This document presents a dissertation written by Willy Anugrah Cahyadi for the degree of Doctor of Philosophy at Pukyong National University in November 2018. The dissertation focuses on improving the data rate and performance of optical camera communications (OCC) by investigating downlink and proposing uplink solutions. Key contributions include achieving a downlink rate of 11,520 bits/s using a split-frame technique and a rate of over 2 Mbits/s using high-density modulation with a neural network. An uplink scheme using a smartphone display is also presented achieving an effective data rate of 360 bits/s. The aim is to address critical limitations of OCC and provide complementary solutions within the standardized use cases.

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Partial fulfillment for the Degree of
Doctor of Philosophy
Willy Anugrah Cahyadi
Advisor: Prof. Yeon Ho Chung
Department of Information and Communications Eng.
Pukyong National University
November 23th, 2018

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Outline
2
Introduction
Motivation and Research Objectives
Main Contributions
• Rate of Downlink OCC
• Rate of Uplink OCC
• Performance of OCC
Conclusions
Future Scope

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INTRODUCTION
Optical Wireless Communications
Optical Camera Communications

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Optical Wireless Communications
 Transmitting information using light without
fiber
– Light propagation through air/gas, liquid,
solid (diffuser), and vacuum
 Advancements of LED  light transmitter
– Miniaturized and highly efficient for generating light
– Can be flickered with a transition period < ms
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Optical Wireless Communications
 Light is more efficient for line-of-sight (LOS)
compared with radio wave
– Directed LOS transmission
– Robustness against weather
– Applicable for underwater communication
 Unregulated optical spectrum
– 10000× more bandwidth compared to radio wave
spectrum
– Imposes less health risks compared to radiation from
radio waves
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Electromagnetic Spectrum
6
Radio waves bandwidth ≈ 300 GHz
IR theoretical bandwidth ≈ 12.5 THz

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Electromagnetic Spectrum
7
Visible light theoretical bandwidth ≈ 320 THz

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Electromagnetic Spectrum
8
10nm 200nm
100nm 280nm
Vacuum UV
315nm 400nm
UV-C UV-B UV-A
Completely absorbed by
ozone layer
UV theoretical bandwidth ≈ 75 PHz

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Classification of OWC
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Indoor Outdoor

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INTRODUCTION
(Optical Camera Communications)

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Principles
 Pragmatic version of VLC
– OCC utilizes a camera receiver instead of PD
– Everybody practically carries a camera everywhere
– An available receiver for everyone to use
 Main theme of this dissertation
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Principles
 Camera receiver
– Single or multiple cameras
 Transmitters:
– Single (illumination) LED
– Array of LEDs
– Digital display
 Advantage
– 2D image capture
 Disadvantage
– Image capture is relatively
slow
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Standards: IEEE 802.15.7
 IEEE 802.15  Working group of IEEE
– Specifies the WPAN standards
– IEEE 802.15.7 is a Task Group in charge of Standards
for Visible Light Communication
– There are 15 subgroups of IEEE 802.15
• TG7r1: subgroup for Optical Wireless Communications
 TG7r1 task group handles
revisions to IEEE 802.15.7-2011
Standard
– LED-ID: wireless light ID
– OCC: Image sensor
communications

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IEEE 802.15.7r1: LED-ID Technology
 LED-ID
– Wireless light ID system using LED lights

