Modeling and performance evaluation of underwater wireless optical communication system in the presence of different sized air bubbles

Singh, Mandeep; Singh, Gurdial; Kaur, Hardeep; Priyanka, .; Kaur, Sehajpal

doi:10.1007/s11082-020-02638-5

Cited by 18 publications

(14 citation statements)

References 27 publications

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“…The degraded quality of received image is majorly due to increase in the multipath dispersion. Other factors affecting the image quality include shot noise, white noise, salt and pepper noise 28 . Thus, a mobile receiver at 40 Mbps will be able to move freely on the receiver plane without affecting the SSIM value of the received image.…”

Section: Numerical Results and Discussionmentioning

confidence: 99%

Quantitative analysis of different LED lamp configurations in indoor VLC system

Priyanka

Singh

et al. 2021

Int J Communication

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Summary In this article, an indoor environment of 5 × 5 × 3 m3 dimensions is considered and a total of nine LED lamps are installed at the ceiling in a symmetrical pattern. The inter‐spatial separation between LED lamps is varied to achieve the dual purpose of lighting and communication services. The multipath channel impulse response for distinct receiver locations is also calculated under line‐of‐sight (LOS) and non‐line‐of‐sight (NLOS) channel conditions. Several performance parameters, that is, illumination uniformity, received power fluctuations, root‐mean‐delay spread (RMDS), are evaluated to estimate the performance of the proposed system. The results show that spatial separation of 1.5 m between the LED lamps outperforms the other considered spatial separations, and the error‐free data transmission rate for the proposed system comes out to be about 40 Mbps across the entire receiver plane. Furthermore, an RGB image is transmitted at 40 Mbps and the received image quality is estimated in terms of image quality parameter, that is, structure similarity index (SSIM) over the receiver plane. The results outlined that the received image shows 100% similarity with the transmitted image, and thus, the proposed system can be effectively deployed in practical indoor environments.

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Section: Numerical Results and Discussionmentioning

confidence: 99%

Quantitative analysis of different LED lamp configurations in indoor VLC system

Priyanka

Singh

et al. 2021

Int J Communication

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“…Each transmitted “1” bit is represented with a rectangular NRZ pulse, that is,

P ((), t) = P \prod ((), \frac{t - T_{b} / 2}{T_{b}})

having a unit amplitude in the duration [

- \frac{T_{b}}{2}

\frac{T_{b}}{2}

], where

P

represents the transmitted power and

T_{b}

represents the duration of each bit. Thus, the total transmitted signal can be expressed as 21

x_{t} ((), t) = \sum_{k = 1}^{240,000} b_{k} P ((), t - k T_{b})

where

b_{k} \in {0, 1}

denotes the bit values in the k th time slot. The intensity modulated signal is directed towards the transmitter aperture which collates the transmitted beam, and then it propagates through the underwater channel.…”

Section: Architecture Of the Proposed System For Image Transmissionmentioning

confidence: 99%

“…Also, the transmitted signal undergoes various losses such as absorption, scattering, beam divergence, beam scintillation, and other impairment losses after propagating through the underwater medium. Mathematically, it can be represented as 21

h_{r} ((), t) = x ((), t) f ((), I) G_{t} G_{r} {(\frac{λ}{4 π d^{2}})}^{2} e^{- ((), α * d) + L_{m}}

where

f (I)

represents the received irradiance fluctuations due the turbulent nature of the ocean that can be modeled using Equation (). The

G_{t} = {(\frac{π D_{t}}{λ})}^{2}

represents the transmitter gain, where

D_{t}

represents the diameter of the transmitter aperture and

λ

is the operating wavelength.…”

Section: Architecture Of the Proposed System For Image Transmissionmentioning

confidence: 99%

“…In an image, SSIM examines the visual possessions of structure, contrast, and luminescence. These three independent components collectively provide overall similarity which can be defined as 21

italicSSIM ((), x, y) = {[l (x, y)]}^{α} + {[C (x, y)]}^{β} + {[S (x, y)]}^{γ}

where

x

and

y

are the transmitted and received images. The luminance factor is estimated by the relation:

l ((), x, y) = \frac{2 μ_{x} μ_{y} + C_{1}}{{μ_{x}}^{2} + {μ_{y}}^{2} + C_{1}}

where

μ_{x}

and

μ_{y}

represent the mean intensities.…”

Section: Architecture Of the Proposed System For Image Transmissionmentioning

confidence: 99%

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Real‐time image transmission through underwater wireless optical communication link for Internet of Underwater Things

