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Updated: Apr 30, 2026
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Quasi-light Storage for Optical Data Packets
Published on: February 6, 2014
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Entropy loading in layered asymmetrically clipped optical OFDM systems for high spectrum efficiency visible light
Optics Express
|February 20, 2026
Summary
Entropy loading (EL) is now demonstrated in layered asymmetrically clipped optical orthogonal frequency division multiplexing (LACO-OFDM) for visible light communication (VLC). This novel approach enhances spectral efficiency and system performance, achieving higher generalized mutual information (GMI).
Area of Science:
- Optical Communications
- Signal Processing
- Wireless Technologies
Background:
- Layered asymmetrically clipped optical orthogonal frequency division multiplexing (LACO-OFDM) is efficient for visible light communication (VLC).
- Entropy loading (EL) enhances multi-carrier systems but hasn't been applied to LACO-OFDM due to inter-layer interference (ILI).
- Residual clipping noise (RCN) in LACO-OFDM complicates EL application.
Purpose of the Study:
- To introduce and evaluate entropy loading (EL) for LACO-OFDM systems.
- To develop a probability-aware RCN power estimation method for accurate SNR assessment.
- To improve the spectral and energy efficiency of VLC systems.
Main Methods:
- Theoretical analysis of probabilistic constellation shaping (PCS) impact on RCN.
- Development of a constellation trimming (CT) based RCN power estimation method.
- Implementation of a total power constrained EL algorithm for LACO-OFDM.
Main Results:
- The proposed CT method accurately estimates SNR with reduced computational complexity.
- The EL algorithm achieves higher generalized mutual information (GMI) compared to existing bit loading (BL) methods.
- An average GMI improvement of ~10% and a maximum gain of 0.2 bits/symbol were observed.
- CT with a threshold of 0.5 significantly reduces computation time (~80%) with comparable GMI.
Conclusions:
- The proposed EL algorithm is the first demonstrated for LACO-OFDM VLC systems.
- The method offers a "win-win" outcome of higher accuracy and lower complexity.
- Significant performance gains in GMI and computational efficiency were validated through simulation and experiment.
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