Comparative Analysis of Optical Multicarrier Modulations: An Insight into Machine Learning-based Multicarrier Modulation

Ibhaze, Augustus E.; Edeko, F.O.; Orukpe, Patience E.

doi:10.35378/gujs.774296

Cited by 3 publications

(3 citation statements)

References 19 publications

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“…The conventional optical schemes were first investigated to adapt the RF/wifi based OFDM for optical communication (VLC). These schemes took cognizance of the peculiarities of VLC applications since the signal had to be real valued and unipolar while maintaining intensity modulation/ direct detection [29]. In line with the related work, among the contending conventional schemes (DCO, ACO and FLIP), FLIP showed superiority in terms of energy efficiency while maintaining spectral efficiency for VLC application.…”

Section: Resultsmentioning

confidence: 81%

“…Following the deductions made in the literature relative to the conventional DCO-OFDM, ACO-OFDM and FLIP-OFDM, it is therefore logical to seek measures for improving upon the BER and spectral performances of the FLIP scheme since it surpasses the DCO and ACO schemes [28,29]. In view of the important parameters of the optical OFDM scheme; transmit power, throughput, bit error rate and signal to noise ratio, it is imperative to optimize the scheme such that the throughput is maximized at low transmit power.…”

Section: Methodsmentioning

confidence: 99%

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A Novel Adaptive OFO-OFDM Modulation for Visible Light Communication

Ibhaze

Edeko

Orukpe

2021

Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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Radio frequency techniques have been deployed in the past time for wireless communication and following its spectral crunch and limited throughput, the visible light spectrum with enormously large bandwidth and potentials for high throughput is being investigated in this work. This study is aimed at investigating and modeling a signal conditioning scheme in the visible light spectrum in view of enhancing the throughput of the network. To effectively enhance communication throughput, a possible solution is to deploy multicarrier techniques. In this work, an adaptive Optimized Flipped Optical (OFO) OFDM is proposed for improved throughput using Lagrange Multiplier and Broyden Fletcher Goldfarb Shanno Algorithm (BFGSA). The Lagrange Multiplier technique was used to formulate the model for the optimization of the throughput constrained by the bit error rate (BER) and the total subcarrier transmit power whereas the BFGSA was used for the estimation of the approximation to the Hessian matrix for the computation of the optimal throughput value. Results showed improved spectral efficiency in favor of the proposed algorithm when compared with the conventional schemes. Further validations revealed the performance superiority of the proposed algorithm when compared with Castel, Wyglinski and Bedeer algorithms under comparable operating conditions for a given average signal to noise ratio (SNR).

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Section: Resultsmentioning

confidence: 81%

Section: Methodsmentioning

confidence: 99%

A Novel Adaptive OFO-OFDM Modulation for Visible Light Communication

Ibhaze

Edeko

Orukpe

2021

Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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“…With its ability to transmit data at high speeds using light waves instead of radio frequency (RF), light-fidelity (LiFi) technology has become a viable substitute for conventional RF-based communication systems [1]. Direct Current Offset Quadrature Amplitude Modulation (DCO-OFDM) is one of the modulation methods used in LiFi systems that has drawn a lot of attention because of its great spectral efficiency and resilience to optical channel defects [2]. But like any communication system, DCO-OFDM based LiFi systems have to overcome obstacles to improve and optimize performance, especially in surroundings that are dynamic and heterogeneous [3].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Algorithms for Performance Enhancement in DCO-OFDM-Based LiFi Systems

Yuvaraja Thangavel, L. Raja, E. Kannan

2024

jes

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This study describes how machine learning methods can be used to enhance the performance of LiFi (light fidelity) systems that are based on DCO-OFDM (direct current bias optical orthogonal frequency division multiplexing). LiFi, a rapidly developing technology that uses light for wireless communication, has to contend with issues like channel impairments and signal interference. This work investigates several machine learning strategies to address these problems and improve the DCO-OFDM LiFi systems' overall performance. It is determined how well various machine learning techniques perform in terms of improving system parameters, decreasing latency, and raising throughput by analyzing real-world data and simulation studies. Various sorts of symmetrical recurrence division multiplexing (OFDM, for example, DC one-sided optical OFDM (DCO-OFDM), are utilized in light devotion (LiFi). A critical DC predisposition in DCO-OFDM brings about optical power failure, while a minor inclination increment cutting commotion. In this manner, it's essential to decide the appropriate DC predisposition level for DCO-OFDM. This examination finds the ideal DC-predisposition an incentive for DCO-OFDM based LiFi frameworks utilizing machine learning (ML) algorithms. To do this, a MATLAB device is utilized to create a dataset for DCO-OFDM. Thusly, Python writing computer programs is utilized to apply machine learning methods. ML is used to recognize the basic DCO-OFDM qualities that influence the ideal DC predisposition. Here, it is exhibited that the base, greatest, and standard deviation of the bipolar OFDM signal, as well as the size of the heavenly body, decide the ideal DC inclination.

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A Brief Overview of Energy Efficiency Resources in Emerging Wireless Communication Systems

Ibhaze

Imoize

Okoyeigbo

2022

Telecom

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It is crucial to design new communication technologies to surmount the setbacks in RF communication systems. A suitable energy-efficiency scheme helps evade needless energy consumption in wireless communication. Appropriate choice of the most suitable energy-efficiency scheme aids in selecting the most energy-efficient equipment to minimize the expense of energy towards decreasing individual network element energy consumption without affecting their unique features. This review presents the energy efficiency challenges in wireless communication by employing different technologies. The emergence of visible light communication (VLC) provides an energy-efficient wireless communication system despite the various challenges inherent in its adoption that limit its physical realization. This work seeks to harness the potential of the transmission capabilities of VLC while providing an insight into novel practical implementation techniques. The work also addresses the energy consumption problem of low-active components and idle period of active components of base stations by using sleep modes for their systematic turning off and on. The high cost of power supply and the environmental emission of gases from base stations are also addressed by integrating a renewable energy resource into the conventional standalone diesel generators. Overall, the work provides an overview of information necessary for foundational research in energy-efficient resources applied to emerging wireless communication systems.

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Comparative Analysis of Optical Multicarrier Modulations: An Insight into Machine Learning-based Multicarrier Modulation

Abstract: Highlights• This paper focuses on the comparative study of optical multicarrier modulation schemes.• A machine learning-based multicarrier modulation is proposed for optical signal conditioning.• An optimal system performance with reduced bit error rate response was achieved.

Cited by 3 publications

References 19 publications

A Novel Adaptive OFO-OFDM Modulation for Visible Light Communication

A Novel Adaptive OFO-OFDM Modulation for Visible Light Communication

Machine Learning Algorithms for Performance Enhancement in DCO-OFDM-Based LiFi Systems

A Brief Overview of Energy Efficiency Resources in Emerging Wireless Communication Systems

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