Abstract

In this paper, we present experimental demonstration of an indoor uplink near-infrared LED camera communication (ICC) that employs near-infrared (IR) light as a communication medium and a camera as the receiver. The proposed ICC exploits advantages of the camera receiver to provide wider coverage and accurate indoor positioning in IR communications. Since near-IR light is the communication medium, ICC can safely increase the light intensity compared with other visible light based wireless communication schemes. Unlike previous studies focused on positioning only, the ICC provides practical uplink indoor wireless communication as well as positioning. As in optical camera communications, the blooming effect from slow speed cameras needs to be mitigated in the ICC. An adaptive intensity compensation algorithm is also proposed for reducing this blooming effect. The blooming reduction algorithm is based on the absence of visible light interference in IR communications. Experiments demonstrate that employing an even low-specification webcam and low-power LEDs can provide centimeter-scale accuracy for the user positioning and a data rate of 6.72 kbit/s at a distance of 100 cm.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

1. Introduction

Optical wireless communications (OWC) have gathered much attention due to a huge increase in indoor wireless traffic and free licensing [1–3]. Over the past decade, within the framework of OWC, visible light communications (VLC) have been extensively documented [2, 3]. VLC is deployed in conjunction with illumination by modulating the data on the light emitting diode (LED) transmitter to increase energy efficiency in indoor communications [3, 4]. Recently, an interesting OWC scheme that utilizes infrared (IR) has been introduced [5]. It is a beam-steered IR light positioning scheme using IR LED and camera [5]. In this IR-based scheme, it yields significantly high signal-to-noise ratio (SNR) at the receiver, compared with visible light counterparts, due largely to narrower and more efficient IR beam [1, 5]. In addition, the IR-based schemes offer approximately 90% power reduction, tenfold wider bandwidth and improved safety to human eyes [1]. The use of IR light also allows higher intensity on the transmitter compared with VLC without causing either discomfort or harm to the user’s eye [1], [2]. Moreover, in regard to uplink transmission, it is found that IR-based schemes are more desirable than VLCs that have difficulty in implementing visible LEDs on end-user devices [1–4]. However, the previous IR study has some limitations on practical applications and implementations as it operates with a narrower irradiance angle of 30° or less, a line-of-sight connection, and less practical beam-steering method.

In the present work, we propose a near-infrared LED camera communication (ICC) that employs near IR beam as a communication medium and a camera as its receiver. It should be noted that the wavelengths of near IR light, which are reflected IR lights (IR-A band), are in the range of 780 nm to 950 nm [1]. The proposed ICC employs 940 nm IR LEDs as transmitters to minimize the interference from visible light. The ICC exploits advantages of optical camera communication (OCC) [6–8] and proposes both practical indoor wireless connection and positioning. OOK modulation and rolling-shutter-based patterning demodulation are employed in the ICC without interference from visible light. The deployment of the camera receiver in the ICC improves the coverage area for the user’s identification, resulting in improved communication and positioning. Compared with previous OCC studies [6–8], the captured frame in the ICC does not contain any surrounding objects or noise since the communication medium is IR light. Thus, a distinct blooming mitigation algorithm, termed adaptive intensity compensation (AIC), is proposed in the ICC. Experiments are conducted to validate that the proposed ICC provides an adequate transmission quality of up to 100 cm using the transmitter with a relatively low power of 600 mW and achieves a data rate of 6.72 kbit/s.

2. Proposed near-infrared camera communication

2.1 Hardware configurations

The proposed ICC is demonstrated through an experimental setup for an uplink scheme shown in Fig. 1(a) and its block diagram shown in Fig. 1(b). The data packet is initially generated in a personal computer (PC) and then uploaded into the microcontroller unit (MCU). An On-Off Keying (OOK) modulation is employed in the MCU since it is the most suitable one for IR communication [1]. The current supply of the MCU is limited to 40 mA for each output channel. Thus, an LED driver is assembled to amplify the current driving the LEDs up to 120 mA per channel. A Fresnel lens is installed on the transmitter unit to focus the light beam. On the receiver side, the camera is covered by a diffuser and an IR blocking filter. The camera is then connected to the processing PC through a USB port and the captured images are processed offline. A rolling-shutter-patterning demodulation is employed for retrieval of the data packet, which is then finally compared with the transmitted ones for transmission quality evaluation.

 figure: Fig. 1

Fig. 1 Proposed ICC (a) experimental setup (b) block diagram and (c) schematic of the transmitter.

