UAV Assisted Radio Resource Allocation in 6G Enabled V2X Networks

Abstract

In order to satisfy the growing demands of developing intelligent transportation systems (ITS), the wireless communication landscape is changing quickly. For real-time vehicular applications, users now need connectivity that is extremely dependable, low-latency, and high-capacity. Various frequency bands have unique benefits. While terahertz (THz) offers extremely high data rates and vast bandwidth, at the expense of high attenuation and short-range limitations, Macro Base Stations (MBS) guarantee long-range communication with dependable coverage. Unmanned aerial vehicles (UAVs), which offer dynamic coverage, line-of-sight (LoS) links, and load balancing in highly mobile environments, are introduced as flexible aerial base stations to overcome these trade-offs. For 6G-enabled Vehicle-to-Everything (V2X) communication, the proposed study designs a heterogeneous multi-tier network that combines macro base stations (MBS), unmanned aerial vehicles (UAVs), and THz small cells. By reducing handovers, offloading traffic, and preserving connectivity for fast-moving vehicles, UAVs support terrestrial infrastructure. The system performance is assessed using large-scale Monte Carlo simulations and modeling based on stochastic geometry. Energy efficiency, rate coverage probability, and signal-to-interference-plus-noise ratio (SINR) coverage probability are among the key performance indicators taken into consideration. According to the simulation results, THz links guarantee high data rates for short-range communication, while UAV deployment greatly increases coverage in congested vehicular environments. By lowering macro cell congestion and increasing fairness, association biasing improves load balancing across tiers. Reliability, throughput, and sustainability have all significantly improved with the suggested UAV-assisted RRM framework, underscoring its potential to enable effective and robust next-generation V2X systems.