Outdoor Path Loss Models for IEEE 802.16 in Suburban and Campus-Like Environments

Luca, Deri; Fiano, F.; Mazzenga, Franco; Monti, Cristiano; Ridolfi, S.; Vallone, Francesco

doi:10.1109/icc.2007.809

Cited by 11 publications

(6 citation statements)

References 1 publication

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“…Oyetunji [12], for the FM broadcast station at the Federal University of Technology, Akure, Nigeria, utilized pathloss measurements to evaluate the prediction performance of irregular terrain models. Outcomes of a measurement campaign conducted for the purposes of characterizing outdoor pathloss in 'campus-like' environments were reported by De-Luca et al, [13], who also utilized the results for the evaluation of some models. In a pair of companion papers, Popoola et al [14,15] presented results of the performance evaluation of five pathloss prediction models, using the results of extensive field measurements carried out over three routes at the campus of the Covenant University, Ota, Nigeria.…”

Section: Introductionmentioning

confidence: 99%

On Some Properties of the Quasi-Moment-Method Pathloss Model Calibration

Ayotunde¹,

Michael²,

Hisham³

et al. 2021

JEEE

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Certain properties of the recently introduced Quasi-Moment-Method (QMM) for the calibration of basic radiowave propagation pathloss models are systematically examined in this paper. Using measurement data concerning three different routes located in a smart campus environment and made available in the open literature, the paper, in particular, investigates the effects of size of pathloss measurement data on the outcomes of the QMM calibration of nine basic pathloss models: namely, COST 231-urban and sub-urban cities models, ECC33-large and medium sized cities models, and the Egli, Ericsson, Hata, Lee, and SUI-'Terrain A' models. Computational results reveal that for the data sizes considered, and in the cases of the basic COST 231 and Hata models, which share identical correction factors for receiver antenna height, the 'model calibration matrix' becomes ill-conditioned for one choice of basis functions. The corresponding calibrated models, however, still predict pathloss with accuracy typical of the QMM. For example, Root Mean Square Error (RMSE) outcomes of predictions due to the calibration of these models, emerged as approximately the same for these three models; with values of 6.03 dB (Route A), 7.96 dB (Route B), and 6.19 dB (Route C). The results also show that when model calibration utilizes measurement data for distances further away from the transmitters (by ignoring measurement data for radial distances less than 100m away from the transmitters) significant improvements in RMSE metrics were recorded. The paper, in terms of the eigenvalues of the model calibration matrices, further examined the responses of these models to calibration with large-sized measurement data, to find that the model calibration matrices remained characterized, in each case, by a distinctly dominant eigenvalue. An important conclusion arising from the results of the investigations is that whereas the QMM model calibration process may lead, in some cases, and when large-sized measurement data is involved, to 'badly-scaled' model calibration matrices, the calibrated models still record very good assessment metrics. Computational results also reveal that with large-sized data sets, QMM models yield pathloss predictions with excellent (close to 0 dB) mean prediction errors.

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Section: Introductionmentioning

confidence: 99%

On Some Properties of the Quasi-Moment-Method Pathloss Model Calibration

Ayotunde¹,

Michael²,

Hisham³

et al. 2021

JEEE

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“…The flexibility of wireless technology, combined with high throughput, scalability and long-range features of the IEEE 802.16 standard helps to fill the broadband coverage gaps and reach millions of new residential and business customers worldwide [2]. Based upon the filed measurements of signal strengths of different places, with different scenarios, path loss models have been devised.…”

Section: Introductionmentioning

confidence: 99%

Methodology for Calculating Path Loss Upper and Lower Bounds for WiMAX

Aboul-Dahab

Kamel

2009

2009 3rd International Conference on New Technologies, Mobility and Security

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The WiMAX (IEEE 802.16) technology is widely deployed to provide users with wireless network connectivity in easy way. Propagation measurements at the frequency of 3.5 GHz for the WiMAX technology have been taken from different places in the world with different topologies. This paper deals with path loss calculation and analysis in order to fined the best methodology for calculating upper and lower bounds for the path loss using Least Square Approximation which help designers of the network to have clear vision of the losses. A comparison between path loss models also is presented here.

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“…Fixed WiMAX is targeted for fixed and nomadic broadband services while mobile WiMAX are designed to provide high mobility services. While the performance and propagation models of the fixed WiMAX system have been widely studied [2][3][4][5], the mobile WiMAX is yet to witness widespread attention. To the best of our knowledge, there are no reports in the literature for mo-bile WiMAX performance presented for the desert terrains that are the subject of this paper.…”

Section: Introductionmentioning

confidence: 99%

“…Operators do drive-tests on a continuous basis, collecting signal levels, network quality and performance which are then used to refine empirical propagation models for system-planning and/or existing network optimization [7][8][9]. Reference [3] provides measurement results for some Italian University campuses in the 3.5 GHz frequency band where they attempted to extract and refine previous path-loss models for their experimental data. Note that the Walfish and Bertoni model is an extension of the COST-231 (and COST-231 Hata model is an extension of the Hata-Okumura model).…”

Section: Introductionmentioning

confidence: 99%

On the Performance of Mobile WiMAX System: Measurement and Propagation Studies

Alshaalan¹,

Alshebeili

Adinoyi³

2010

IJCNS

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In this paper, we present drive test results for mobile WiMAX system for desert and cosmopolitan terrains where there are few studies reported in the literature. The extensive measurement is performed in the framework of the physical performance of the WiMAX technology which is often considered as a 4G system. Path loss model is fitted for the collected data. The work is unique in the sense that most empirical channel models are produced in regions where the environments (weather, buildings, vegetation, among others) are quite different from the desert terrains that are considered in this study. We also show that shadowing is truly lognormal in dB and the standard deviation values are calculated for the desert terrain from the measurement data. The measurements are collected using WiMAX BS station, with greenpacket dongle, and NEMO versatile outdoor drive test equipment to evaluate and characterize the performance of the system. The received signal strength indicators measured, are analyzed to complement network design and network optimization for regions where the popular models may not be accurate

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Outdoor Path Loss Models for IEEE 802.16 in Suburban and Campus-Like Environments

Cited by 11 publications

References 1 publication

On Some Properties of the Quasi-Moment-Method Pathloss Model Calibration

On Some Properties of the Quasi-Moment-Method Pathloss Model Calibration

Methodology for Calculating Path Loss Upper and Lower Bounds for WiMAX

On the Performance of Mobile WiMAX System: Measurement and Propagation Studies

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