UAV-Assisted Partial Co-Operative NOMA-Based Resource Allocation in CV2X and TinyML-Based Use Case Scenario

The evolution of Internet of Vehicles (IoV) from Internet of Things (IoT) has revolutionized Smart cities, enabling vehicle communication for safety and traffic information dissemination. However, fulfilling time-sensitive applications like safety alerts via Cellular Vehicle-to-Everything (C-V2X) faces resource constraints. This study presents a nonorthogonal multiple access (NOMA)-based resource allocation for C-V2X in ultradense networks (UDNs). This article has also discussed the role of tiny machine learning (TinyML) in unmanned aerial vehicle (UAV) and it is demonstrated with use case scenario. Additionally, a generalized expression for scheduling time fraction is derived for the proposed scheme. The proposed framework optimizes power allocation, accommodating high-speed users and UAV scenarios to improve performance in obstructed regions. Numerical analysis demonstrates an approximate 85% throughput increase over conventional schemes, affirming the efficiency of the NOMA-based approach for enhanced C-V2X performance.