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IEEE 802.15.7r1: Concept of OCC
 Modulate LED light source with data bits
 Received by a camera
– That decodes the bits and extracts the data
 High-precision positioning solution
– Using smart device camera
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IEEE 802.15.7r1: Use Cases
 LED QR/2D Color Code
– LED based barcode as a tag and smartphone camera as the reader
 P2P Tx/Rx & Relay Application
– Device-to-device short range communication
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IEEE 802.15.7r1: Use Cases
 Signage/Display
– Tag: Display/Signage
– Reader: Smartphone
camera
 Exhibition and
Store Service
 In-flight
Service
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IEEE 802.15.7r1: Use Cases
 Underwater / Seaside communication
 Smart living: Smart office and smart home
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Critical Issues in OCC
 Information carrier in 2D image capture
– Spatial coordinate, intensity, color, and shape
 Image processing
– Generally has a slow capture rate
• Millions of pixels processed by the camera (Megapixels)
• Cameras in general: 30-60 fps
• Slow-motion cameras: 240-480 fps
• High-speed cameras: 10000-1 million fps (reduced resolution)
– Compared to PD in VLC  up to 10 GHz sampling
rate
 OCC data rate is somehow limited
– tens of bit/s ~ few Kbit/s
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Critical Issues in OCC
 OCC has been studied for either LOS link or
NLOS link only, not both
 Uplink channels for OCC have never been
explored
– It is essential to support the uplink in indoor wireless
communications
 Flickering LEDs or displays
– Cause serious focus issues on camera receiver
 Static cameras are only considered in the OCC
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MOTIVATION
AND
OBJECTIVES
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Motivation
 Why OCC?
– OCC has been formulated in the 802.15.7r1
standardization activity for the past 7 years
• The most recent update will be released at the end of
Nov 2018
– OCC is the most practical or viable indoor OWC scheme
• Camera receiver is available on daily used smartphones
– OCC has much potential and variation, but its rate and
performance still need to be enhanced significantly for
practical or commercial applications in the near future.
• The rate is somewhat limited to a few kbps in the literature
• The performance is also not competitive, compared with its RF
counterparts

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Objectives
 Providing improved and complementary solutions
– To address the critical disadvantage (rate, performance)
of OCC
– Within the scope of the standardized OCC use cases
 Investigating data rate improvements
– Both downlink and uplink channels in OCC
– Higher than existing studies in OCC
 Proposing uplink solutions for OCC
– Undocumented in the literature
 Investigating complementary solutions
– Maintaining illumination provision
– Providing a wide orientation in OCC
• Both LOS and NLOS
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RATE OF DOWNLINK OCC
• Split-frame Technique
• High-density Modulation with Neural Network

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Split-frame Technique
 An alternate method to increase the camera
capture rate
– Utilizing dual camera
• Multiple cameras are common in smartphones
– Capturing the transmitter on each camera
– Splits the capturing process  2× data rate increase
Experiment distance
Transmitter LCD
Data generator
computer
Data processing
computerDual camera on
smartphones
(receivers)

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Split-frame Technique
 Acquires half of the capture frame
– Reduces the frame capture period by half
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Rolling Shutter Demodulation
(RSD) Split-frame

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Experiment Parameters
Parameter Values
Capture device Android-based smartphone
Video capture resolution 1280×720 pixels
Camera lens and sensor size
f/2.2 aperture, 31 mm lens, 64° diagonal FOV,
and 1/3” sensor size.
Video capture rate
30 and 60 fps (standard shutter)
30, 60, and 120 fps (split-frame)
Frame period 17, 20, 25, 33, 40, 50, 67, and 100 ms
Transmitter flicker rate
(LCD refresh rate)
60, 50, 40, 30, 25, 20, 15, and 10 Hz
Transmitter size 30×30 cm2
Experimented distances 100 – 300 cm (20 cm increments)
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 Split-frame enables faster capture rate
– 60 fps  120 fps

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Fitting the Transmission Frame
Full-fit frame Partial-fit frame
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 The requirement for split-frame
– Equally divides the transmission frame
– Full-fit frame:
TX frame fills the camera capture frame fully
– Partial-fit frame:
TX frame fills the camera capture frame partially

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Achievable Data Rate
 Data rate depends on the transmitter frame period
 11,520 bit/s data rate was achieved
– Effective capture rate of 120 fps

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BER vs Distance

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Comparison
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Parameters RSD Split-frame
Transmission distance 50 cm 200 cm
Increases resolution + data rate
+ transmission
distance
+ data rate
Increases number of
cells/LEDs
+ data rate
− transmission
distance
+ data rate
Frame fit Strictly full-fit
Partial-fit or
full-fit
Transmitter type LED only
LED and
Digital displays

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Increasing Data Rate in OCC
 Common methods to increase data rate
– Increase camera capture rate, although it is
impractical for existing devices, such as smartphones
– Increase the number of LEDs/cells, color, and
intensity
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126.72 Kbit/s @ 1.4 m distance
330 fps FPGA-controlled camera
Huang, W, et al., “Design and implementation of a real-time CIM-MIMO OCC system,” Optics
Express, vol. 24, 2016.

