Is it possible to define a different energy detection threshold for each interface in a WLAN node?

Hello,

I am trying to simulate a swarm of drones for a search and rescue scenario using UAV and WLAN toolboxes. The scenario is described in the figure:

The drones communicate through WiFi, using one interface to communicate with ground stations, and another interface to communicate between them. It is a FANET for which I am trying to test UAV mobility models aimed at improving coverage and maintaining connectivity between ground nodes and a control station. The first question is: Considering that the interfaces are in two different frequency bands, is it possible to define a different energy detection threshold for each interface in a WLAN node? According to the documentation, the EDThreshold field is numeric scalar, so if the answer to the first question is NO, the second question is: Is there an alternative where I can change the energy detection threshold depending on the frequency band? Finally, I need to test performance parameters such as MACThroughput, AppAvgPacketLatency, and PacketLossRatio between the ground nodes and the control station. Right now, I was able to obtain those statistics between the AP (on the UAV) and the ground node, but I need them to be end-to-end (ground node to-UAV-to-control station). The third and fourth questions are: How can I define a mesh network between the aerial nodes? Does it depend only on the traffic confugurations or should I use the addPath function?

I appreciate your help.

Answer 1

[SANKALP DEV]

Hi William,

I understand that you are currently working on a simulation project involving a swarm of drones for a search and rescue scenario, utilizing UAV and WLAN Toolboxes. Here are some insights and recommendations for your questions:

• The WLAN Toolbox does not inherently allow for the definition of distinct energy detection thresholds for individual interfaces within a WLAN node. The 'EDThreshold' parameter is a single numeric value that applies universally to the entire node.
• To adapt the energy detection threshold based on the frequency band, a custom solution is required. This entails modifying the WLAN node's behaviour by either creating a custom node model or extending existing functionality. Such customization involves programming and fine-tuning to accommodate different thresholds according to the frequency band. Utilize WLAN Toolbox APIs and functions to access and manipulate the relevant parameters.
• Establishing a mesh network among aerial nodes (drones) in your simulation can be achieved using the 'addMeshPath' function provided by the WLAN Toolbox. This function facilitates the creation of communication paths between nodes, specifying source and destination nodes, as well as defining path properties such as path loss, shadowing, and fading characteristics. By utilizing 'addMeshPath,' you can design the desired mesh network topology between the drones effectively.
• To measure end-to-end performance metrics like 'MACThroughput,' 'AppAvgPacketLatency,' and 'PacketLossRatio' between ground nodes and the control station in your simulation, you need to comprehensively model the entire network. This includes ground nodes, aerial drones, and the control station. Simulate the network's behaviour and collect statistical data to assess these performance parameters accurately.

For more in-depth information on UAV and WLAN Toolboxes, I recommend referring to the official MATLAB documentations:

'UAV' - UAV Toolbox Documentation (mathworks.com)

'WLAN' - WLAN Toolbox — Functions (mathworks.com)

I hope this gives you a better insight on how to effectively utilize UAV and WLAN toolboxes to achieve your goals.

Best regards,

Sankalp