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SLIPT in Joint Dimming Multi-LED OWC Systems with Rate Splitting Multiple Access

Sepideh Javadi, Sajad Faramarzi, Farshad Zeinali, Hosein Zarini, Mohammad Robat Mili, Panagiotis D. Diamantoulakis, Eduard Jorswieck, George K. Karagiannidis

TL;DR

This work addresses energy efficiency and data-rate optimization in SLIPT-enabled optical wireless networks employing multiple LEDs by introducing a joint-dimming scheme to selectively activate LEDs. It combines RSMA to improve spectral efficiency and uses a PPO-based DRL approach to solve a non-convex, mixed-integer data-rate maximization problem under power, QoS, and energy-harvesting constraints. The proposed framework jointly optimizes beamforming, LED selection, and RSMA rate adaptation, with a model-free MDP formulation and a clipped surrogate PPO algorithm to ensure real-time operation. Numerical results show RSMA yields substantial rate gains and that there exists an optimal dimming level (around $\eta \approx 0.66$) that balances data rate and energy consumption, highlighting practical gains for energy-constrained indoor OWC deployments.

Abstract

Optical wireless communication (OWC) systems with multiple light-emitting diodes (LEDs) have recently been explored to support energy-limited devices via simultaneous lightwave information and power transfer (SLIPT). The energy consumption, however, becomes considerable by increasing the number of incorporated LEDs. This paper proposes a joint dimming (JD) scheme that lowers the consumed power of a SLIPT-enabled OWC system by controlling the number of active LEDs. We further enhance the data rate of this system by utilizing rate splitting multiple access (RSMA). More specifically, we formulate a data rate maximization problem to optimize the beamforming design, LED selection and RSMA rate adaptation that guarantees the power budget of the OWC transmitter, as well as the quality-of-service (QoS) and an energy harvesting level for users. We propose a dynamic resource allocation solution based on proximal policy optimization (PPO) reinforcement learning. In simulations, the optimal dimming level is determined to initiate a trade-off between the data rate and power consumption. It is also verified that RSMA significantly improves the data rate.

SLIPT in Joint Dimming Multi-LED OWC Systems with Rate Splitting Multiple Access

TL;DR

This work addresses energy efficiency and data-rate optimization in SLIPT-enabled optical wireless networks employing multiple LEDs by introducing a joint-dimming scheme to selectively activate LEDs. It combines RSMA to improve spectral efficiency and uses a PPO-based DRL approach to solve a non-convex, mixed-integer data-rate maximization problem under power, QoS, and energy-harvesting constraints. The proposed framework jointly optimizes beamforming, LED selection, and RSMA rate adaptation, with a model-free MDP formulation and a clipped surrogate PPO algorithm to ensure real-time operation. Numerical results show RSMA yields substantial rate gains and that there exists an optimal dimming level (around $\eta \approx 0.66$) that balances data rate and energy consumption, highlighting practical gains for energy-constrained indoor OWC deployments.

Abstract

Optical wireless communication (OWC) systems with multiple light-emitting diodes (LEDs) have recently been explored to support energy-limited devices via simultaneous lightwave information and power transfer (SLIPT). The energy consumption, however, becomes considerable by increasing the number of incorporated LEDs. This paper proposes a joint dimming (JD) scheme that lowers the consumed power of a SLIPT-enabled OWC system by controlling the number of active LEDs. We further enhance the data rate of this system by utilizing rate splitting multiple access (RSMA). More specifically, we formulate a data rate maximization problem to optimize the beamforming design, LED selection and RSMA rate adaptation that guarantees the power budget of the OWC transmitter, as well as the quality-of-service (QoS) and an energy harvesting level for users. We propose a dynamic resource allocation solution based on proximal policy optimization (PPO) reinforcement learning. In simulations, the optimal dimming level is determined to initiate a trade-off between the data rate and power consumption. It is also verified that RSMA significantly improves the data rate.
Paper Structure (17 sections, 23 equations, 5 figures, 1 table, 1 algorithm)

This paper contains 17 sections, 23 equations, 5 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Signal Model
  4. Channel Model
  5. JD Control
  6. Data Rate
  7. Energy Harvesting
  8. Problem Formulation
  9. Proposed DRL-based Approach
  10. MDP formulation
  11. State
  12. Action
  13. Reward Function
  14. The PPO-Based Analysis
  15. Simulation Results
  16. ...and 2 more sections

Figures (5)

  • Figure 1: An OWC system with an LED array, serving $K$ single-PD users for illumination, communication and EH.
  • Figure 2: Convergence: average reward vs the episode number.
  • Figure 3: System EE versus dimming level under $P_{\text{max}}=20~\text{Watts}$ and $\text{QoS}=3~\text{bits/sec}$.
  • Figure 4: Average system data rate versus the minimum QoS of users, under $P_{\text{max}}=20~\text{Watts}$, $K=4$, and $P^\text{Har}_{\text{min}}=10^{-8}~\text{Watts}$.
  • Figure 5: Average system data rate versus the minimum EH requirement under $P_{\text{max}}=20~\text{Watts}$, $K=4$, and $\text{QoS}=3~\text{bits/sec}$.