Exploiting User Clustering and Fixed Power Allocation for Multi-Antenna UAV-Assisted IoT Systems.

Area of Science:

• Wireless Communication
• Internet of Things (IoT)
• Aerial Networks

Background:

• IoT systems increasingly rely on Unmanned Aerial Vehicles (UAVs) for enhanced connectivity and coverage.
• Integrating multi-antenna UAVs with Non-Orthogonal Multiple Access (NOMA) offers a promising approach to boost IoT device performance and transmission reliability.

Purpose of the Study:

• To investigate user clustering and power allocation strategies for multi-antenna UAV-mounted relays in IoT networks.
• To analyze the impact of antenna selection techniques (Maximum Ratio Transmission and Best Selection) on system performance.
• To evaluate the performance of the proposed system in practical scenarios with and without direct base station links.

Main Methods:

• Derivation of closed-form expressions for Outage Probability (OP) and Ergodic Capacity (EC) for IoT devices.
• Comparative analysis of two multi-antenna UAV scenarios: Maximum Ratio Transmission and Best Selection.
• Performance evaluation under Nakagami-m fading conditions.
• Comparison with Orthogonal Multiple Access (OMA) schemes.

Main Results:

• The number of antennas on UAVs critically impacts system performance.
• Outage Probability (OP) decreases with increasing Signal-to-Noise Ratio (SNR), antenna count, and fading severity.
• The proposed NOMA-based UAV relay system demonstrates superior outage performance compared to OMA.
• Analytical results are validated through Monte Carlo simulations.

Conclusions:

• Multi-antenna UAV-mounted relays combined with NOMA effectively enhance IoT system reliability and performance.
• Antenna selection strategies offer a cost-effective way to leverage multi-antenna benefits.
• The proposed system provides a significant improvement over OMA, particularly in outage performance.