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Increasing Data Rate in OCC
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Boubezari, S, et al., “Smartphone camera based visible light communication,” Journal of Lightwave Technology, vol. 34, 2016.
112.5 Kbit/s
15 cm distance
Monochrome
75×50 cells

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High-density Modulation with NN
 A denser modulation is proposed to achieve the
Mbit/s data rate efficiently
– Practical smartphone camera
– Existing screen-based transmitter
 High-density modulation (HDM)
– Combines 4 modulation entities:
1. Cell (group of pixels in digital display)
2. Color
3. Intensity
4. Shape
– Requires an NN for demodulation
 A data rate of 2.66 Mbit/s for a distance of up
to 20 cm
– Device-to-device OCC
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High-density Modulation with NN
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Experiment Setup
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 Screen size: 7.2 cm×12.7 cm

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Structure of HDM Scheme
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0 0 0 0
0 0 0 1
0 0 1 0
0 0 1 1
0 1 0 0
0 1 0 1
0 1 1 0
0 1 1 1
1 0 0 0
1 0 0 1
1 0 1 0
1 0 1 1
1 1 0 0
1 1 0 1
1 1 1 0
1 1 1 1
4 bits
9 bits
• 3 bits of R
• 3 bits of G
• 3 bits of B
16 shapes
512 color
intensities Shape
modulation
Cell formulation
(78×44 cells)
Color +
intensity
modulation
Data
bits

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Structure of TX Frame
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 78×44 cells
 20 anchors
– 2 on each
corner
– 2 on each
side
– 4 on center

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Anchors – Color calibration
 Anchors for color calibration
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Color Chromaticity:
1. Black
2. Red
3. Green
4. Blue
5. White
6. Magenta
7. Yellow
8. Cyan
Intensity:
12.5% gray
 25% gray
 37.5% gray
 50 % gray
 62.5% gray
 75% gray
 87.5% gray
 100% gray (white)
The CIE 1931 color space
chromaticity diagram

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TX
RX
Bits
Color
composition
Bits
8 levels
of Red
Anchor
identification
8 levels
of Green
8 levels
of Blue
512 color
intensity
palette
HDM
Anchors for
color
chromaticity
Anchors for
intensity
TX
Frame
Perceived color
chromaticity
Perceived intensity
Calibrated
512 color intensity
palette
References
HDD
Color Calibration Scheme
Color calibration
Camera
imperfections
Display screen imperfections
Optical
channel

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Trained NN Structure
41
Neural Network (NN) Structure
Layer 1: Layer 2:
36 bits
Unique bit patterns
(16 bits)
36 bits
36 bits
NN33×33
pixels
16 shapes
1
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2
1
2
16
Output:
16 bits
Input:
36 bits

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System Diagram
42
TX
Random
bits
Received
bits
Color intensity
modulation
Frame
generation
LCD DisplayDisplay
RX
Shape
modulation
HDM
Camera
capture
2X resolution
Synchronized
framesHDD
Color
calibration
Smartphone
NN
Filtering
Optical
Channel

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Experiment Parameters
No.
HDM format
(NE, NC, NS)
Transmitter Receiver
TX screen
resolution
Flickering
rate
Camera
resolution
Camera
capture rate
1 78×44, 512, 16 TX1 (2560×1440) 60 Hz 1280×720 120 fps
2 78×44, 512, 16 TX2 (1280×720) 60 Hz 1280×720 120 fps
3 78×44, 512, 16 TX1 (2560×1440) 30 Hz 1920×1080 60 fps
4 39×22, 512, 16 TX1 (2560×1440) 60 Hz 1280×720 120 fps
5 39×22, 512, 16 TX1 (2560×1440) 30 Hz 1920×1080 60 fps
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 TX 1 screen size: 7.2 cm×12.7 cm (smartphone)
 TX 2 screen size: 9.6 cm×15.1 cm (tablet)

