Resource management for multi-drone communications in next-generation NOMA-enabled wireless networks

Area of Science:

• Wireless Communication Networks
• Network Optimization
• Aerial Communication Systems

Background:

• Unmanned Aerial Drones (UADs) are crucial for next-generation wireless networks, providing flexible coverage for remote and emergency situations.
• Challenges in UAD networks include high latency, low spectral efficiency, and fairness issues among multiple drones.
• Existing solutions often struggle with the complexity of optimizing UAD-user associations and power allocation.

Purpose of the Study:

• To develop an optimization framework for multi-UAD communication networks utilizing Non-Orthogonal Multiple Access (NOMA).
• To address challenges of high latency, low spectral efficiency, and fairness in UAD networks.
• To maximize spectral efficiency by optimizing ground user-to-UAD associations and drone power allocation.

Main Methods:

• Developed a framework for optimizing multi-UAD communication networks based on NOMA.
• Addressed the complex mixed-integer, nonconvex, and nonlinear optimization problem.
• Implemented a two-stage optimization: first UAD-user associations, then NOMA power allocation for each user.

Main Results:

• The proposed NOMA framework significantly outperforms traditional Orthogonal Multiple Access (OMA) methods.
• Achieved improved spectral efficiency compared to benchmark NOMA techniques.
• Demonstrated lower complexity and faster convergence in numerical simulations.

Conclusions:

• The optimization framework effectively enhances spectral efficiency and overall performance in multi-UAD networks.
• The proposed NOMA-based approach offers a superior solution compared to OMA and other NOMA techniques.
• This framework provides a robust and efficient method for improving UAD network connectivity in dynamic environments.