Quantitative Measurement of Path Loss Model Adaptation Using the Least Squares Method in an Urban DVB-T2 System

Keawbunsong, Pitak; Duangsuwan, Sarun; Supanakoon, Pichaya; Promwong, Sathaporn

doi:10.1155/2018/7219618

Cited by 6 publications

(4 citation statements)

References 23 publications

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“…From Figure 5, we can see that almost half of the studies are based on traditional linear regression. On the one hand, some are directly modeled using linear regression based on measured data for street [45], bleeding [46][47][48], indoor [49][50][51][52][53][54], urban [55][56][57], vegetation shielding [58][59][60], vehicle-to-vehicle channels (V2V) [61], and station scenarios [62]. At the same time, some researchers have used linear regression to fit the standard models.…”

Section: Indexmentioning

confidence: 99%

The Current Progress and Future Prospects of Path Loss Model for Terrestrial Radio Propagation

Wang,

Hao,

Yang

2023

Electronics

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The radio channel model is a major factor supporting the whole life cycle of the terrestrial radio system, including the demonstration, design, validation, operation, and so on. To improve the spectrum sharing and spectral efficiency in terrestrial radio services, we analyze three types of path loss models in detail: deterministic, empirical, and semi-empirical models, to meet the requirements of path loss modeling for supporting traditional band expansion and reuse. Then, we conduct a comparative analysis based on the characteristics of the current models. Furthermore, a preview of the future terrestrial path loss modeling methods is provided, including intelligent modeling processes and multi-model hybridization methods. Finally, we look forward to the potential technology that can be used in future wireless communication, such as terahertz communication, reconfigurable intelligent surface technology, and integrated communication and sensing technology. The above research can provide a reference for the development of terrestrial radio channel modeling, promoting the technologies of terrestrial channel modeling. We hope this paper will stimulate more interest in modeling terrestrial radio channels.

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Section: Indexmentioning

confidence: 99%

The Current Progress and Future Prospects of Path Loss Model for Terrestrial Radio Propagation

Wang,

Hao,

Yang

2023

Electronics

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“…8. These measurements allowed us to estimate the values of A and n for each access point (AP) using the least squares method [45]. Table II presents the path loss parameters for the selected environment.…”

Section: Evaluation Proceduresmentioning

confidence: 99%

TLB & WC-TLB-MM: The Improved Min-Max Algorithms for Multi Targets Indoor Localization

Adiyatma,

Suroso,

Cherntanomwong

2023

IEEE Access

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Internet of Things (IoT)-based Indoor localization is the most commonly used system to determine target locations indoors. It applies to various purposes, e.g., indoor navigation, asset tracking in warehouse management, and tracking people in hospitals. Distance-based techniques using the Received Signal Strength Indicator (RSSI), e.g., Min-Max, are widely applied because they can be directly implemented without prerequisite work such as site surveys. However, a challenging indoor environment with high numbers of interiors and people can obstruct signal propagation. This obstruction can reduce the accuracy of translating RSSI to distance using the path loss model, which will degrade the localization accuracy. In this paper, we introduce two improved Min-Max (MM) algorithms, i.e., Three Layer Bounding Box Min-Max (TLB-MM) and Weighted Centroid TLB-MM (WC-TLB-MM), to alleviate the issue and achieve higher localization accuracy. The novelty of the proposed TLB-MM is incorporating RSSI error functions to generate three-layer bounding boxes: the inner, middle, and outer in the Min-Max algorithm. Meanwhile, WC-TLB-MM enhanced the TLB-MM algorithm by integrating the Weighted Centroid Localization Algorithm (WCLA) in the calculation process. We validate our proposal by conducting various experiments using Wi-Fi at 2.4 GHz deployed in a laboratory room of 10.17 m × 9.12 m. Experimental results demonstrate that TLB-MM improved the accuracy performance to 55.78% and 30.86%, while WC-TLB-MM gave 40.93% and 7.65% compared to Min-Max and WCLA, respectively. From these results, our proposed methods are proven simple yet applicable to RSSI-based indoor localization systems.

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“…The performances of both tuned models were not consistent, as RMSE values reported by the authors varied from as low as 1.523dB in one case, to as high as 20.8009dB in another. Unlike what obtained with the examples described in the foregoing discussions, Keawbunsong et al [6], focused model calibration attention on a third generation terrestrial Digital Video broadcasting network. Their approach is also a least square linear regression method that incorporated a random error term.…”

Section: Introductionmentioning

confidence: 97%

An evaluation of Quasi-Moment-Method calibrated pathloss models for Benin City Nigeria

Adelabu¹,

Ayorinde²,

Muhammed³

et al. 2021

Nig. J. Tech.

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This paper introduces the Quasi-Moment-Method (QMM) as a novel radiowave propagation pathloss model calibration tool, and evaluates its performance, using field measurement data from different cellular mobile communication network sites in Benin City, Nigeria. The QMM recognizes the suitability of component parameters of existing basic models for the definition of ‘expansion’ and ‘testing functions’ in a Galerkin approach, and simulations were carried out with the use of a FORTRAN program developed by the authors, supported by matrix inversion in the MATLAB environment. Computational results reveal that in terms of both Root Mean Square (RMS) and Mean Prediction (MP) errors, QMM-calibrated models performed much better than an ‘optimum’ model reported for the NIFOR (Benin City), by a recent publication. As a matter of fact, the QMM-calibrated COST231 (rural area) model recorded reductions in RMS error of between 31.5% and 71% compared with corresponding metrics due to the aforementioned ‘optimum’ model. The simulation results also revealed that of the five basic models (COST231-rural area and suburban city, ECC33 (medium and large sized cities), and Ericsson models) utilized as candidates, the two ECC33 models, whose performances were consistently comparable, represented the best models for QMM-model calibration in the Benin City environments investigated.

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Quantitative Measurement of Path Loss Model Adaptation Using the Least Squares Method in an Urban DVB-T2 System

Cited by 6 publications

References 23 publications

The Current Progress and Future Prospects of Path Loss Model for Terrestrial Radio Propagation

The Current Progress and Future Prospects of Path Loss Model for Terrestrial Radio Propagation

TLB & WC-TLB-MM: The Improved Min-Max Algorithms for Multi Targets Indoor Localization

An evaluation of Quasi-Moment-Method calibrated pathloss models for Benin City Nigeria

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