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Experiment Results
44
Config. 2:
– Larger screen
Config. 3:
– Higher camera
resolution
– Reduced
capture rate
Config. 4:
– Reduced cells
Config. 5:
– Reduced cells
– Higher camera
resolution

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Experiment Results
45
 PSNR is utilized to evaluate reception quality
 A minimum PSNR of 22dB is required
– Adequate transmission quality

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RATE OF UPLINK OCC
• Low Rate Display-based Solution
• High Rate Near-infrared-based Solution

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Display-based Uplink Scheme for OCC
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Display-based Uplink Scheme for OCC
 2×2 RGB cells displayed on smartphone screen
– Resolution: 2560×1440 pixels
– Size: 50 mm × 50 mm
– Flicker rate: 30 Hz
 Chamber dimension (cm):
100×100×200
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Display-based Uplink Scheme for OCC
 Camera
– Capture rate: 60 fps
– Resolution: 1280×720 pixels
– FOV: 60°
 Effective data rate: 360 bit/s
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Display-based Uplink Scheme for OCC
50
FEC limit

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Display-based Uplink Scheme for OCC
 Considerable data rate limitation
– Smartphone screen size is too small for practical
uplink distance transmission
– Glare from the smartphone screen is significant
– 360 bit/s  hardly extendable
– 90 cm distance  60° orientation angle
 Smartphone screen is dedicated
for communication
– Inconvenience for the user
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High Rate Near-infrared-based Solution
 Infrared-based proximity sensors on
smartphones (with near-IR LEDs)
– IR is invisible to human eyes  non-disruptive
– Visible to the camera
• Especially if the IR-filter is removed
 A potential uplink transmitter
52
IR LEDs

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Infrared LED Camera Comm. (ICC)
 Transmitter: IR LEDs with wavelength of 940 nm
 Receiver: a modified webcam
– Removed IR blocking filter
– IR band-pass filter (Hoya R-72)
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distance
Rx
Processing
PC
Tx
Tx
MCU
(modulation)
IR LEDs
(940 nm)
Data packet
generation
Rx
Processing PC
(demodulation)
Camera
(Removed IR blocking filter)
Retrieved data
packet
LED
driver
Diffuser + IR band pass filter
Fresnel lens

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Transmitter and Receiver Units
54
Flexible
arm
IR LEDs
Fresnel lens
Connected to LED
driver and MCU
Camera
holder
Camera
unit
IR bandpass
filter (940nm)
Diffuser +
holder
Modified
camera
IR blocking
filter removed
Custom designed
mounting

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MCU + LED Driver Schematic
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Data Packet
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PayloadHeader
4-bit 28-bit
Cyclic prefix
1-bit
zero gap
 Header is a cyclic prefix of the payload
– Important for synchronization

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Flowchart of ICC Positioning
57
START
Acquire frame +
calculate mean intensity
Fix camera
exposure time
to 1/4096 s
Mean intensity
of pixel rows
(mR)
Mean intensity
of pixel columns
(mC)
Estimate Tx
position
LY=(max (mR) – σR) LX=(max (mC) – σC)
μX= mean
(mC)

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Demodulation
END
Start demodulation on
payload data
Yes
NoHeader
acquired?
Normalize mF based on the
threshold
MLE
Acquire
the pixel columns having
intensity < μX
Mean intensity
of filtered pixel
rows (mF)
AIC
Flowchart of ICC Sync + Demodulation

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AIC Algorithm
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MLE Algorithm
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Correlation
Pixel rows
𝛾 x =
𝑘=𝑥
𝑥+𝐻−1
𝑟 𝑘 𝑟 𝑘 + 𝑁

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Coverage Test
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Parameter Values
Room dimension 130 cm×81 cm×200 cm
Video capture resolution 640×480 pixels
Camera FOV 60° diagonal FOV
Video capture rate 60 fps
Exposure period 1/4096 s
Ambient illuminance 800-900 lx (from illumination)

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Coverage Test
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SNR(dB)
Offset from the center (cm)
 Wider FOV of the camera
– More consistent SNR for uplink on 3 exemplary positions
of the transmitter compared to a PD solution

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Fixed Data Rate of 6.72 Kbit/s
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BER
Transmission distance (cm)
10-4
SNR(dB)
5
10
15
20
25
30
35
40
45
20 40 60 80 100 120 140 160 180 2000
10-3
10-2

