exploring_lora
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exploring_lora [2018/09/29 13:35] – [4.1. Time on Air] samer | exploring_lora [2018/09/29 15:44] – samer | ||
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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:// | 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:// | ||
+ | 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:// | ||
==== -. Time on Air ==== | ==== -. 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:// | + | 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:// |
<WRAP center round help 100%> | <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 |
- | * Visualise the experimental results | + | * 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 | + | * Visualise the experimental results |
+ | * Analyze the obtained results and compare with the theoretical computations. You can superpose the theoretical results and the experimental | ||
</ | </ | ||
- | ==== -. 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 |
+ | |||
+ | For this, you will start by identifying a set of geographical locations or Test Points (TP). These TPs should be astutely chosen to challenge the limits of LoRa transmission. Then you should implement a function on the server that measures the ratio of successfully delivered packets or PDR. | ||
<WRAP center round help 100%> | <WRAP center round help 100%> | ||
- | * Draw the PER as a function of the transmission period for the different | + | * Draw the test points on a map and motivate your choices. |
- | * What type of mathematical models enables to theoretically compute | + | * Visualise |
+ | * Analyze | ||
</ | </ | ||
- | ==== -. Coverage | + | ==== -. [Classroom activity] Collisions and Packet Delivery Ratio ==== |
+ | In this section, you will measure the impact of collisions on the network throughput under different transmission periods. | ||
- | 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: | + | The setting for this experiment is unique: |
- | <code c++> | + | * Only one server is required in the classroom. This server should compute the ratio of successfully delivered packets or PDR. |
- | rf95.setModemConfig(RH_RF95:: | + | * All groups are required to use the same frequency, spreading factor, and coding rate. |
- | rf95.setModemConfig(RH_RF95:: | + | |
- | rf95.setModemConfig(RH_RF95:: | + | |
- | </ | + | |
<WRAP center round help 100%> | <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 | + | * What type of mathematical models enables to theoretically compute |
</ | </ | ||
- | ==== -. 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. | 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. | ||
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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:// | 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:// | ||
- | ===== -. Coverage Challenge ===== | ||
exploring_lora.txt · Last modified: 2021/10/20 12:52 by samer