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Figure 1(c) shows the schematic of the transmitter comprising an ATMega328P based MCU with a clock of 16 MHz, a TLC5940 based LED driver IC, and the IR LEDs as the transmitter. The designed transmitter unit, shown in Fig. 2(a), utilizes five IR LEDs emitting an IR light with a wavelength of 940 nm. Each IR LED has an operating voltage of 1.5 V with a maximum current of 120 mA. An acrylic based Fresnel lens with a diameter of 25 mm is installed on the metal cover. In addition, as illustrated in both Figs. 2(a) and 2(b), a flexible arm is attached at the base of the transmitter unit for the ease of moving of the transmitter during the experiment. Since the communication medium is IR light with 940 nm wavelength, a modification to the camera is required for efficient capture.

 figure: Fig. 2

Fig. 2 Transmitter unit (a) assembly of the transmitter unit and (b) the installed transmitter unit.

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Figure 3(a) illustrates the USB webcam employed as the receiver having its internal IR blocking filter removed to allow IR light to reach the sensor. A thin polyvinyl-based diffuser with a transmittance of 80% is attached on the camera cover and an IR bandpass filter (Hoya R-72) with a wavelength of 720 nm – 2000 nm is fixed on top of the camera cover with a 3D-printed mounting. The diffuser is important to spread the diffusion of the IR beam before it is captured by the camera, thus improving the intensity distribution that is useful for rolling shutter demodulation. The assembled camera unit is shown in Fig. 3(b) along with the camera holder.

 figure: Fig. 3

Fig. 3 Receiver unit (a) assembly of the camera and (b) assembled camera unit and holder.

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2.2 Data transmission

Since a rolling-shutter-patterning demodulation is employed for reception, a data packet needs to be configured for the transmission. The transmitted data packet contains a 4-bit header, a 28-bit payload, and a 1-bit zero gap as illustrated in Fig. 4(a). The content of the header itself is a cyclic prefix of the payload that is useful for synchronization that will be elaborated in the next subsection. The OOK modulated data is then transmitted through the LEDs with a flickering rate of 8 KHz. This flicker rate can be translated to a data rate of 8 kbit/s. However, an effective data rate is found to be 6.72 kbit/s, when the bits for the header and the zero gap are excluded. Figure 4(b) shows the measured output of the LED driver using a digital oscilloscope to verify the consistency of the generated pulses to drive the LEDs.

 figure: Fig. 4

Fig. 4 Data transmission: (a) data packet and (b) measured output of the LED driver.

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2.3 Synchronization and demodulation

The processes of the reception, i.e., synchronization and demodulation in ICC, are shown in Fig. 5. The process initializes by fixing the exposure time of the camera to 1/4096 s to limit the amount of light entering the sensor and preventing ghosting between captured frames. The first step is frame acquisition with an example frame shown in Fig. 6(a). It can be observed that the captured frame contains only the infrared light without the image of the environment due to the use of short exposure time of 1/4096 s, together with the diffuser and the IR bandpass filter. Afterward, the mean intensities of both the pixel rows and pixel columns of the frame (mR and mC) are calculated with examples shown in Figs. 6(b) and 6(c). Then, a calculation of three values is carried out, i.e., LY, LX, and μX. Both LY and LX are calculated by subtracting each standard deviation (σR and σC) from each maximum mean intensity value (max of mR and mC), while μX is the mean of mC. The peak values above the limits (LY and LX) are then used to estimate the position of the transmitter on y-axis and x-axis of the camera, respectively. The pixel row/column of the first peak value above the limits (LY and LX) is the estimated coordinate indicating the position of the transmitter.

 figure: Fig. 5

Fig. 5 Flowchart of ICC synchronization and demodulation.

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 figure: Fig. 6

Fig. 6 Thresholding (a) captured image from the camera (b) mean intensity of each pixel row (c) mean intensity of each pixel column and (d) binary thresholding performed after the AIC.

