scholarly journals Better coverage, better outcomes? Mapping mobile network data to official statistics using satellite imagery and radio propagation modelling

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0241981
Author(s):  
Till Koebe
Keyword(s):  
Satellite Imagery ◽  
Voronoi Tessellation ◽  
Mobile Network ◽  
Radio Propagation ◽  
Network Coverage ◽  
Sources Of Information ◽  
Real World Application ◽  
Modelling Techniques ◽  
Data Source ◽  
Propagation Modelling

Mobile sensing data has become a popular data source for geo-spatial analysis, however, mapping it accurately to other sources of information such as statistical data remains a challenge. Popular mapping approaches such as point allocation or voronoi tessellation provide only crude approximations of the mobile network coverage as they do not consider holes, overlaps and within-cell heterogeneity. More elaborate mapping schemes often require additional proprietary data operators are highly reluctant to share. In this paper, I use human settlement information extracted from publicly available satellite imagery in combination with stochastic radio propagation modelling techniques to account for that. I show in a simulation study and a real-world application on unemployment estimates in Senegal that better coverage approximations do not necessarily lead to better outcome predictions.

scholarly journals Analysis of 4G mobile network coverage in UTeM technology campus

2020 ◽  
Vol 18 (2) ◽  
pp. 882
Author(s):  
Zahariah Manap ◽  
Anis Suhaila Mohd Zain ◽  
Rahaini Mohd Said ◽  
Shawn Shivaneson Balakirisnan
Keyword(s):  
Open Source Software ◽  
Mobile Network ◽  
Propagation Loss ◽  
Network Coverage ◽  
Received Signal Strength Indicator ◽  
Signal Degradation ◽  
Two Factors ◽  
Grid Points ◽  
Coverage Profile ◽  
Better Than

<p><span>This paper proposes an analysis of the coverage performance of 4G cellular services in UTeM Technology Campus. The performance of the cellular services is presented as the network’s coverage profile which is based on the received signal strength indicator (RSSI). The area under study is virtually divided into 64 grid points where the average RSSI measurements are captured by using an open source software namely G-Mon. The measured values are mapped into the network coverage profile which represents the signal reception quality at each of the grid points. A statistical analysis called Two-Way ANOVA is performed to investigate the correlation of the performance of 4G cellular services in UTeM Technology Campus with the mobile phone brands and service operators. Based on the analysis, it is found that the signal reception in outdoor areas are better than that of indoor areas. In addition, the analysis shows that the propagation loss and signal degradation are two factors that contribute to the 4G services’ performance in UTeM Technology Campus. </span></p>

Individual growth estimation of Ucides occidentalis (Brachyura, Ocypodidae) in the Gulf of Guayaquil, Ecuador by indirect methods and multi-model selection

Crustaceana ◽  
2016 ◽  
Vol 89 (13) ◽  
pp. 1509-1524 ◽  
Author(s):  
René Zambrano ◽  
E. Alberto Aragón-Noriega ◽  
Gabriela Galindo-Cortes ◽  
Lourdes Jiménez-Badillo ◽  
Manuel Peralta
Keyword(s):  
Growth Models ◽  
Stock Assessment ◽  
Individual Growth ◽  
Sources Of Information ◽  
Indirect Methods ◽  
Frequency Distributions ◽  
Capture Recapture ◽  
Data Source ◽  
Gulf Of Guayaquil ◽  
Growth Estimation

Ucides occidentalis (Ortmann, 1897) is a commercial crab in the Ecuadorian continental coast, however, little knowledge is available about its biology. A very important aspect for stock assessment and fisheries management is the species’ individual growth. In this paper U. occidentalis growth in males and females was determined by indirect methods and the multi-model approach. By Kernel density estimators size frequency distributions were built, separating their Gaussian components by the Bhattacharya’s method. Using modal progression, the cohorts were identified, and one was selected to apply asymptotic, non-asymptotic, and Schnute’s versatile growth models. The best fit model was selected using the Akaike and Bayesian weights. Case 1 of Schnute was the winner model in both sexes, asymptotic in males with cephalothorax width (CW), and , but it was non-asymptotic for females with an inflexion point in 2.49 years that corresponded to 73.72 mm CW. The type of individual growth of this species varies between sexes, which may be linked to reproductive issues; however, we should consider the data source and their impact on the interpretations that we can draw about individual growth. Therefore, for future studies, using other sources of information such as commercial catches or capture-recapture to validate the results presented, is recommended.

