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

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

doi:10.11591/eei.v12i3.5006

Cited by 5 publications

(6 citation statements)

References 26 publications

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“…In all three cases there is a greater error in the abscissa axis (mu), affecting the symmetry in the vertical axis. It can be concluded that the logistic distribution is better adapted to the data obtained from radiocommunication systems, which is why the different propagation models are considered as modifications of the logarithmic model [34]. Table 7 presents the distribution correlation matrix for the LQI range parameters of the data set with no missing values.…”

Section: Resultsmentioning

confidence: 99%

Description and analysis of Sigfox received signal strength indicator dataset by using statistical techniques

Lara-Cueva,

Yandún-Imbaquingo,

Bustamante-Lucio

2024

Bulletin EEI

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Low power wide area network (LPWAN) technology has expanded and is essential in the development of applications for the internet of things (IoT). The Sigfox LPWAN network is characterized by its long-range coverage, low cost and power consumption. In this article, a set of 5174 values is analyzed, containing 1606 null RSSI data, obtained with the Sipy module and MicroPython, which provide a coverage map of several points with a resolution of 200 meters deployed in Quito–Ecuador. It is evaluated the type of distribution to which the set of network measurements is adjusted and an optimal 900 MHz propagation model in suburban environments is determined from the measurements obtained from the known base station. As a result, the lost values of RSSI were predicted using the inverse normal distribution method in the original values, observing that they conform to a logistic distribution. The data from the base station were subjected to a data augmentation algorithm designed in MATLAB, determining that the stanford university interim (SUI) model reduces the precision error in the trend of the curve by not presenting changes greater than 5 dB, achieving a precision of 97% with respect to the fit of the curve of the data.

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Section: Resultsmentioning

confidence: 99%

Description and analysis of Sigfox received signal strength indicator dataset by using statistical techniques

Lara-Cueva,

Yandún-Imbaquingo,

Bustamante-Lucio

2024

Bulletin EEI

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“…By considering the frequency, transmitted distance, height of the base station antenna, and height of the mobile antenna, one could reasonably predict the propagation loss expected in the original Okumura model. However, it should be noted that the calculated losses using the Hata model start to differ from the Okumura curves beyond certain limits [3,6].…”

Section: B Hata Modelmentioning

confidence: 90%

“…Researchers have developed and studied various models that aim to capture the complex characteristics of wireless signals in different propagation environments, such as urban, suburban, and rural areas. These models consider an array of factors, including distance, terrain, building structures, and interference sources, to accurately characterize the wireless channel [3]. The selection of an appropriate radio channel propagation model depends on several factors, including the frequency band, geographical region, and deployment scenario of the wireless network.…”

Section: Radio Wave Propagation Modelsmentioning

confidence: 99%

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Comparative Analysis for Radio Channel Propagation Models in the City of Tripoli/ Libya for 4G/LTE Networks

Abdurahman,

Salah,

Aljledi

et al. 2023

IJECER

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The accurate prediction of radio channel propagation is one of the most important factors for the design and optimization of wireless communication systems. Path loss is the key element to design appropriate propagation model. There are different propagation models used to predict path loss, however, inaccurate propagation model may result in unsatisfactory services for the Global System for Mobile communications (GSM) network. These include low data rates, high co-channel interference, and wasted received power.This paper presents a comparative analysis of radio channel propagation models specifically for urban environment. The aim is to evaluate and compare the performance of various models and accurately predict path loss and signal behavior in urban settings. The research focuses on adapting the Okumura-Hata model which is used by the Libya Telecom and Technology Company (LTT) for Long Term Evolution (LTE) technology in the GSM Band. This study is based on real time measurements collected in downtown Tripoli in Libya. It suggests considering other models, such as Standard Propagation Model (SPM), Cost-231, and Ericsson. Using MATLAB for simulation, the findings indicate that SPM model is the best fit especially when distance is over ~22 Km.

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“…In another paper presented by [72], five different empirical models-the FSPL, SUI model, Ericsson model, Okumura model, and COST-231 Hata model-were compared with empirical data measurements to find the best suitable model to predict path loss in the urban environment of Cologne, Germany, at 2.5 GHz. The analytical results showed that the COST-231 Hata model was the most suitable, with a minimum RMSE of 5.27 dB.…”

Section: Los and Nlos Indoormentioning

confidence: 99%

Performance of Path Loss Models over Mid-Band and High-Band Channels for 5G Communication Networks: A Review

Shaibu,

Onwuka,

Salawu

et al. 2023

Future Internet

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The rapid development of 5G communication networks has ushered in a new era of high-speed, low-latency wireless connectivity, as well as the enabling of transformative technologies. However, a crucial aspect of ensuring reliable communication is the accurate modeling of path loss, as it directly impacts signal coverage, interference, and overall network efficiency. This review paper critically assesses the performance of path loss models in mid-band and high-band frequencies and examines their effectiveness in addressing the challenges of 5G deployment. In this paper, we first present the summary of the background, highlighting the increasing demand for high-quality wireless connectivity and the unique characteristics of mid-band (1–6 GHz) and high-band (>6 GHz) frequencies in the 5G spectrum. The methodology comprehensively reviews some of the existing path loss models, considering both empirical and machine learning approaches. We analyze the strengths and weaknesses of these models, considering factors such as urban and suburban environments and indoor scenarios. The results highlight the significant advancements in path loss modeling for mid-band and high-band 5G channels. In terms of prediction accuracy and computing effectiveness, machine learning models performed better than empirical models in both mid-band and high-band frequency spectra. As a result, they might be suggested as an alternative yet promising approach to predicting path loss in these bands. We consider the results of this review to be promising, as they provide network operators and researchers with valuable insights into the state-of-the-art path loss models for mid-band and high-band 5G channels. Future work suggests tuning an ensemble machine learning model to enhance a stable empirical model with multiple parameters to develop a hybrid path loss model for the mid-band frequency spectrum.

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

Cited by 5 publications

References 26 publications

Description and analysis of Sigfox received signal strength indicator dataset by using statistical techniques

Description and analysis of Sigfox received signal strength indicator dataset by using statistical techniques

Comparative Analysis for Radio Channel Propagation Models in the City of Tripoli/ Libya for 4G/LTE Networks

Performance of Path Loss Models over Mid-Band and High-Band Channels for 5G Communication Networks: A Review

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