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The next step after positioning is the data demodulation. It can be observed in Fig. 6(b), however, that due to severe blooming effect, the binary threshold for demodulation proves to be inaccurate even after performing a 4th order polynomial fitting on mR [7]. Thus, robust blooming mitigation is required as previously studied in [7, 8]. The proposed AIC algorithm starts the blooming effect mitigation by filtering columns having mC values lower than μX. Then, we recalculate mean intensity of the pixel rows based on the filtered columns, producing mF values. Figure 6(d) shows mF values. It can be seen that mF has minor blooming effect and more accurate binary thresholding. In this regard, AIC successfully reduces the blooming caused by the presence of significantly high intensity on the center compared with the surrounding diffused light within the capture frame. The intensity of mF is normalized based on the threshold to produce both the demodulated binary data (binary thresholding) and the normalized intensity data with binary threshold as the base value. It should be noted that an additional algorithm is necessary for time synchronization to identify the header. To this end, the maximum likelihood algorithm (MLE) is employed as an additional algorithm to synchronize the normalized intensity data by locating the header before the binary thresholding is performed. The header location for time synchronization is considered important in ICC, since the rate of IR LED flicker and the camera capture rate are not always linearly correlated [6–8]. The content of the header itself is a cyclic prefix of the payload that enables MLE to synchronize the beginning of the data packet correctly using a modified log-likelihood calculation [9].

γ(x)=k=xx+H1r(k)×r(k+N)

The correlation,γ, for each data packet is obtained as a multiplication of two normalized intensity values (r(k) and r(k+N)) that are separated by the length of the payload (N). The accumulation is performed as many as H times, which is the length of the header. Figure 6(e) shows the correlation value relative to each pixel row, indicating that the MLE successfully identifies the beginning of each header as the maximum value of the correlation (red dotted lines).

3. Experiment results and analysis

The experiments were conducted indoors within an environment having a dimension of 130 cm × 81 cm × 200 cm affected by an ambient illuminance of 800-900 lx from the LED illumination on the ceiling. In the receiver, the modified webcam was employed in a video capture mode with a manual configuration of 640 × 480 pixels resolution, a capture rate of 60 fps, and an exposure time of 1/4096 s.

The first experiment was a coverage test illustrated in Fig. 7(a) with a height set to 115 cm between the receiver and the transmitter. It was conducted to compare the coverage achieved by the proposed ICC and the IR communication based on the photodiode (PD) receiver. The evaluation was carried out by means of SNR measurements to indicate the consistency of ICC for receiving an equal intensity of IR beam across its whole coverage range. SNR is generally calculated as a ratio of the signal power to the noise power in IR communication. However, ICC uses a camera and the calculation of SNR in the camera sensor is defined by the ratio of average signal value μsig to the standard deviation of the background σbg [10]. The results for the coverage test, shown in Fig. 7(b), indicate that the proposed ICC provides better coverage and consistency against conventional PD-based IR communication due to the use of a camera with a wider field-of-view (FOV) of 60°. To achieve comparable coverage, a conventional PD-based solution needs multiple PDs distributed across the room since the FOV of PD is generally confined to 30°.

 figure: Fig. 7

Fig. 7 Experiment for coverage and positioning (a) ICC diagram (b) SNR measurements.

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The second experiment was carried out to evaluate the positioning accuracy with the identical parameters. As shown in Fig. 7(a), three transmitter positions are set to the center of the floor, 8 cm offset from the center, and 55 cm offset from the center, respectively. Table 1 shows that the angular accuracy achieved in the proposed ICC is approximately 1.6°. Angular accuracy is the angle difference between calculated position of the transmitter and the actual position of the transmitter in the experiment. It is interesting to analyze the accuracy with increased resolution. When the resolution is increased to 1280 × 720 pixels, the achieved angular accuracy is improved to be approximately 0.3°. Table 2 shows the accuracy with increased resolution. When compared with the previous scheme [5], the proposed ICC is slightly worse, due mainly to the fact that the use of diffuser that increases the perceived size of the transmitter in the captured frame of the camera. However, while the accuracy is slightly compromised, the proposed ICC provides twice larger coverage using an even lower resolution camera. In addition, the proposed ICC employs the camera not only for positioning function but also for uplink communication.

