Propagation loss prediction: A comparative study with application to the mobile radio channel

Delisle, G.Y.; Lefèvre, Jean-Paul; Lecours, M.; Chouinard, Jean‐Yves

doi:10.1109/t-vt.1985.24041

Cited by 46 publications

(21 citation statements)

References 7 publications

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“…In the end, it was concluded that no single path loss model was able to predict path loss consistently. In [18], a comparative assessment of five models was presented with respect to the data collected in the urban and suburban environments at 910 MHz. However, the paper does not provide a conclusion about which model gives the best results.…”

Section: Related Workmentioning

confidence: 99%

On the Study of Empirical Path Loss Models for Accurate Prediction of Tv Signal for Secondary Users

Фарук¹,

Ayeni²,

Adediran³

2013

PIER B

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Abstract-Demand for wireless communication technologies and systems keep increasing and has reached the peak where the capacity can only be achieved by improving spectrum utilization. The spectrum allocated to TV broadcast systems can be shared by wireless data services through exploiting spatial reuse opportunities (Spatial TV white space).Path loss models are used extensively in signal prediction, coverage optimization and interference analysis. Recently it is being used in estimating distances for safe operation of secondary users in TV white space. Peculiarities of these models give rise to high prediction errors when deployed in a different environment other than the one initially built for. It is however not very clear which model gives the best fit and what the penalties are for using the models outside the intended coverage area. In this paper, we assess the fitness of nine empirical widely used path loss models using five novel metrics to gauge their performance. In order to achieve this, field strength measurements were conducted in the VHF and UHF regions along six different routes that spanned through the urban, suburban and rural areas of Kwara State, Nigeria. A program was developed in VB 6.0 language to compute the path losses for the empirical models. The measurement results were converted to path losses and are compared with the model's prediction. The results show that no single model provides a good fit consistently. However, Hata and Davidson models provide good fitness along some selected routes with measured RMSE values of less than 10 dB. ITU-R P.1546-4, Walfisch Ikegami (WI), Egli, CCIR and FSPL perform woefully, with higher RMSE and SC-RMSE (Spread Corrected RMSE) values. Further analysis on the error spread as a function of distance along 60 km route revealed that Hata and Davidson models show symmetry up to about 30 km with slight divergence between 24 km and 30 km after which Davidson model gives lower prediction error along the route. The prediction errors for Davidson model distributes nearly symmetrically around the mean error of 2.15 dB. It is noteworthy that the Gaussian error distribution within the window of ±5 dB dominates the frequency counts. However, the error counts for CCIR model closely follow normal distribution with a mean error of −6.37 dB but Hata, FSPL, Walfisch Ikegami and ITU-R P. 529-3 models do not follow normal distribution curve.

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Section: Related Workmentioning

confidence: 99%

On the Study of Empirical Path Loss Models for Accurate Prediction of Tv Signal for Secondary Users

Фарук¹,

Ayeni²,

Adediran³

2013

PIER B

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“…Specifically, the Delisle statistical terrain diffraction loss estimate (Ld ∆h) is selected by running Microsoft Excel Solver's nonlinear optimization tool on the first drive test data. According to Delisle et al (1985), Ld ∆h) value of 15 is set as the minimum and 400 as the maximum. The Microsoft Excel's Solver nonlinear optimization is run with the condition that 15 P Ld ∆h P 400 and the objective is to minimize the root mean square error between the measured pathloss in the first drive test and the Blomquist-Ladell model predicted pathloss.…”

Section: Resultsmentioning

confidence: 99%

“…Where h is the height of transmitter above ground in m h is the height of receiver above ground in m d is the distance between transmitter and receiver along line of sight path in km d D is the distance between transmitter and receiver along line of sight path in m (1000d) f is the carrier frequency in MHz λ is the carrier wavelength in m ϵ is the dielectric constant (relative permittivity) of the ground (Delisle recommends ϵ =10 for dry earth [12].…”

Section: Methodsmentioning

confidence: 99%

“…Where Ld ∆h is the statistical terrain diffraction loss estimate which describes the "roughness" of the terrain as presented by Delisle, Lefevre, Lecours and Chouinard [12]. A value of U15 is considered minimal, U 200 is used for hilly terrain, and U 400 for very rugged terrain.. Delisle proposed the method for computing an estimate of additional losses due to terrain [12].…”

Section: Methodsmentioning

confidence: 99%

“…A value of U15 is considered minimal, U 200 is used for hilly terrain, and U 400 for very rugged terrain.. Delisle proposed the method for computing an estimate of additional losses due to terrain [12]. L GH is the basic free-space loss.…”

Section: Methodsmentioning

confidence: 99%

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Tuning and Cross Validation of Blomquist-Ladell Model for Pathloss Prediction in the GSM 900 Mhz Frequency Band

Aloziem¹

2017

IJTAM

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Abstract:In this paper, Blomquist-Ladell model is tuned and used for the prediction of total pathloss for GSM signal in the 900 MHz band. The model combined free-space loss, excess plane-earth loss and tunable multiple knife-edge diffraction loss to give the total loss. Pathloss data captured from two drive test conducted in Uyo suburban area are used in the study. The first drive test dataset are used to tune the Blomquist-Ladell model, particularly to select the value of the statistical terrain diffraction loss that minimizes the root mean square error (RMSE) of the model prediction. The tuned Blomquist-Ladell model is then cross validated with the second drive test dataset. The results show that the Blomquist-Ladell model performed very well; with the training data (first drive test dataset) the model has RMSE of 2.935598 dB and Prediction Accuracy of 98.16323% and in the cross validation data (the second drive test dataset) the model has RMSE of 3.398141dB and Prediction Accuracy of 97.82251%. In both cases, the RMSE is below 3.5 dB which is below the acceptable maximum value of 7dB for such pathloss prediction model.

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Multihop relaying for broadband wireless access systems at 800 and 3500 MHz in rural areas

2014

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This paper addresses the coverage enhancement for broadband wireless access (BWA) at 800 and 3500 MHz in a rural scenario in north Germany using multi-hop relay concepts. The investigation is divided into two phases: In phase I, the coverage of a single BWA system in a rural area is predicted and verified with measurement data. In phase II, the coverage from the BWA system is analyzed and enhanced through the deployment of relay stations. The number of relay stations required for each carrier frequency is determined, and the positions of the relay stations are identified via three different relay placement algorithms, namely path-loss-based, distance-based, and hybrid algorithms. At 800 MHz, the path-loss-based algorithm requires seven relay stations to achieve an overall coverage of 95%. The hybrid and distance-based algorithms require 11 and 14 relay stations, respectively, to achieve the same coverage. At 3500 MHz, path-loss based and hybrid algorithms require 19 and 16 relay stations, respectively, to achieve the same coverage. The distance-based requires 20 relay stations to achieve an overall coverage of 82%. Further increase of relay stations has led to higher interference. Lastly, the transmit power of the relay station is optimized via an intelligent power allocation scheme. The results show that 20% of the total transmit powers from 14 relay stations can be saved at 800 MHz whereas 18% of the total transmit powers from the 20 relay stations can be saved at 3500 MHz.

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Propagation loss prediction: A comparative study with application to the mobile radio channel

Cited by 46 publications

References 7 publications

On the Study of Empirical Path Loss Models for Accurate Prediction of Tv Signal for Secondary Users

On the Study of Empirical Path Loss Models for Accurate Prediction of Tv Signal for Secondary Users

Tuning and Cross Validation of Blomquist-Ladell Model for Pathloss Prediction in the GSM 900 Mhz Frequency Band

Multihop relaying for broadband wireless access systems at 800 and 3500 MHz in rural areas

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