Energy-efficient subchannel assignment and power allocation in VLC-IoT systems with SLIPT

Area of Science:

• Wireless Communication
• Energy Harvesting
• Internet of Things

Background:

• Visible Light Communication (VLC) systems offer high bandwidth and energy efficiency.
• Integrating Internet of Things (IoT) devices with VLC enables simultaneous information and power transfer (SLIPT).
• Optimizing energy efficiency (EE) in SLIPT-VLC-IoT systems is crucial for sustainable operation.

Purpose of the Study:

• To investigate joint subchannel assignment and power allocation for EE optimization in SLIPT-VLC-IoT systems.
• To address the challenges posed by a complex mixed-integer fractional nonlinear programming problem.
• To develop efficient schemes for resource management in these advanced communication systems.

Main Methods:

• Formulated a mixed-integer fractional nonlinear programming problem for EE optimization.
• Decomposed the problem into subchannel assignment and power allocation subproblems.
• Proposed a virtual cell formation and subchannel assignment (VCF-SA) scheme.
• Developed a quadratic transformation-based power allocation (QTBPA) scheme to solve the fractional programming problem iteratively.

Main Results:

• The proposed VCF-SA and QTBPA schemes effectively optimize energy efficiency.
• Simulation results demonstrate superior EE performance compared to existing benchmarks.
• Analysis provided insights into the impact of various system parameters on EE.

Conclusions:

• The developed joint optimization framework significantly enhances EE in SLIPT-VLC-IoT systems.
• The proposed iterative approach provides a viable solution for complex resource allocation problems.
• This research contributes to the advancement of energy-efficient wireless communication technologies.