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Multiplexing B5G/6G Services over Aerial VLC Networks: A Comprehensive Radio Resource Management Framework

Zarini, H ; Sharif University of Technology | 2024

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  1. Type of Document: Article
  2. DOI: 10.1109/JIOT.2024.3523016
  3. Publisher: 2024
  4. Abstract:
  5. Downlink transmission of a non-orthogonal visible light communication system, empowered by unmanned aerial vehicles (UAVs), is studied for coexisting enhanced mobile broadband (eMBB), ultra-reliable low-latency communication (URLLC), and massive machine-type communication (mMTC) services. A joint resource allocation problem involving user association, transmit power, and flight trajectory of UAVs is formulated, with the goal of characterizing a multi-objective trade-off as a weighted sum of the power consumption of each UAV and the perceived quality of experience (QoE) of its associated eMBB users, while ensuring the service-specific requirements for eMBB, mMTC, and URLLC are met. Assuming the imperfection of channel state information, we invoke a generalized Benders decomposition (GBD) methodology, leveraging tools from convex optimization and multi-agent deep reinforcement learning to address this problem. We further analytically derive the upper and lower bounds on the reward function for each UAV as a learning agent. Extensive simulations confirm that our proposed method outperforms the single-agent counterpart in the literature, with up to a 22% reduction in power consumption and a 13% gain in perceived QoE. Additionally, compared to the globally optimal brute-force method for UAV-user association, our proposed method experiences only a trivial performance loss in a small-scale scenario. © 2014 IEEE
  6. Keywords:
  7. Enhanced mobile broadband (eMBB) ; Massive machine type communication (mMTC) ; Ultra-reliable low latency communication (URLLC) ; Unmanned aerial vehicle (UAV) ; Visible light communication (VLC) ; Aircraft communication ; Benchmarking ; Deep reinforcement learning ; Dynamic programming ; Health risks ; Light transmission ; Linear programming ; Mobile telecommunication systems ; Nonlinear programming ; Orthogonal functions ; Quality of service ; Radio communication ; Rayleigh fading ; Reinforcement learning ; Resource allocation ; Risk analysis ; Risk assessment ; Scales (weighing instruments) ; Stochastic programming ; Aerial vehicle ; Low-latency communication ; Machinetype communication (MTC) ; Mobile broadband ; Visible light ; Convex optimization
  8. Source: IEEE Internet of Things Journal ; 2024 ; 23274662 (ISSN)
  9. URL: https://ui.adsabs.harvard.edu/abs/2025IITJ...1211600Z/abstract