Singh

et al. 2021

Int J Communication

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Summary The Internet of Underwater Things (IoUTs) can be considered as a potential candidate to interconnect physical devices (things) such as submarines, ships, divers, buoys, and unmanned underwater vehicles (AUVs) to collect and exchange information with each other in the ocean environment. Traditionally, sound waves have been used to transfer information between IoUTs, but due to the lack of limited bandwidth and data rate, the underwater wireless optical communication (UWOC)‐based IoUTs can be considered as a viable solution. In this work, a real‐time RGB image is transferred between two IoUTs using an intensity modulation direct detection (IM/DD) on–off keying (OOK) modulation scheme. To estimate the performance of the reconstructed image, structure similarity index (SSIM) and peak signal‐to‐noise ratio (PSNR) have been evaluated. During transmission of an image through the water, the quality of the received image degrades due to the absorption, scattering, and underwater turbulence which further limits the transmission range. Thus, to enhance the quality of the received images, two filters, that is, median and Wiener filters, have been proposed. The median filter improves the SSIM and PSNR of the reconstructed image more appropriately as compared to the Wiener filter. The results show that the proposed median filter can enhance the communication range of the UWOC point‐to‐point link by 100 m.

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“…Our research group also conducted related technical research, analyzed the transmission performance of the multiary modulation format in the atmospheric turbulence channel [22], [23], and adopted polarization multiplexing and quadrature phase shift keying (QPSK) multiplexing technology to achieve 384 Gbps communication. The above researches are all pursuing the multiplexing of various technologies [24], but there are atmospheric turbulence effects in self-use space channels [25], [26], which cause beam drift, random fluctuations, and spot fragmentation, which makes it difficult to use in practical engineering. When being tracked and aligned, there is a pointing error, which aggravates the influence of the received optical signal [6], [27], [28].…”

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confidence: 99%

32 Gbps QPSK Optical Communication Technology Based on a New Equalizer in Atmospheric Turbulence

Yao

Zhang

et al. 2021

IEEE Access

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In this paper, cascaded least mean square-least mean square (LMS-LMS) adaptive equalization scheme is proposed based on fiber coupling system, in order to improve the transmission performance of quadrature phase shift keying (QPSK) modulated optical signals in medium and weak turbulence channels. First, the transmission performance of QPSK optical signal in different atmospheric turbulence channels is simulated and analyzed according to the characteristics of optical fiber coupling system and the characteristics of atmospheric turbulence channel. Secondly, cascaded LMS-LMS equalization scheme is proposed, and its distortion signal is corrected based on the original simulation results to verify the effectiveness and robustness of LMS-LMS. Finally, atmospheric turbulence simulator is used to verify the improvement effect of cascaded LMS-LMS adaptive equalizer under different turbulence conditions. The experimental results show that when the coherence length is r 0 = 1.6 cm and the received optical power is −34 dBm, the system can transfer the information at a rate of 32 Gbps QPSK after using cascaded LMS-LMS adaptive equalizer, and the bit-error ratio (BER) is lower than the minimum limit of forward error correction (FEC, 3.8 × 10 −3 ). Therefore, this work provides parameters for signal processing to suppress signal noise caused by turbulence disturbance and the noise of the device itself, when QPSK optical signal transmission system are used in the actual free space optical communication (FSOC).INDEX TERMS Free space optical communication, quadrature phase shift keying, atmospheric turbulence simulator, cascaded LMS-LMS adaptive equalizer. I. INTRODUCTIONFree-space optical communication (FSOC) technology uses the laser as a carrier wave for communication, which combines the advantages of radio communication and optical fiber communication. FSOC has the advantages of strong anti-electromagnetic interference ability, high security, high communication speed, and large information capacity. It is characterized by small system size, lightweight, low power consumption, simple construction, and flexibility mobility has significant strategic needs and application value in both military and civilian fields [1]-[3]. FSOC can be used as an emergency communication solution, applied to earthquake relief, emergency, anti-terrorism, public security investigation, and other fields.Specifically, it can provide military confidential information services for multi-arms joint offense and defense, and has outstanding advantages in local warfare, battlefield networking, and information confrontation. In addition, benefiting from the advantages of high bandwidth, fast and convenient transmission, and low cost, FSOC is the best choice for solving the "last 1 kilometer" of information transmission and the transmission of the fifth-generation mobile communication technology (5G) small and micro base stations [3]. Because the traditional microwave satellite communication method is difficult to meet the demand of the highest transmission ba...

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Modeling and performance evaluation of underwater wireless optical communication system in the presence of different sized air bubbles

Cited by 18 publications

References 27 publications

Quantitative analysis of different LED lamp configurations in indoor VLC system

Quantitative analysis of different LED lamp configurations in indoor VLC system

Real‐time image transmission through underwater wireless optical communication link for Internet of Underwater Things

32 Gbps QPSK Optical Communication Technology Based on a New Equalizer in Atmospheric Turbulence

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