Graph-based multi-user scheduling for indoor cooperative visible light transmission.

Area of Science:

• Wireless communication
• Optical networking
• Signal processing

Background:

• Indoor visible light communication (VLC) offers a promising alternative to radio frequency spectrum limitations.
• Dense light-emitting diode (LED) deployment in VLC systems leads to significant inter-channel interference (ICI).
• ICI negatively impacts signal-to-interference-plus-noise ratio (SINR) and spectral efficiency, hindering system performance.

Purpose of the Study:

• To develop an efficient multi-user scheduling framework for indoor VLC systems.
• To mitigate inter-channel interference (ICI) through interference coordination and cooperative transmission.
• To enhance spectral efficiency and user fairness in VLC networks.

Main Methods:

• Investigated a multi-user scheduling framework based on graph theory, incorporating interference coordination and cooperative transmission.
• Introduced cell-centric (CC) and user-centric (UC) clustering for cooperative transmission.
• Formulated and solved scheduling problems using linear programming, greedy algorithms, and bipartite graph theory.

Main Results:

• The proposed graph-based scheduling achieved up to a 7.7 dB gain in SINR compared to non-cooperative transmission.
• Bipartite graph scheduling demonstrated high spectral efficiency and a strong service fairness index.
• The greedy algorithm showed robustness to receiver rotation and occlusion, with a minor SINR penalty.

Conclusions:

• Graph-based scheduling effectively mitigates ICI in indoor VLC systems.
• The proposed framework enhances SINR, spectral efficiency, and user fairness.
• The approach is robust to various environmental factors like occlusion and receiver rotation.