Tables Icon

Table 1. Positioning Accuracy with a Resolution of 640 × 480 pixels

Tables Icon

Table 2. Positioning Accuracy with a Resolution of 1280 × 720 pixels

The final experiment was carried out to evaluate the communication quality. The distance between the transmitter and the receiver varies from 10 cm to 200 cm with an increment of 10 cm. It can be observed from Fig. 8(a) that at a fixed data rate of 6.72 kbit/s, a BER of better than 10−3 can be achieved up to 120 cm. The SNR degrades significantly after 90 cm due to the reduced effectiveness of the AIC algorithm. It is caused by a lower intensity of the blooming effect that is harder to filter from the background noise on the sensor. On the other hand, Fig. 8(b) shows experimental results of the data rate while maintaining a BER of 10−3 (target BER). The experimental results show that an SNR value of more than 15 dB is required to ensure the target BER and an achievable data rate of 6.72 kbit/s.

 figure: Fig. 8

Fig. 8 Transmission quality experiments (a) BERs with the fixed data rate of 6.72 kbit/s and (b) data rates with the target BER of 10−3.

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4. Conclusion

An infrared LED camera communication has been proposed to provide both practical uplink indoor communication and positioning. A laboratory-scale experiment was conducted to verify the scheme and proves that it can achieve centimeter-scale positioning at a data rate of 6.72 kbit/s at a maximum distance of 200 cm. From the experiments, it is verified that the ICC can offer a versatile uplink communication with near-IR light as its medium and the camera receiver for a wider coverage. It should be noted, however, that the present transmission quality can be further improved by applying error correction codes and higher resolution cameras. Likewise, the data rate and positioning accuracy can also be enhanced using higher speed and higher resolution cameras.

Funding

National Research Foundation of Korea (NRF) (2018R1D1A3B07049858).

Acknowledgment

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the article. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2018R1D1A3B07049858).

References and links

1. T. Koonen, “Indoor optical wireless systems: technology, trends, and applications,” J. Lightwave Technol. 36(8), 1459–1467 (2018). [CrossRef]  

2. D. C. O’Brien, “Optical wireless communications: current status and future prospects,” in Proc. IEEE Summ. Top., Newport Beach (2016).

3. P. H. Pathak, X. Feng, P. Hu, and P. Mohapatra, “Visible light communication, networking, and sensing: a survey, potential and challenges,” IEEE Comm. Surv. and Tutor. 17(4), 2047–2077 (2015). [CrossRef]  

4. C. H. Yeh, Y. L. Liu, and C. W. Chow, “Real-time white-light phosphor-LED visible light communication (VLC) with compact size,” Opt. Express 21(22), 26192–26197 (2013). [CrossRef]   [PubMed]  

5. A. Gomez, K. Shi, C. Quintana, G. Faulkner, B. C. Thomsen, and D. C. O’Brien, “A 50 Gb/s transparent indoor optical wireless communications link with an integrated localization and tracking system,” J. Lightwave Technol. 34(10), 2510–2517 (2016). [CrossRef]  

6. W. A. Cahyadi, Y. H. Kim, Y. H. Chung, and C.-J. Ahn, “Mobile phone camera-based indoor visible light communications with rotation compensation,” IEEE Photonics J. 8(2), 1–8 (2016). [CrossRef]  

7. C. W. Chow, C. Y. Chen, and S. H. Chen, “Visible light communication using mobile-phone camera with data rate higher than frame rate,” Opt. Express 23(20), 26080–26085 (2015). [CrossRef]   [PubMed]  

8. W. C. Wang, C. W. Chow, L. Y. Wei, Y. Liu, and C. H. Yeh, “Long distance non-line-of-sight (NLOS) visible light signal detection based on rolling-shutter-patterning of mobile-phone camera,” Opt. Express 25(9), 10103–10108 (2017). [CrossRef]   [PubMed]  

9. T. Adiono, W. Cahyadi, and A. Salman, “DVB-T synchronizer architecture design and implementation,” in International Conference on Electrical Engineering and Informatics, 594–599 (2009).

10. Z. Chen, X. Wang, S. Pacheco, and R. Liang, “Impact of CCD camera SNR on polarimetric accuracy,” Appl. Opt. 53(32), 7649–7656 (2014). [CrossRef]   [PubMed]  

References

  • View by:

