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K-nearest neighbor model for classification between four different Hermite gaussian beams in MDM/FSO systems under rainy weather

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Abstract

In this paper the K-Nearest Neighbor (KNN) model which is one of machine learning (ML) algorithm is applied to distinguish between the four distinct Hermite Gaussian (HG) beams (HG00, HG01, HG02, and HG03) in mode division multiplexed (MDM)-free space optics (FSO) communication system. First, the performance of the FSO system using these different HG beams is investigated for rainy weather conditions in various Indian cities having distinct geographical locations. Transmission performance is evaluated in terms of quality (Q)-factor, signal-to-noise ratio (SNR), bit error rate (BER), and eye diagrams. Then, the values of the BER for the different HG beams are applied to the KNN ML model as to classify between them. HG modes are used for capacity enhancement. Results indicate that 80 Gbps can be transmitted over 1000 m in Hyderabad, 800 m in Pune, 580 m in Chennai, and 475 m in Mumbai at log (BER) ~ \({10}^{-15}\), Q-factor less than 8, and SNR ~ 10 dB. Additionally, the K-Nearest Neighbor (KNN) ML model shows 94% classification accuracy between four HG beams.

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Abbreviations

HG:

Hermite gaussian

FSO:

Free space optics

Q-factor:

Quality factor

SNR:

Signal to noise ratio

BER:

Bit error rate

ML:

Machine learning

KNN:

K-nearest neighbor

HDTV:

High-definition television

RF:

Radio frequency

LED:

Light emitting diode

OWC:

Optical wireless communication

MDM:

Mode division multiplexing

WDM:

Wavelength division multiplexing

OOK:

On-off keying

OFDM:

Orthogonal frequency division multiplexing

AI:

Artificial intelligence

PRBSG:

Pseudo random bit sequence generator

NRZ:

Non-return-to-zero

SL:

Spatial laser

MZM:

Mach-Zehnder modulator

MUX:

Multiplexer

DeMUX:

Demultiplexer

PIN:

Positive-intrinsic-negative

PD:

Photodiode detector

LPF:

Low pass filter

PDF:

Probability density function

ROC:

Receiver operating characteristic

AUC:

Area under the roc curve

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Acknowledgements

This study is supported via funding from Prince Sattam bin Abdulaziz University project number (PSAU/2023/R/1444).

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, University Institute of Engineering, Chandigarh University, Mohali, Punjab, India

    Mehtab Singh

  2. Arab Academy for Science, Technology and Maritime Transport, Alexandria, 1029, Egypt

    Ahmed Métwalli

  3. Department of Electrical Engineering, College of Engineering in Wadi Alddawasir, Prince Sattam Bin Abdulaziz University, Wadi Aldawaser, KSA, Saudi Arabia

    Hassan Yousif Ahmed & Medien Zeghid

  4. Electronics and Micro-Electronics Laboratory (E. μ. E. L), Faculty of Sciences, University of Monastir, Monastir, Tunisia

    Medien Zeghid

  5. Department of Mathematics, College of Science and Humanities in Alkharj, Prince Sattam Bin Abdulaziz University, 11942, Alkharj, Saudi Arabia

    Kottakkaran Sooppy Nisar

  6. Alexandria Higher Institute of Engineering and Technology, Alexandria, 21311, Egypt

    Somia A. Abd El-Mottaleb

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  1. Mehtab Singh
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  2. Ahmed Métwalli
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  3. Hassan Yousif Ahmed
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  5. Kottakkaran Sooppy Nisar
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Contributions

Conceptualization: MS, AM, HYA, Software: MS, HYA, MZ, KSN, SAE; Writing Original draft: MS, AM, HYA, MZ, KSN, SAE; Investigation: AM, MZ, HYA, SAE; Writing review and editing: MS, HYA, KSN. All the authors read and approve the manuscript.

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Correspondence to Kottakkaran Sooppy Nisar.

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Singh, M., Métwalli, A., Ahmed, H.Y. et al. K-nearest neighbor model for classification between four different Hermite gaussian beams in MDM/FSO systems under rainy weather. Opt Quant Electron 55, 974 (2023). https://doi.org/10.1007/s11082-023-05229-2

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