Mobile Network Operators’ Coverage in Ecuador | by Bryan R. Vallejo | Jun, 2022
Geovisualization of Cellular Antenna’s development of 2G, 3G, and 4G
Since 2017, the OpenCell ID organization has been collecting the location of cellular antennas from the community around the world. This open data project contains ~3.3GB of data compressed worldwide and includes location attributes, mobile network operator code, coverage, and country code. The dataset helps public/private institutions to understand the pattern of antenna coverage. Nowadays, the USA is the country with the most coverage (as a number of cells) with ~7 million and followed by Germany with ~2 million.
The latest technology developed for telecommunication is the 5G which covers mobile broadband with data rates up to 20Gbps (much faster than traditional mobile technologies). The first country to commercialize 5G technology was South Korea in 2019 being nowadays the leader in this development.[1] The top 10 countries in 5G development by 2021 are South Korea, Norway, United Arab Emirates, Saudi Arabia, Qatar, Kuwait, Sweden, China, Taiwan, and New Zealand.
Ecuador is still failing to reach this technology and still heavily relies on 2G and 3G connections with samples over 20%. [2]
Every connection carried out on mobile phones is registered in the closer antenna. The calls, messages, and operations related to mobile data connection are stored in the cellular antenna where the mobile phone was used. At a national and global level, a huge volume of data is stored from millions of users that are clients of Mobile Network Operators. The data is anonymized and reflect mostly pings in different locations of the user.
Some companies have been clever in the analytical development of this huge volume of data. The insights of the analysis can reveal the flows of internal population, international tourism, and network statistics. Surprisingly, this analysis has been proved reliable by United Nations and can be used by National Statistics Offices around the world for Official Statistics.
The Estonian company Positium is the leader in mobile positioning data analytics for Human Mobility. Being present at the World Data Forum 2021, the private company talked about their actions taken to support the Covid-19 emergency situation with an innovative dashboard for population moves.
If you are willing to understand the outputs of the analysis of Mobile Positioning Data and its application I suggest you read this story:
This story is meant to show how to manipulate data from OpenCell ID and how to visualize it. In terms of classes:
- By Mobile Network Operator
- By technologies 2G, 3G (most used in Ecuador), and 4G
- By your own creativity
Find the country of your interest and download the data from Open Cell ID. Then you decompress the data like:
from datetime import datetime
import pandas as pd# read with Pandas
data = pd.read_csv(r’740.csv.gz’, header=None, compression=’gzip’)
The first issue with the country data is that it does not contain a column name. So to help you a bit you just add them like this:
# change columns of OpenCell
col_names = [‘radio’, ‘mcc’, ‘mnc’, ‘lac’, ‘cid’, ‘changeable_0’,
‘long’, ‘lat’, ‘range’, ‘sample’, ‘changeable_1’,
‘created’, ‘updated’, ‘avgsignal’]data.columns = col_names
Let’s add the generation 2G, 3G, and 4G and the Operator. For this practice, I will only use Movistar, Tuenti, and Claro.
# add generation
data[‘radio’] = data[‘radio’].replace(‘UMTS’, ‘3G’).replace(‘GSM’, ‘2G’).replace(‘LTE’, ‘4G’).replace(‘CDMA’, ‘3G’)# add operator
data = data.loc[data['mnc'].isin([0, 1, 3])]
data['mnc'] = data['mnc'].replace(0, 'Movistar').replace(1, 'Claro').replace(3, 'Tuenti')
So, it might be looking like:
The coverage by Operator:
Generally, all operator are connected to the antennas. Despite Tuenti shows a small amount of antennas (Sized by Coverage) it actually is connected to the entire network of cellular antennas. Claro is the Operator that seems to have more Infrastructure.
The coverage by Generation:
Seems that 2G and 3G are the dominants as it was said before. 4G is still in development. It can be seen that mostly it is developed in urban areas like Quito, Guayaquil, Cuenca, Manta, or Machala.
In the Galapagos Islands, 2G and 3G are the dominants as continental areas.
The coverage by Temporality:
I enjoy making messy maps.
The Open Cell ID is a source of open data that can help to analyze the distribution of Cellular Antenas at a worldwide level. But do not take it for granted. Some antennas seems to be located in the ocean or in the middle of the street. Is that right? Well, I believe as it is an open source dataset the protection of the real location can be altered. But still, good to have a reference, especially if we are working with geovisualization at a national level.
This practice can support to visualize the spatial distribution of Mobile Network Operators in different countries and the Technology Generation of their cellular antennas. So, just use this material to have a better overview of what it is going on in telecommunication development.
[1] Inter-American Development Bank. (2020). “5G the driver for the next generation digital society in Latin America and the Caribbean” This work is licensed under a Creative Commons IGO 3.0 Attribution-NonCommercial-NoDerivatives (CC-IGO BY-NC-ND 3.0 IGO) license ( https://creativecom — mons.org/licenses/by-nc-nd/3.0/igo/legalcode ) and may be reproduced with attribution to the IDB and for any non-commercial purpose. No derivative work is allowed
[2] Ookla (2021). “Growing and Slowing: The State of 5G Worldwide in 2021”. https://www.ookla.com/articles/state-of-worldwide-5g-2021#:~:text=5G%20slowed%20down%20at%20the%20global%20level&text=Over%20the%20past%20year%20from,Mbps)%20during%20the%20same%20period.
