the design of cellular communication systems. In this paper signal level interpolation around measured signal levels is introduced as a means to predict coverage areas. For signal level interpolation surface fitting methods are required and three methods have been evaluated: Moving Least Squares (MLS), Delaunay Triangulation and Averaging for Interpolation. The first two methods interpolate signal level values over a wide area with samples from only a few measurement points, while Averaging for Interpolation requires closely spaced, evenly scattered points. MLS and Delaunay Triangulation are described in the literature while Averaging for Interpolation is a novel method developed by the author. The interpolated signal levels have been compared with measurements. The mean of the standard deviation of the error for seven test cases is 6.1 dB with the MLS method and 5.1 dB with Triangulation. A comparison between all three methods revealed that in cases of closely spaced, evenly scattered points Averaging for Interpolation gives the smallest mean value of the standard deviation (3.0 dB) for four cases.

show abstract

Section: A Results For Moving Least Squares and Triangulationmentioning

confidence: 99%

“…There have been several suggestions for improving the Okumura-Hata and COST231-Hata models to take more propagation environment data into account [7], [8] and [9]. However, these modifications require either digital maps with sufficient resolution or on-site measurements.…”

Section: ) Enhanced Okumura-hata and Cost231-hata Modelsmentioning

confidence: 98%

Signal level interpolation for coverage area prediction

Backman

IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004

View full text Add to dashboard Cite

show abstract

Adaptive propagation prediction models in land mobile systems

Cited by 1 publication

References 2 publications

Signal level interpolation for coverage area prediction

Signal level interpolation for coverage area prediction

Contact Info

Product

Resources

About