IEEE 802.11-15/0803r2 Frame Collision Management

IEEE 802.11-15/0803r2 Frame Collision Management
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Interference in 11ax scenarios poses a significant challenge, hindering the goals of 11ax. Implementing Frame Collision Information (FCI) can help reduce interference through effective management and control. This contribution outlines methods for FCI management and provides a practical use case example. In high-density scenarios, frame collisions escalate due to hidden terminals and simultaneous backoff completion. Frame Collision Detection (FCD) plays a crucial role in determining countermeasures to mitigate interference, such as site surveys and multi-rate control. Various FCD methods, including energy detection-based approaches, are discussed. FCI contains crucial collision timing information that aids in identifying collision causes, facilitating informed control countermeasure selection.

  • IEEE 802.11-15
  • Frame Collision Management
  • Interference Reduction
  • FCI Management
  • High-Density Scenarios

Uploaded on Mar 19, 2025 | 0 Views


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  1. Crazyflie Development at a High Level

  2. There are two(-ish) main ways to control the Crazyflie: The CF python library The CFClient (which in reality is just using the CF python library, but with a GUI) The app layer Both can make setpoints directly or work through the High Level Commander

  3. What are setpoints? Exact implementation can be found in src/modules/interface/stabilizer_types.h as setpoint_t 2 levels to control: Position(X, Y, Z), Attitude (pitch, roll, yaw) Each level has 3 different modes: Absolute mode, velocity mode, disabled

  4. High Level Commander The high level commander handles the actions (such as take off or go to ) passed to it by the CFlib or app It can use a planner to create a group of setpoints to create a trajectory for these high level action

  5. Interacting with the commander framework with CFlib Four ways, each has its own example in crazyflie-lib-python/examples/autonomy/ 1. 2. Send setpoints directly using commander class from Crazyflie object (autonomousSequence.py) The motionCommander class has a simplified API and sends velocity setpoints continuously based on methods called (motion_commander_demo.py) Using the high level commander directly using HighLevelCommanderClass on Crazyflie object (autonomous_sequence_high_level.py) Using PositionHlComander class for simplified API to send commands to high level commander (position_commander_demo.py) 3. 4.

  6. App channel When compiling Crazyflie with APP = 1 in the makefile, the firmware will call appMain() after the startup sequence appInit() can be used to set up anything before appMain() runs The app api communicates using packets. Implementation in src/modules/interface/app_channel.h Example of it being used in examples/app_appchannel_test/ App has access to params, logs, peer to peer capabilities

  7. Firmware that helps the commander

  8. Sensors On-board Sensors: Accelerometer: acceleration in body fixed coordinates in m/s2 Gyroscope: angle rate in roll, pitch, and yaw (rad/s) Pressure Sensor: Airpressure in mBar Flowdeck v2: Time of Flight sensor: Distance to a surface in millimeters Optical flow sensor: The detection movement of pixels in px per timesample Loco positioning deck: Ultra wide band module: The distance between two UWB modules or Time difference of arrival in meters Lighthouse deck: IR receivers: Sweep angle of htc vive basestations in radians

  9. State Estimators The state estimators use all the sensor data into an estimate of the state of the crazyflie. It is crucial for keeping the crazyflie stable and in the air. It uses two filters: the complementary filter and the extended Kalman filter

  10. State Controllers There are three types of controllers: PID controller, INDI controller, Mellinger controller As of right now PID is the only one available for use? Uses the difference between the state estimator and the setpoints given to the controller to request changes in the power distributor

  11. Cascaded PID Controller Setpoints get sent to the PID controller Attitude Rate PID: Affects gyroscope rates directly Attitude PID controller: Takes in estimates attitude from estimator and compares against setpoints desired attitude Position and Velocity PID controller: Takes in estimates from state estimator on position and velocity and compares against given setpoints

  12. Some lower level schematics

  13. More low level information

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