Resource Allocation in Uplink NOMA-IoT Based UAV for URLLC Applications.

Area of Science:

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

Background:

• Future 5G networks aim to expand Internet of Things (IoT) connectivity, facing challenges in bandwidth, power, and latency.
• Unmanned Aerial Vehicles (UAVs) are increasingly utilized as aerial base stations to improve wireless network performance.
• Non-Orthogonal Multiple Access (NOMA) is a key technology for enhancing multiple access capabilities.

Purpose of the Study:

• To develop a high-capacity IoT uplink network by integrating NOMA with UAVs.
• To optimize resource allocation for maximizing system throughput and minimizing IoT application delay.
• To investigate power allocation strategies for ensuring user fairness.

Main Methods:

• Formulation of a resource allocation problem for a NOMA-UAV integrated IoT network.
• Implementation of an algorithm to maximize system throughput and minimize application delay.
• Investigation of power allocation techniques to achieve user fairness.

Main Results:

• The proposed algorithm demonstrated a 31.8% improvement in delay and a 99.7% increase in reliability compared to the max CQI algorithm.
• A 50.8% enhancement in fairness was achieved while maintaining system sum rate and spectral efficiency.
• The algorithm proved effective in preserving system complexity.

Conclusions:

• The developed NOMA-UAV integrated algorithm offers superior performance for IoT connectivity in 5G networks.
• The proposed approach is suitable for ultra-reliable low-latency communication (URLLC) applications.
• This integration provides a robust solution for enhancing IoT network capacity, reliability, and fairness.