Performance evaluation for RF propagation models based on data measurement for LTE networks

Shakir, Zaenab; Al-Thaedan, Abbas; Alsabah, Ruaa; Al-Sabbagh, Ali; Salah, Monera; Zec, Josko

doi:10.1007/s41870-022-01006-8

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…The drive/walk test has been the classic technique to collect radio signal measurements in mobile network operators [18], [35], [36]. These measurements are used for coverage evaluation, operator benchmarking, and trouble shooting and optimizing cellular networks.…”

Section: Methods 21 Datasetmentioning

confidence: 99%

User equipment geolocation depended on long-term evolution signal-level measurements and timing advance

Shakir

Zec

Kostanic

et al. 2023

IJECE

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<p>A new approach is described for investigating the accuracy of positioning active long-term evolution (LTE) users. The explored approach is a network-based method and depends on signal level measurements as well as the coverage of the serving cell. In a two-dimensional coordinate system, the algorithm simultaneously applies LTE measured data with a combination of a basic prediction model to locate the mobile device’s user. Furthermore, we introduce a unique method that combines timing advance (TA) and the measured signal level to narrow the search region and improve accuracy. The developed method is assessed by comparing the predicted results from the proposed algorithm with satellite measurements from the global positioning system (GPS) in various scenarios calculated via the number of cells that user equipment concurrently reports. This work separates seven different cases starting from a single reported cell to five reported cells from up to 3 sites. For analysis, the root mean square error (RMSE) is computed to obtain the validation for the proposed approach. The study case demonstrates location accuracy based on the numbers of registered cells with the mean RMSE improved using TA to approximately 70-191 m for the range of scenarios.</p>

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Section: Methods 21 Datasetmentioning

confidence: 99%

User equipment geolocation depended on long-term evolution signal-level measurements and timing advance

Shakir

Zec

Kostanic

et al. 2023

IJECE

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“…The LTE data was measured in Cologne, Germany, with a total length route 16 km as shown in Figure 1 and frequency band 2,500 MHz. The data is collected using the driving test (DT) that the operators commonly use to collect, test, and optimize the coverage area and figure out the troubles [25], [26]. DT gathers data at various distances from the base stations starting at l0 m to 2 km.…”

Section: Datasetmentioning

confidence: 99%

Performance analysis for a suitable propagation model in outdoor with 2.5 GHz band

et al. 2023

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As demand for mobile wireless network services continues to rise, network planning and optimization significantly affect development. One of the critical elements in network planning is predicting pathloss. Thus, propagation models predict pathloss in indoor and outdoor environments. Choosing the appropriate propagation model for the area out of existing models is essential for network planning. Selected propagation models suitable with 2.5GHz, such as Friis Free Space Propagation Model (FSPL), Sandford University Interim (SUI), Ericsson, Okumura, and COST-231 HATA models, are utilized for evaluation and compared with empirical data collected from long-term evolution (LTE) networks in urban areas. The best acceptable model is chosen based on statistical results such as mean, standard deviation, and root mean square errors (RMSE). The analytical results show Cost-231 Hata model fits the empirical pathloss with a minimum RMSE of 5.27 dB.

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“…To improve the accuracy in estimating the harvestable power, considerations of reflection, diffraction, and scattering of the waves must be considered. In this case, the power is evaluated as in Equation (3), and the model is known as the two-ray model [ 41 ].

where

and

represent the effective height of the receiving and transmitting antenna, respectively; the other parameters are defined as above.…”

Section: Rectenna Feeding Techniques (Rft)mentioning

confidence: 99%

“…One of the most popular is the log-distance path-loss model; this includes random shadowing effects caused by a signal obstruction such as a building. The harvestable power is, in this case, expressed as follows [ 41 ]:

…”

Section: Rectenna Feeding Techniques (Rft)mentioning

confidence: 99%

Radiofrequency Energy Harvesting Systems for Internet of Things Applications: A Comprehensive Overview of Design Issues

Mouapi

2022

Sensors

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Radiofrequency energy harvesting (RF-EH) solutions have evolved significantly in recent years due to the ubiquity of electromagnetic waves in any environment. This review presents a comprehensive report on autonomous wireless sensor (WS) design considerations based on RF-EH. The obtainability of RF-EH-WS is driven by development efforts in the areas of RF-EH circuit design, known as rectifying antenna (Rectenna), the minimization of the energy budget of WS (MEB-WS), and finally, power management modules (PMM). The PMM aims to optimize the energy efficiency of the WS. In addition to these three factors, examining the RF power levels harvested related to the rectenna feeding technique (RFT) is essential. Since we did not find any review presenting a holistic view of these design considerations, we strived to provide a detailed picture of recent advances and new enhancements in this review. To address this issue, this review gives an overview of the seminal and contemporary studies in the RF-EH-WS field. The IoT issues are also discussed in terms of their basic requirement to support reduced size or miniaturized smart objects, which are common matters in current applications of WS nodes. Potential open issues that might be considered for future research are also discussed in this article. For a more detailed description of all presented concepts, many significant references are provided for the readers.

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Performance evaluation for RF propagation models based on data measurement for LTE networks

Cited by 5 publications

References 18 publications

User equipment geolocation depended on long-term evolution signal-level measurements and timing advance

User equipment geolocation depended on long-term evolution signal-level measurements and timing advance

Performance analysis for a suitable propagation model in outdoor with 2.5 GHz band

Radiofrequency Energy Harvesting Systems for Internet of Things Applications: A Comprehensive Overview of Design Issues

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