Smart color channel allocation for visible light communication cell ID

Le, Nam-Tuan; Jang, Yeong Min

doi:10.1016/j.osn.2014.06.005

Cited by 12 publications

(6 citation statements)

References 18 publications

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“…In [ 24 ], the visible light Cell-ID was used for channel allocation. In [ 25 ], several realistic VLID based navigation systems used in underground subway stations and in a super market were demonstrated.…”

Section: Algorithms In Vlc Based Positioningmentioning

confidence: 99%

An in-Depth Survey of Visible Light Communication Based Positioning Systems

Yoo

2016

Sensors

278

179

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While visible light communication (VLC) has become the candidate for the wireless technology of the 21st century due to its inherent advantages, VLC based positioning also has a great chance of becoming the standard approach to positioning. Within the last few years, many studies on VLC based positioning have been published, but there are not many survey works in this field. In this paper, an in-depth survey of VLC based positioning systems is provided. More than 100 papers ranging from pioneering papers to the state-of-the-art in the field were collected and classified based on the positioning algorithms, the types of receivers, and the multiplexing techniques. In addition, current issues and research trends in VLC based positioning are discussed.

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Section: Algorithms In Vlc Based Positioningmentioning

confidence: 99%

An in-Depth Survey of Visible Light Communication Based Positioning Systems

Yoo

2016

Sensors

278

179

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“…VLC localization techniques can be classified into proximity, fingerprinting, triangulation, and photography vision. In the proximity technique [28,29,30], the relative position is estimated on the basis of the unique identification code of the light source, which defines one specific coordinate in the database. The accuracy level depends on the field of view of the transmitter.…”

Section: State Of the Artmentioning

confidence: 99%

“…To analyze the performance of the system’s SNR over signal propagation, the noise model plays an important role. Optical noise includes shot noise ∂, thermal noise, and multipath inter-symbol interference [29], defined by Equations (31)–(34), respectively. normalN=Nshot+Nthermal+Ninterference, Nshot=2qWμ(P r+PrISI)Ben+2qWIbgI2Ben+ ε, Nthernal=8πKTkGδAI2Ben2+ 16π2KTkEgmδ2A2I3Ben3, …”

Section: Proposed Localization Estimation Schemementioning

confidence: 99%

Photography Trilateration Indoor Localization with Image Sensor Communication

Jang

2019

Sensors

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Localization has become an important aspect in a wide range of mobile services with the integration of the Internet of things and service on demand. Numerous mechanisms have been proposed for localization, most of which are based on the estimation of distances. Depending on the channel modeling, each mechanism has its advantages and limitations on deployment, exhibiting different performances in terms of error rates and implementation. With the development of technology, these limitations are rapidly overcome with hybrid systems and enhancement schemes. The successful approach depends on the achievement of a low error rate and its controllability by the integration of deployed products. In this study, we propose and analyze a new distance estimation technique employing photography and image sensor communications, also named optical camera communications (OCC). It represents one of the most important steps in the implemented trilateration localization scheme with real architectures and conditions of deployment which is the second our contribution for this article. With the advantages of the image sensor hardware integration in smart mobile devices, this technology has great potential in localization-based optical wireless communication

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“…Some of these researches are worth highlighting [6][7][8][9][10][11] including a transmission protocol and image processing technique [6], encoding and decoding methods to improve the data rate from a long distance [7], an analysis of varying SNR ratio based on the distance and velocity [8], and an adapted encoding method for varying the distance necessary when the vehicle is moving [9]. Meanwhile, our previous work [12] provides the concept of a multicolor transmission on multiple LED channels, which could be helpful for further extension to heavy traffic conditions. Asynchronous communication means that no synchronization is required for communication from the LED transmitter to the camera receiver.…”

Section: Introductionmentioning

confidence: 99%

Asynchronous Scheme for Optical Camera Communication-Based Infrastructure-to-Vehicle Communication

Nguyen

Jang

2015

International Journal of Distributed Sensor Networks

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This paper introduces infrastructure-to-vehicle (I2V) communication based on asynchronous optical camera communication (OCC), the transmitter of which can be an LED traffic light or electronic display, with the receiver being the existing front vehicle camera. In asynchronous OCC-based I2V communication, the key technique is an asynchronous scheme. An asynchronous scheme not only takes advantage of simplicity owing to the lack of an uplink or synchronization requirement, but is also the most feasible solution for communication to/from moving vehicles where synchronization is difficult to achieve within a short time. An asynchronous scheme for OCC-based I2V communication is proposed, and a performance evaluation shows its feasibility for use in a number of promising OCC-based wireless communication applications and services in a vehicular environment.

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Smart color channel allocation for visible light communication cell ID

Cited by 12 publications

References 18 publications

An in-Depth Survey of Visible Light Communication Based Positioning Systems

An in-Depth Survey of Visible Light Communication Based Positioning Systems

Photography Trilateration Indoor Localization with Image Sensor Communication

Asynchronous Scheme for Optical Camera Communication-Based Infrastructure-to-Vehicle Communication

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