  1. T. Koonen, “Indoor optical wireless systems: technology, trends, and applications,” J. Lightwave Technol. 36(8), 1459–1467 (2018).
    [Crossref]
  2. D. C. O’Brien, “Optical wireless communications: current status and future prospects,” in Proc. IEEE Summ. Top., Newport Beach (2016).
  3. P. H. Pathak, X. Feng, P. Hu, and P. Mohapatra, “Visible light communication, networking, and sensing: a survey, potential and challenges,” IEEE Comm. Surv. and Tutor. 17(4), 2047–2077 (2015).
    [Crossref]
  4. C. H. Yeh, Y. L. Liu, and C. W. Chow, “Real-time white-light phosphor-LED visible light communication (VLC) with compact size,” Opt. Express 21(22), 26192–26197 (2013).
    [Crossref] [PubMed]
  5. A. Gomez, K. Shi, C. Quintana, G. Faulkner, B. C. Thomsen, and D. C. O’Brien, “A 50 Gb/s transparent indoor optical wireless communications link with an integrated localization and tracking system,” J. Lightwave Technol. 34(10), 2510–2517 (2016).
    [Crossref]
  6. W. A. Cahyadi, Y. H. Kim, Y. H. Chung, and C.-J. Ahn, “Mobile phone camera-based indoor visible light communications with rotation compensation,” IEEE Photonics J. 8(2), 1–8 (2016).
    [Crossref]
  7. C. W. Chow, C. Y. Chen, and S. H. Chen, “Visible light communication using mobile-phone camera with data rate higher than frame rate,” Opt. Express 23(20), 26080–26085 (2015).
    [Crossref] [PubMed]
  8. W. C. Wang, C. W. Chow, L. Y. Wei, Y. Liu, and C. H. Yeh, “Long distance non-line-of-sight (NLOS) visible light signal detection based on rolling-shutter-patterning of mobile-phone camera,” Opt. Express 25(9), 10103–10108 (2017).
    [Crossref] [PubMed]
  9. T. Adiono, W. Cahyadi, and A. Salman, “DVB-T synchronizer architecture design and implementation,” in International Conference on Electrical Engineering and Informatics, 594–599 (2009).
  10. Z. Chen, X. Wang, S. Pacheco, and R. Liang, “Impact of CCD camera SNR on polarimetric accuracy,” Appl. Opt. 53(32), 7649–7656 (2014).
    [Crossref] [PubMed]

2018 (1)

2017 (1)

2016 (2)

A. Gomez, K. Shi, C. Quintana, G. Faulkner, B. C. Thomsen, and D. C. O’Brien, “A 50 Gb/s transparent indoor optical wireless communications link with an integrated localization and tracking system,” J. Lightwave Technol. 34(10), 2510–2517 (2016).
[Crossref]

W. A. Cahyadi, Y. H. Kim, Y. H. Chung, and C.-J. Ahn, “Mobile phone camera-based indoor visible light communications with rotation compensation,” IEEE Photonics J. 8(2), 1–8 (2016).
[Crossref]

2015 (2)

C. W. Chow, C. Y. Chen, and S. H. Chen, “Visible light communication using mobile-phone camera with data rate higher than frame rate,” Opt. Express 23(20), 26080–26085 (2015).
[Crossref] [PubMed]

P. H. Pathak, X. Feng, P. Hu, and P. Mohapatra, “Visible light communication, networking, and sensing: a survey, potential and challenges,” IEEE Comm. Surv. and Tutor. 17(4), 2047–2077 (2015).
[Crossref]

2014 (1)

2013 (1)

Adiono, T.

T. Adiono, W. Cahyadi, and A. Salman, “DVB-T synchronizer architecture design and implementation,” in International Conference on Electrical Engineering and Informatics, 594–599 (2009).

Ahn, C.-J.

W. A. Cahyadi, Y. H. Kim, Y. H. Chung, and C.-J. Ahn, “Mobile phone camera-based indoor visible light communications with rotation compensation,” IEEE Photonics J. 8(2), 1–8 (2016).
[Crossref]

Cahyadi, W.

T. Adiono, W. Cahyadi, and A. Salman, “DVB-T synchronizer architecture design and implementation,” in International Conference on Electrical Engineering and Informatics, 594–599 (2009).

Cahyadi, W. A.

W. A. Cahyadi, Y. H. Kim, Y. H. Chung, and C.-J. Ahn, “Mobile phone camera-based indoor visible light communications with rotation compensation,” IEEE Photonics J. 8(2), 1–8 (2016).
[Crossref]

Chen, C. Y.

Chen, S. H.

Chen, Z.

Chow, C. W.

Chung, Y. H.

W. A. Cahyadi, Y. H. Kim, Y. H. Chung, and C.-J. Ahn, “Mobile phone camera-based indoor visible light communications with rotation compensation,” IEEE Photonics J. 8(2), 1–8 (2016).
[Crossref]

Faulkner, G.

