6G IoV Networks Driven by RF Digital Twin Modeling
Zengcan Liu, Houjun Sun, Gintare Marine, Hulin Wu
Abstract
Internet of Vehicles (IoV) is a crucial component of 6G mobile network, where energy efficiency is a major concern. To achieve green communication in IoV, this paper proposes a digital twin (DT) method and develops related machine learning-based energy-efficient approach. The channel model examined in this paper takes into account incident waves reflected by moving objects and the impacts of radio signals between various vehicles. 3D ray tracing is used to model the millimeter-wave channel in IoV to reflect radio frequency(RF)-domain digital twin matching. Finally, we present numerical results to justify the effectiveness of our proposed scheme.
Topics & Concepts
Computer scienceExtremely high frequencyRadio frequencyChannel (broadcasting)Energy (signal processing)Ray tracing (physics)Digital radioElectronic engineeringWirelessMobile radioComputer networkTelecommunicationsEngineeringPhysicsStatisticsMathematicsQuantum mechanicsMillimeter-Wave Propagation and ModelingAdvanced MIMO Systems OptimizationTelecommunications and Broadcasting Technologies