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The first unofficial implementation of a paper with the title of "UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices" (IEEE Transactions on Wireless Communications 2019)

Home Page: https://ieeexplore.ieee.org/document/8842600

License: MIT License

MATLAB 100.00%
optimization path-planning resource-allocation trajectory-planning uav convex-optimization

uav-trajectory-planning's Introduction

Reproducing "UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices"

The first unofficial implementation of a paper with the titled "UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices". In this repository, I implemented a sub-optimal algorithm based on successive convex approximation (SCA) as introduced by Samir et al. (2019). Specifically, I reproduced the Figure 3 in the paper, where the goal is to optimize the UAV trajectory and allocation of resources to maximize the total number of served IoT devices within a flight mission duration based on a given set of target time constraints.

image

Paper: M. Samir, S. Sharafeddine, C. M. Assi, T. M. Nguyen and A. Ghrayeb, "UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices," in IEEE Transactions on Wireless Communications, vol. 19, no. 1, pp. 34-46, Jan. 2020, doi: 10.1109/TWC.2019.2940447. > https://ieeexplore.ieee.org/document/8842600

Summary

I summarize the paper and the implementation in this slides

optimization-problem

How to execute the code

  1. Install CVX on MATLAB : http://cvxr.com/cvx/download/
  2. Change rician variable in the main.m to true or false as needed
  3. Execute the matlab code, i.e., main.m

If the plot is not displayed after the iteration is completed, please execute this in the command window:

hold on; scatter(X, Y, 10, 'b');scatter(device_X, device_Y,50, 'r'); xlim([0 800]);ylim([0 800]); text(device_X, device_Y, split(num2str(deadline))); hold off

Reproduced Results

Rician Channel

rician_figure

Path-loss Channel

path_loss_figure

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uav-trajectory-planning's Issues

The rate

(alpha*((Pch_power_gain(abs(h(i,n))^2))/noise_power), Here isn't it linear instead of dB?

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