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SVM aided LEDs selection for generalized spatial modulation of indoor VLC systems
- Publication Year :
- 2021
-
Abstract
- In order to reduce the complexity of the light-emitting diodes (LEDs) selection procedure in generalized spatial modulation (GSM) assisted indoor visible light communication (VLC) system, a support vector machine (SVM) aided low complexity and high efficiency machine learning LEDs selection algorithm is proposed for the considered GSM–VLC system. By modeling the LEDs selection problem in indoor GSM–VLC system as a multi-classification task, an optimization problem is constructed by utilizing kernel SVM. After the optimal parameters are obtained from the training stage, an LEDs selection procedure can be accomplished efficiently by SVM aided learning system for any given user’s channel state information. Simulation results and complexity analysis show that, compared with traditional LEDs selection algorithms, the proposed SVM aided LED selection algorithm can achieve an ideal bit error ratio (BER) performance while having considerable lower complexity for the considered GSM–VLC system.
- Subjects :
- Optimization problem
Computer science
business.industry
Visible light communication
02 engineering and technology
021001 nanoscience & nanotechnology
01 natural sciences
Atomic and Molecular Physics, and Optics
Electronic, Optical and Magnetic Materials
010309 optics
Support vector machine
Optics
GSM
Channel state information
0103 physical sciences
Electronic engineering
Bit error rate
Electrical and Electronic Engineering
Physical and Theoretical Chemistry
0210 nano-technology
business
Selection algorithm
Selection (genetic algorithm)
Subjects
Details
- Language :
- English
- ISSN :
- 00304018
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....fc7fb963cbeb7227f92148b88dbe7a68