Digital Twin for UAV-RIS Assisted Vehicular Communication Systems

This paper investigates the issue of resource allocation for unmanned aerial vehicle and reconfigurable intelligent surface (UAV-RIS) assisted vehicular communication systems. To adapt the high dynamics of vehicular networks, we conceive a digital twin-based system over RIS-embedded environment towa...

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Bibliographic Details
Published in:IEEE transactions on wireless communications Vol. 23; no. 7; pp. 7638 - 7651
Main Authors: Wu, Mingming, Xiao, Yue, Gao, Yulan, Xiao, Ming
Format: Journal Article
Language:English
Published: New York IEEE 01.07.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Autonomous aerial vehicles
Communication systems
Communications systems
Digital twins
Discrete time systems
Dynamic programming
Dynamical systems
Fading
Linear programming
Mixed integer
Nonlinear programming
Optimization
Power consumption
Power demand
Power management
Quality of service
Quality of service architectures
reconfigurable intelligent surface
Reconfigurable intelligent surfaces
Reconfiguration
Resource allocation
unmanned aerial vehicle
Unmanned aerial vehicles
Vehicle dynamics
vehicular communications
Wireless communication
ISSN:1536-1276, 1558-2248, 1558-2248
Online Access:Get full text
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Summary:This paper investigates the issue of resource allocation for unmanned aerial vehicle and reconfigurable intelligent surface (UAV-RIS) assisted vehicular communication systems. To adapt the high dynamics of vehicular networks, we conceive a digital twin-based system over RIS-embedded environment towards environmental-aware communications. Specifically, a digital twin system can leverage data-driven models to predict the large-scale fading of future stages, while RIS is capable of controlling the propagation environments in real time, which can be utilized to mitigate prediction errors imposed by the small-scale fading. Using the capabilities of "prediction" and "reconfiguration", we expect to comprehensively foresee the dynamic changes in vehicular networks. In particular, the above-mentioned issue is formulated as a multi-slot total power consumption minimization problem under the quality of service (QoS) and energy constraints. Considering the finite battery energy of the UAV and the circuit power of the RIS, the transmit power of the UAV and the number of active reflecting elements (REs) are jointly scheduled for a finite time horizon. To tackle this mixed integer non-linear programming (MINLP) problem, we transform the original model into a discrete-time dynamic system. According to whether the dynamics of radio environments are predictable or not, the optimal offline and online policies are derived by using the deterministic and stochastic dynamic programming algorithms, respectively. To reduce the computation complexity, we further propose a novel online policy based on the idea of double-strategy selection. Finally, numerical results demonstrate that the proposed online policy exhibits near-optimal performances and outperforms other benchmarks in terms of transmission failure probability and effective power consumption.
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ISSN:1536-1276
1558-2248
1558-2248
DOI:10.1109/TWC.2023.3342991