Joint Trajectory and IRS Phase Shift Optimization for Dual IRS-UAV-Assisted Uplink Data Collection in Wireless Sensor...

Area of Science:

• Wireless Communication
• Network Engineering
• Robotics

Background:

• Intelligent reflecting surface-assisted unmanned aerial vehicles (IRS-UAVs) are increasingly vital in communication systems.
• Wireless sensor networks (WSNs) face challenges in uplink data transmission efficiency.

Purpose of the Study:

• To propose a novel double IRS-UAVs assisted framework to enhance uplink communication in WSNs.
• To maximize the pairwise sum rate while ensuring quality of service (QoS) constraints are met.

Main Methods:

• A joint optimization algorithm was developed to simultaneously optimize UAV trajectories and IRS phase shifts.
• Slack variables were introduced to linearize nonlinear constraints, enabling iterative subproblem solving.
• A coordinated optimization framework was employed for iterative refinement of solutions.

Main Results:

• The proposed algorithm effectively optimizes UAV flight trajectories.
• Significant improvements in the system's pairwise total rate were achieved, outperforming traditional schemes by 11.91% and 16.36% on average.
• The framework successfully balances maximizing sum rate with meeting QoS requirements.

Conclusions:

• The double IRS-UAVs framework offers a superior solution for uplink communication in WSNs.
• Joint optimization of UAV trajectories and IRS phase shifts is crucial for performance enhancement.
• The proposed method provides a robust and efficient approach to improving wireless communication rates.