Feng, X.

P. H. Pathak, X. Feng, P. Hu, and P. Mohapatra, “Visible light communication, networking, and sensing: a survey, potential and challenges,” IEEE Comm. Surv. and Tutor. 17(4), 2047–2077 (2015).
[Crossref]

Gomez, A.

Hu, P.

P. H. Pathak, X. Feng, P. Hu, and P. Mohapatra, “Visible light communication, networking, and sensing: a survey, potential and challenges,” IEEE Comm. Surv. and Tutor. 17(4), 2047–2077 (2015).
[Crossref]

Kim, Y. H.

W. A. Cahyadi, Y. H. Kim, Y. H. Chung, and C.-J. Ahn, “Mobile phone camera-based indoor visible light communications with rotation compensation,” IEEE Photonics J. 8(2), 1–8 (2016).
[Crossref]

Koonen, T.

Liang, R.

Liu, Y.

Liu, Y. L.

Mohapatra, P.

P. H. Pathak, X. Feng, P. Hu, and P. Mohapatra, “Visible light communication, networking, and sensing: a survey, potential and challenges,” IEEE Comm. Surv. and Tutor. 17(4), 2047–2077 (2015).
[Crossref]

O’Brien, D. C.

Pacheco, S.

Pathak, P. H.

P. H. Pathak, X. Feng, P. Hu, and P. Mohapatra, “Visible light communication, networking, and sensing: a survey, potential and challenges,” IEEE Comm. Surv. and Tutor. 17(4), 2047–2077 (2015).
[Crossref]

Quintana, C.

Salman, A.

T. Adiono, W. Cahyadi, and A. Salman, “DVB-T synchronizer architecture design and implementation,” in International Conference on Electrical Engineering and Informatics, 594–599 (2009).

Shi, K.

Thomsen, B. C.

Wang, W. C.

Wang, X.

Wei, L. Y.

Yeh, C. H.

Appl. Opt. (1)

IEEE Comm. Surv. and Tutor. (1)

P. H. Pathak, X. Feng, P. Hu, and P. Mohapatra, “Visible light communication, networking, and sensing: a survey, potential and challenges,” IEEE Comm. Surv. and Tutor. 17(4), 2047–2077 (2015).
[Crossref]

IEEE Photonics J. (1)

W. A. Cahyadi, Y. H. Kim, Y. H. Chung, and C.-J. Ahn, “Mobile phone camera-based indoor visible light communications with rotation compensation,” IEEE Photonics J. 8(2), 1–8 (2016).
[Crossref]

J. Lightwave Technol. (2)

Opt. Express (3)

Other (2)

T. Adiono, W. Cahyadi, and A. Salman, “DVB-T synchronizer architecture design and implementation,” in International Conference on Electrical Engineering and Informatics, 594–599 (2009).

D. C. O’Brien, “Optical wireless communications: current status and future prospects,” in Proc. IEEE Summ. Top., Newport Beach (2016).

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Figures (8)

Fig. 1
Fig. 1 Proposed ICC (a) experimental setup (b) block diagram and (c) schematic of the transmitter.
Fig. 2
Fig. 2 Transmitter unit (a) assembly of the transmitter unit and (b) the installed transmitter unit.
Fig. 3
Fig. 3 Receiver unit (a) assembly of the camera and (b) assembled camera unit and holder.
Fig. 4
Fig. 4 Data transmission: (a) data packet and (b) measured output of the LED driver.
Fig. 5
Fig. 5 Flowchart of ICC synchronization and demodulation.
Fig. 6
Fig. 6 Thresholding (a) captured image from the camera (b) mean intensity of each pixel row (c) mean intensity of each pixel column and (d) binary thresholding performed after the AIC.
Fig. 7
Fig. 7 Experiment for coverage and positioning (a) ICC diagram (b) SNR measurements.
Fig. 8
Fig. 8 Transmission quality experiments (a) BERs with the fixed data rate of 6.72 kbit/s and (b) data rates with the target BER of 10−3.

Tables (2)

Tables Icon

Table 1 Positioning Accuracy with a Resolution of 640 × 480 pixels

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Table 2 Positioning Accuracy with a Resolution of 1280 × 720 pixels

Equations (1)

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γ ( x ) = k = x x + H 1 r ( k ) × r ( k + N )

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