Geovisualization of Cellular Antenna’s development of 2G, 3G, and 4G
Since 2017, the OpenCell ID organization has been collecting the location of cellular antennas from the community around the world. This open data project contains ~3.3GB of data compressed worldwide and includes location attributes, mobile network operator code, coverage, and country code. The dataset helps public/private institutions to understand the pattern of antenna coverage. Nowadays, the USA is the country with the most coverage (as a number of cells) with ~7 million and followed by Germany with ~2 million.
The latest technology developed for telecommunication is the 5G which covers mobile broadband with data rates up to 20Gbps (much faster than traditional mobile technologies). The first country to commercialize 5G technology was South Korea in 2019 being nowadays the leader in this development.[1] The top 10 countries in 5G development by 2021 are South Korea, Norway, United Arab Emirates, Saudi Arabia, Qatar, Kuwait, Sweden, China, Taiwan, and New Zealand.
Ecuador is still failing to reach this technology and still heavily relies on 2G and 3G connections with samples over 20%. [2]
Every connection carried out on mobile phones is registered in the closer antenna. The calls, messages, and operations related to mobile data connection are stored in the cellular antenna where the mobile phone was used. At a national and global level, a huge volume of data is stored from millions of users that are clients of Mobile Network Operators. The data is anonymized and reflect mostly pings in different locations of the user.
Some companies have been clever in the analytical development of this huge volume of data. The insights of the analysis can reveal the flows of internal population, international tourism, and network statistics. Surprisingly, this analysis has been proved reliable by United Nations and can be used by National Statistics Offices around the world for Official Statistics.
The Estonian company Positium is the leader in mobile positioning data analytics for Human Mobility. Being present at the World Data Forum 2021, the private company talked about their actions taken to support the Covid-19 emergency situation with an innovative dashboard for population moves.
If you are willing to understand the outputs of the analysis of Mobile Positioning Data and its application I suggest you read this story:
This story is meant to show how to manipulate data from OpenCell ID and how to visualize it. In terms of classes:
- By Mobile Network Operator
- By technologies 2G, 3G (most used in Ecuador), and 4G
- By your own creativity
Find the country of your interest and download the data from Open Cell ID. Then you decompress the data like:
from datetime import datetime
import pandas as pd# read with Pandas
data = pd.read_csv(r’740.csv.gz’, header=None, compression=’gzip’)
The first issue with the country data is that it does not contain a column name. So to help you a bit you just add them like this:
# change columns of OpenCell
col_names = [‘radio’, ‘mcc’, ‘mnc’, ‘lac’, ‘cid’, ‘changeable_0’,
‘long’, ‘lat’, ‘range’, ‘sample’, ‘changeable_1’,
‘created’, ‘updated’, ‘avgsignal’]data.columns = col_names
Let’s add the generation 2G, 3G, and 4G and the Operator. For this practice, I will only use Movistar, Tuenti, and Claro.
# add generation
data[‘radio’] = data[‘radio’].replace(‘UMTS’, ‘3G’).replace(‘GSM’, ‘2G’).replace(‘LTE’, ‘4G’).replace(‘CDMA’, ‘3G’)# add operator
data = data.loc[data['mnc'].isin([0, 1, 3])]
data['mnc'] = data['mnc'].replace(0, 'Movistar').replace(1, 'Claro').replace(3, 'Tuenti')
So, it might be looking like:
The coverage by Operator:
Generally, all operator are connected to the antennas. Despite Tuenti shows a small amount of antennas (Sized by Coverage) it actually is connected to the entire network of cellular antennas. Claro is the Operator that seems to have more Infrastructure.
The coverage by Generation:
Seems that 2G and 3G are the dominants as it was said before. 4G is still in development. It can be seen that mostly it is developed in urban areas like Quito, Guayaquil, Cuenca, Manta, or Machala.
In the Galapagos Islands, 2G and 3G are the dominants as continental areas.
The coverage by Temporality:
I enjoy making messy maps.
The Open Cell ID is a source of open data that can help to analyze the distribution of Cellular Antenas at a worldwide level. But do not take it for granted. Some antennas seems to be located in the ocean or in the middle of the street. Is that right? Well, I believe as it is an open source dataset the protection of the real location can be altered. But still, good to have a reference, especially if we are working with geovisualization at a national level.
This practice can support to visualize the spatial distribution of Mobile Network Operators in different countries and the Technology Generation of their cellular antennas. So, just use this material to have a better overview of what it is going on in telecommunication development.
[1] Inter-American Development Bank. (2020). “5G the driver for the next generation digital society in Latin America and the Caribbean” This work is licensed under a Creative Commons IGO 3.0 Attribution-NonCommercial-NoDerivatives (CC-IGO BY-NC-ND 3.0 IGO) license ( https://creativecom — mons.org/licenses/by-nc-nd/3.0/igo/legalcode ) and may be reproduced with attribution to the IDB and for any non-commercial purpose. No derivative work is allowed
[2] Ookla (2021). “Growing and Slowing: The State of 5G Worldwide in 2021”. https://www.ookla.com/articles/state-of-worldwide-5g-2021#:~:text=5G%20slowed%20down%20at%20the%20global%20level&text=Over%20the%20past%20year%20from,Mbps)%20during%20the%20same%20period.
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