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--- exploring_lora [2018/09/29 13:35] – [4.1. Time on Air] samer
+++ exploring_lora [2018/09/29 17:29] – [4.2. Coverage] samer
@@ Line 118: / Line 118: @@
 In the following, you will design and implement a set of scenarios that enable to evaluate the performance of the LoRa modulation. As you will deal with scientific assessment, you are required to use scientific tools to show the results. You have the choice between [[http://www.gnuplot.info | gnuplot]], [[https://matplotlib.org/index.html#|matplotlib]] with Python, and MATLAB. Take some time to become familiar with one of these software as you will be required to use them in different occasions of your academic programme.
+As we are in presence of variable radio conditions, some experiments should be repeated multiple times and results can be shown as probability distributions. Take a look at this excellent repository of data visualisation tools [[https://www.data-to-viz.com]].
 ==== -. Time on Air ====
-In this section, you will measure the Time on Air (ToA) as given by the time necessary to transmit a message on the radio interface. You will assess the impact of the spreading factor, bandwidth, coding rate, the message size on the ToA.
+In this section, you will measure the Time on Air (ToA) as given by the time necessary to transmit a message on the radio interface. You will assess the impact of the spreading factor, bandwidth, coding rate, and the message size on the ToA.
-For this, you can start by implementing a function on the client that measures the time necessary for sending a message. For example, you can use the [[https://www.arduino.cc/en/Reference/Micros| micros()]] function available in the arduino libraries. As we are in presence of variable experimental conditions, experiments should be repeated.
+For this, you will start by implementing a function on the client that measures the time necessary for sending a message. For example, you can use the [[https://www.arduino.cc/en/Reference/Micros| micros()]] function available in the arduino libraries. Now, you can modify one of the parameters (spreading factor, bandwidth, coding rate, message size) and record the impact on the ToA. Note well that you may need to repeat the experiment in order to obtain the statistical distributions.
 <WRAP center round help 100%>
-  * Describe the scenarios you used for assessing the impact of radio parameters on the ToA. You can join commented extracts of your code.
+  * Describe the scenarios you used for assessing the impact of the different parameters on the ToA.
-  * Visualise the experimental results using for example [[http://www.physics.csbsju.edu/stats/box2.html | box plots]] of the ToA as a function of the different radio parameters.
+  * Join commented extracts of your code and raw data in attached files.
-  * Analyze the obtained results and compare with the theoretical computations. You can superpose the theoretical results and the practical ones on the same graph.
+  * Visualise the experimental results by plotting the ToA as a function of each one of the different parameters.
+  * Analyze the obtained results and compare with the theoretical computations. You can superpose the theoretical results and the experimental ones on the same graph.
 </WRAP>
-==== -. Packet Delivery Ratio ====
-In this section, you will measure the Packet Error Rate (PER) under the three different radio configurations and for different transmission periods. For this, you can start by implementing a function on the client that measures the ratio of successfully delivered packets.
+==== -. Coverage ====
-Only for this test, all groups are required to use the same frequency (for example 868.10 MHz).
+In this section, you will measure the coverage of LoRa under different radio configurations.
+For this, you will start by identifying a set of geographical locations or Test Points (TP). These TPs should be astutely chosen to explore the limits of LoRa coverage. Then you should implement a function on the server that measures the ratio of successfully delivered packets or PDR for three different radio configurations. Such configurations should ensure different reliability levels.
 <WRAP center round help 100%>
-  * Draw the PER as a function of the transmission period for the different radio configurations. Analyze your results.
+  * Draw the test points on a map and motivate your choices.
-  * What type of mathematical models enables to theoretically compute the PER?
+  * Visualise the experimental results by plotting the PDR for each TP and each radio configuration.
+  * Analyze the obtained results.
 </WRAP>
+==== -. [Classroom activity] Collisions and Packet Delivery Ratio ====
-==== -. Coverage ====
+In this section, you will measure the impact of collisions on the network throughput under different transmission periods.
+The setting for this experiment is unique:
-In this section, you will measure the coverage of LoRa devices under the three different radio configurations. For this, you can start by identifying a set of Test Points (TP) on the campus. Then, you should implement a function that sends packets with different radio configurations. Note that the following functions in the Arduino sketch enable to modify //on the fly// the LoRa parameters:
+  * Only one server is required in the classroom. This server should compute the ratio of successfully delivered packets or PDR.
+  * All groups are required to use the same frequency, spreading factor, and coding rate.
-<code c++>
-rf95.setModemConfig(RH_RF95::Bw125Cr45Sf128);
-rf95.setModemConfig(RH_RF95::Bw31_25Cr48Sf512);
-rf95.setModemConfig(RH_RF95::Bw125Cr48Sf4096);
-</code>
 <WRAP center round help 100%>
-  * Draw the test points on a map.
+  * Draw the PER as a function of the transmission period. Analyze your results.
-  * Give a statistical measure of the PER and the RSSI for each TP with each of the different radio configurations.
+  * What type of mathematical models enables to theoretically compute the PER?
 </WRAP>
-==== -. Path Loss ====
+===== -. Coverage Challenge =====
 In this section, you will study the properties of the radio channel as used by the LoRa technology. For this, you should obtain a large set of RSSI values for different distances, preferably in a free space setting.
@@ Line 168: / Line 170: @@
 In order to compute distances in your experiment, you can get the GPS coordinates as recorded by your smartphone using an application such as [[https://play.google.com/store/apps/details?id=com.flashlight.lite.gps.logger&hl=en|Ultra GPS Logger]]. You can export the time-location correspondence in a CSV format from this application. As for the time-RSSI correspondence, you can use a {{ :log-windows.py.zip |logger file}} on your laptop. Finally, the time matching enables you to obtain the RSSI for each GPS location, hence for different distances.
-===== -. Coverage Challenge =====