Radio propagation modelling in the downlink LTE

2010 ◽  
Author(s):  
Andrew Deroussent ◽  
Kumbesan Sandrasegaran ◽  
Huda Adibah Mohd Ramli ◽  
Riyaj Basukala
Keyword(s):  
Radio Propagation ◽  
Propagation Modelling

scholarly journals 5G uplink interference simulations, analysis and solutions: The case of pico cells dense deployment

2021 ◽  
Vol 11 (3) ◽  
pp. 2245
Author(s):  
Balboul Younes ◽  
Fattah Mohammed ◽  
Mazer Saïd ◽  
Moulhime El Bekkali
Keyword(s):  
High Speed ◽  
Mobile Network ◽  
Industrial Applications ◽  
Wireless Transmission ◽  
Interference Avoidance ◽  
Network Coverage ◽  
5G Network ◽  
Radio Resources ◽  
Flexible Management ◽  
The Internet Of Things

The launch of the new mobile network technology has paved the way for advanced and more productive industrial applications based on high-speed and low latency services offered by 5G. One of the key success points of the 5G network is the available diversity of cell deployment modes and the flexibility in radio resources allocation based on user’s needs. The concept of Pico cells will become the future of 5G as they increase the capacity and improve the network coverage at a low deployment cost. In addition, the short-range wireless transmission of this type of cells uses little energy and will allow dense applications for the internet of things. In this contribution, we present the advantages of using Pico cells and the characteristics of this type of cells in 5G networks. Then, we will do a simulation study of the interferences impact in uplink transmission in the case of PICO cells densified deployment. Finally, we will propose a solution for interference avoidance between pico cells that also allows flexible management of bands allocated to the users in uplink according to user’s density and bandwidth demand.

scholarly journals Challenges for Methods of Teaching English Vocabulary to Non-native Students

2020 ◽  
Vol 7 (5) ◽  
pp. 556-575
Author(s):  
Omer Elsheikh Hago Elmahdi ◽  
Abdulrahman Mokbel Mahyoub Hezam
Keyword(s):  
Relevant Literature ◽  
Careful Analysis ◽  
Native Students ◽  
Sources Of Information ◽  
Teaching English ◽  
Record Keeping ◽  
Data Source ◽  
Definition Of ◽  
New Research ◽  
Teaching Learning

This study is meant to have a through argument about the main topic of this research, which is the challenges of teaching methods of English vocabulary to non-native students. The researchers try to introduce a conceptual coverage of certain areas that are relevant to English vocabulary teaching / learning. This conceptual coverage includes: the definition of the term vocabulary, kinds of vocabulary, the importance of vocabulary, general principles for successful vocabulary teaching, teaching vocabulary in the English as a foreign language (EFL) context is challenging, techniques of teaching vocabulary, and the need for teaching vocabulary. Among the qualitative methods the researchers chose the record keeping method. This method makes use of the already existing reliable documents and similar sources of information as the data source. This data can be used in a new research. The researchers have collected a number of relevant studies and quarrying critically and deeply in these studies to signal out the Challenges for Methods of Teaching English Vocabulary to Non-native Students. Qualitative data collection allows collecting data that is non-numeric and helps us to explore how decisions are made and provide a detailed insight. For reaching such conclusions the data that is collected should be holistic, rich and nuanced and findings to emerge through careful analysis. This is why the researchers have examined and collected many relevant references, case studies that deal with teaching vocabulary.  To carry out this research the researchers have introduced certain questions and surveyed a huge number of previous studies after covering the relevant literature. Finally, the challenges that are critically obtained by the researchers are classified into three main categories. The first category, challenges related to students, the second one, challenges related to teachers, and the third one, challenges related to methods/ techniques/ strategies of teaching vocabulary.

scholarly journals An Expedient, Generalizable and Realistic Data-Driven Indoor Propagation Model

2021 ◽  
Author(s):  
Stefanos Sotirios Bakirtzis ◽  
Jiming Chen ◽  
Kehai Qiu ◽  
Jie Zhang ◽  
Ian Wassell
Keyword(s):  
Measurement Data ◽  
Wireless Channel ◽  
Propagation Model ◽  
Radio Propagation ◽  
Data Driven ◽  
Indoor Environments ◽  
Real World Data ◽  
Propagation Models ◽  
Frequency Bands ◽  
Propagation Modelling

Efficient and realistic indoor radio propagation modelling tools are inextricably intertwined with the design and operation of next generation wireless networks. Machine learning (ML)-based radio propagation models can be trained with simulated or real-world data to provide accurate estimates of the wireless channel characteristics in a computationally efficient way. However, most of the existing research on ML-based propagation models focuses on outdoor propagation modelling, while indoor data-driven propagation models remain site-specific with limited scalability. In this paper we present an efficient and credible ML-based radio propagation modelling framework for indoor environments. Specifically, we demonstrate how a convolutional encoder-decoder can be trained to replicate the results of a ray-tracer, by encoding physics-based information of an indoor environment, such as the permittivity of the walls, and decode it as the path-loss (PL) heatmap for an environment of interest. Our model is trained over multiple indoor geometries and frequency bands, and it can eventually predict the PL for unknown indoor geometries and frequency bands within a few milliseconds. Additionally, we illustrate how the concept of transfer learning can be leveraged to calibrate our model by adjusting its pre-estimate weights, allowing it to make predictions that are consistent with measurement data. <br>

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