lora_radio_coverage
Differences
This shows you the differences between two versions of the page.
Both sides previous revisionPrevious revisionNext revision | Previous revisionNext revisionBoth sides next revision | ||
lora_radio_coverage [2016/10/15 17:13] – [3. Experiment Settings and Data Analysis] samer | lora_radio_coverage [2016/10/27 09:26] – [2. Software Platform] samer | ||
---|---|---|---|
Line 20: | Line 20: | ||
===== -. Software Platform ===== | ===== -. Software Platform ===== | ||
- | For basic hands-on with the prototype devices, you can refer to the article [[simple_lora_prototype|Simple Prototype of LoRa Communications]]. Start by downloading the {{ : | + | For basic hands-on with the prototype devices, you can refer to the article [[simple_lora_prototype|Simple Prototype of LoRa Communications]]. Start by downloading the {{ : |
==== -. Base station ==== | ==== -. Base station ==== | ||
- | The software package on the base station is forked from [[https:// | + | The software package on the base station is forked from [[https:// |
<WRAP center round tip 60%> | <WRAP center round tip 60%> | ||
Line 30: | Line 30: | ||
</ | </ | ||
- | Now, you can run the {{ :log.py.zip |log.py}} script on the base station computer. This script reads data from the USB interface connected to the Arduino and outputs the received power in a CSV text file. | + | Now, you can run the {{ :log.py.zip |log.py}} script on the base station computer. This script reads data from the USB interface connected to the Arduino and outputs the received power in a CSV text file for each successful LoRa transmission. |
- | For the script to work, you should make sure to specify the adequate interface on your computer in the python source file. The following is an example with an Arduino Uno connected to Mac OS: | + | For the script to work, you should make sure to specify the adequate interface on your computer in the python source file. The following |
<file py log.py> | <file py log.py> | ||
Line 51: | Line 51: | ||
==== -. Mobile Device ==== | ==== -. Mobile Device ==== | ||
- | On the mobile device side, you should install and run [[https:// | + | On the mobile device side, you should install and run [[https:// |
- | {{: | + | {{: |
- | {{: | + | {{: |
- | {{: | + | {{: |
- | {{: | + | {{: |
Line 62: | Line 62: | ||
===== -. Experiment Settings and Data Analysis ===== | ===== -. Experiment Settings and Data Analysis ===== | ||
- | During the coverage test on the USJ CST campus, we placed the base station in a third floor classroom in one of the highest building of the campus. As mentioned before, the connected computer logs periodically timestamps and information on the received signal power. We carried the mobile device around the campus walking slowly so that the LoRa transmission and the GPS update can take place. | + | During the coverage test on the USJ [[http:// |
- | After the end of the walk, GPS data can be exported form the GPS essentials application | + | After the end of the walk, GPS data was exported form the GPS essentials application as in the following screenshot. |
- | {{ : | + | {{ : |
- | Let us rename the obtained | + | Let us rename the exported |
- | Sort by transforming the GPX (XML GPS format) to CSV with the following command: | + | Start by transforming the GPX (XML GPS format) to CSV with the following command: |
<code bash> | <code bash> | ||
python gpx_to_csv.py ./ | python gpx_to_csv.py ./ | ||
</ | </ | ||
- | Then, merge the GPS data with the log file by perform | + | Then, merge the GPS data with the log file by performing |
<code bash> | <code bash> | ||
python timing_match.py ./ | python timing_match.py ./ | ||
Line 84: | Line 84: | ||
</ | </ | ||
===== -. Coverage Results ===== | ===== -. Coverage Results ===== | ||
- | {{: | + | |
+ | Figure 3 depicts a typical output of the coverage test campaign. The base station is represented on the map. Green line correspond to good signal reception, while red line identify the communication drops between the mobile device and the base station. | ||
+ | |||
+ | [{{ : | ||
+ | |||
+ | ===== -. Lessons and Future Works ===== | ||
+ | This basic coverage test shows the exciting performance of the LoRa technology: | ||
+ | * We successfully covered large parts of the campus with a very small transmission device placed indoors. Can you imagine the same with WiFi/ | ||
+ | * The mobile device is powered by a smartphone. We expect small LoRa end-devices to work on a battery for years. Can you imagine the same with GPRS, 3G, or 4G devices? | ||
+ | * The test is performed with a spreading factor of 7, we expect more robust communication (thus, larger coverage) when using higher spreading factors. | ||
+ | * The indoor base station has an omnidirectional antenna with 3dBi gain, we expect larger coverage with directional rooftop antennas. | ||
+ | |||
+ | The first academic LoRa network deployed by USJ will be an excellent trial field to get more insights on the performance of this very promising technology. The future tests will enable to study the properties of the radio channel in the 868 MHz bandwidth, with a special focus on the vineyard agricultural environment. |
lora_radio_coverage.txt · Last modified: 2021/08/28 09:49 by samer