Enhancing spectral efficiency of FSO system using adaptive SIM/M‐PSK and SIMO in the presence of atmospheric turbulence and pointing errors

Alnahhal, Mohammed; Ismail, Tawfik

doi:10.1002/dac.3942

Cited by 24 publications

(4 citation statements)

References 32 publications

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“…Then the constellation map is used as the input sample for the pattern recognition of DCNN satellite modulation signals constructed in this study, and the changes of different characteristic parameters in the constellation map with the increase of SNR are compared. The results show that PSK modulation signal patterns can be effectively identified when the SNR is greater than 10dB, which is basically consistent with the results of Mohamed Al-Nahhal et al (2019) [ 25 ]. Next, in this study, the effects of different activation functions on the recognition accuracy of the constructed model are compared.…”

Section: Discussionsupporting

confidence: 90%

Analysis of the pattern recognition algorithm of broadband satellite modulation signal under deformable convolutional neural networks

Li¹,

Li²

2020

PLoS ONE

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This research aims to analyze the effects of different parameter estimation on the recognition performance of satellite modulation signals based on deep learning (DL) under low signal to noise ratio (SNR) or channel non-ideal conditions. In this study, first, the common characteristics of broadband satellite modulation signal and the commonly used signal feature extraction algorithm are introduced. Then, the broadband satellite modulation signal pattern recognition model based on deformable convolutional neural networks (DCNN) is built, and the broadband satellite signal simulation is conducted based on Matlab software. Next, the signal characteristics of binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), 8 phase shift keying (PSK), 16 quadratic amplitude modulation (QAM), 64QAM, and 32 absolute phase shift keying (APSK) are extracted by the constellation map, and the ratio changes of T 1 and T 2 with SNR are compared. When SNR is given, it is compared with VGG model, AlexNet model, and ResNe model. The results show that the constellation points of satellite signals with different modulations are evenly distributed. T 1 of PSK modulation signals increases significantly with the increase of SNR. When SNR is greater than 10, PSK modulation signals can be identified. When T 2 is set and SNR is greater than 15dB, 16QAM and 32APSK signals can be distinguished. In the model, the Relu activation function, mini-batch gradient descent (MBGD) algorithm, and Softmax classifier have the best recognition accuracy. PSK modulation signals have the best recognition rate when the SNR is 0dB, and the recognition accuracy of different modulation signals at 20dB is over 98%. When the data length reaches 4000, the recognition accuracy of different modulation signals is higher than 97%. Compared with other algorithms, this algorithm has the highest recognition accuracy (99.83%) and shorter training time (3960s). In conclusion, the broadband satellite modulation signal pattern recognition algorithm of DCNN constructed in this study can effectively identify the patterns of different modulation signals.

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Section: Discussionsupporting

confidence: 90%

Analysis of the pattern recognition algorithm of broadband satellite modulation signal under deformable convolutional neural networks

Li¹,

Li²

2020

PLoS ONE

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“…In an earlier study, 35 the authors have presented a model that shows how ML techniques can be utilized to manage resource allocation and routing in multidimensional time–space–frequency optical networks. But, in this work, the authors did not consider the BER parameter in their analysis.…”

Section: Related Workmentioning

confidence: 99%

Machine learning‐based predictive modeling for failure management of optical spatial mode division multiplexing system

Kaur

Parasher²,

Srivastava

et al. 2022

Int J Communication

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The bit error rate (BER) in optical communication systems is often get degraded due to various factors like launch power, dispersion, modal noise, and so on. Finding the most optimal launch power for a signal to provide acceptable BER is usually difficult on an installed link. Therefore, in this paper, an attempt has been made to use machine learning-based linear regression technique for predicting the optimal signal quality for spatial division multiplexed (SDM)-based fiber optical transmission system for a fixed distance. This technique helps in predicting the optimal value of continuous launch power. Therefore, to demonstrate the given concept in this research work, the generic setup of an SDM optical long-haul system of 20 km in length has been designed and simulated in Optisystem-14.0. The light sources in our experiments are two spatial optical transmitters with an emission wavelength of around 1550 nm. Abiding to the first step for the regression analysis, that is the data preparation, normality and correlation checks were performed. After this, a linear regression model is developed which was validated through a summary report, coefficients and diagnostic plots. Furthermore, the accuracy of the model is improved by employing Cook's distance. These tests help in dealing with the influence points that hinders the prediction ability of the proposed model. The results show that the R-squared value is 0.9366, and value of adjusted R 2 comes out to be around 0.9344; we therefore came to infer that the model explains nearly 94% variations in the dependent variables. K E Y W O R D Sbit error rate (BER), launch power (LP), linear regression, optical transmission systems, spatial division multiplex (SDM)

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“…Hence, the system capacity as well as the spectral efficiency of a CPDM system is doubled than an existing PDM system. The Shannon capacity limit (SCL) is defined as the theoretical maximum amount of information that can be achieved during the transmission of the data between the Tx and Rx and the SCL is a useful metric for determining the spectral efficiency of the system [24]- [25]. The Shannon capacity 𝐶 (unit: b/s) and spectral efficiency 𝑆 (unit: b/s/Hz) are given by [25]- [27]:…”

Section: S D Fso C M a Novel System Design For Proposed Hybrid Cpdm-c...mentioning

confidence: 99%

Design of Novel Hybrid CPDM-CO-OFDM FSO Communication System and its Performance Analysis under Diverse Weather Conditions

Chowdhury,

Choyon

2021

Preprint

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A comprehensive novel design is proposed for the free-space optical (FSO) communication system by hybridizing circular polarization division multiplexing (CPDM) with coherent optical orthogonal frequency division multiplexing (CO-OFDM) and its performance is investigated realistically under diverse turbulent weather conditions of Bangladesh. Here we consider Gamma-Gamma (G-G) distribution for the turbulent FSO channel model. Moreover, the proposed scheme presents an excellent performance since CPDM technique not only maximizes the link capacity of FSO system but also enhances the spectral efficiency (SE) of the system. Besides, multipath-fading, which is appeared during the FSO transmission, is significantly mitigated by OFDM modulation. The outcomes from simulation confirm the advantages of the proposed hybrid scheme and also it can serve as a reference for the FSO application even in the turbulent weather conditions. Performance analysis of the proposed model is described in terms of optical power spectrum (OPS), optical signal to noise ratio (OSNR), bit error rate (BER), Q factor, constellation diagrams, and eye diagrams.

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Enhancing spectral efficiency of FSO system using adaptive SIM/M‐PSK and SIMO in the presence of atmospheric turbulence and pointing errors

Cited by 24 publications

References 32 publications

Analysis of the pattern recognition algorithm of broadband satellite modulation signal under deformable convolutional neural networks

Analysis of the pattern recognition algorithm of broadband satellite modulation signal under deformable convolutional neural networks

Machine learning‐based predictive modeling for failure management of optical spatial mode division multiplexing system

Design of Novel Hybrid CPDM-CO-OFDM FSO Communication System and its Performance Analysis under Diverse Weather Conditions

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