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Data Rates with Target BER of 10-3
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Transmission distance (cm)
20 40 60 80 100 120 140 160 180 200
Datarate(bit/s)
7000
6000
5000
4000
3000
2000
1000
0
SNR(dB)
5
10
15
20
25
30
35
40
45

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Infrared-based Indoor Positioning
 Indoor positioning system (IPS) is an important
breakthrough
– GPS does not work indoors
– Uplink channel in OCC utilizes an IR LED
• a viable IPS solution
 IR LED  An invisible beacon utilized for IPS
 Surveillance camera is often available in indoor
environments
– The camera is sensitive to IR light
(switchable IR blocking filter)
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Day mode Night mode

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Infrared-based Indoor Positioning
66
 The surveillance camera is set to night-mode
– Captures both visible light and IR light
– Requires an algorithm to minimize the ambient light
interference
– Wide FOV of 170
 Designed beacon
– Similar to IR LED on the proximity sensors of the smartphone

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Infrared-based Indoor Positioning
67
 Experiment setup

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Infrared-based Indoor Positioning
68
 ROI for Measurement Area

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Algorithm of Positioning Scheme
69
Start
RGB channel mixing
(monochrome)
Fixed exposure
period
Surveillance
image
Red channel retrieval
(monochrome)
Frame capture start
Intraframe positioning
End

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Intraframe Positioning Scheme
70
𝑥 𝑝
𝑥𝑖
= 𝑆
2𝑑 tan−1 1
2
𝛼
𝑣 𝑤
𝑦𝑝
𝑦𝑖
= 𝑆
2𝑑 tan−1 1
2
𝛽
𝑣ℎ
 (𝑥𝑖, 𝑦𝑖): acquired
beacon’s coordinate
 (𝑥 𝑝, 𝑦𝑝): physical
beacon’s coordinate
 𝛼: horizontal FOV
 𝛽: horizontal FOV
 𝑆: scaling constant
 𝑑: distance between
camera and the experi-
ment plane

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Experiment Parameters
71
Parameter Values
Room dimension 350 cm × 390 cm × 220 cm
Flicker rate of the beacon 2 KHz
Operating voltage of the beacon 5V
Operating power of the beacon 150 mW
Ambient illuminance (minimum – maximum) 480 - 1120 lx
Exposure periods of the camera
1/500 s, 1/1000 s,
1/2000 s and 1/4000 s
Video resolution of the camera 1920 × 1080 pixels
Capture rate of the camera 30 fps
FOVs of the camera
(diagonal, horizontal, and vertical)
170°, 168°, and 164°
Fixed height of the beacon 100 cm

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Various Exposure Periods
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1/500 s
1/1000 s
115 cm
37 cm
AccuracyCaptured frame

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Various Exposure Periods
73
1/2000 s
1/4000 s
1 cm
1 cm
AccuracyCaptured frame

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RGB Channel Mixing
 The exposure period is fixed to 1/2000 s
– Limit the interference
– Captured images are darker
 Mixing the RGB channels
– Produces brighter images  for surveillance
74
RGB
channel
mixing
Captured frame Frame for surveillance

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Results: Static Beacon Positions
75
Errors:
due to the interference
light near the beacon
– The camera captures both
visible and IR light

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Results: Static Beacon Positions
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Static positions
Mean positioning
errors
Misidentified
frames
Position 1 2 cm 0%
Position 2 4 cm 1%
Position 3 2 cm 5%
Position 4 6 cm 5%
Position 5 2 cm 2%
Position 6 3 cm 3%
Position 7 2 cm 1%

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Results: Moving Beacon
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Moving
speed
(approximate)
Exposure
period
Mean
positioning
errors
Misidentified
frames
50 cm/s 1/2000 s 3 cm 3%
50 cm/s 1/4000 s 2 cm 1%
100 cm/s 1/2000 s 4 cm 3%
100 cm/s 1/4000 s 3 cm 1%
Results: Moving Beacon
78
Shorter exposure period  more accurate positioning with less misidentified frames
Intraframe algorithm does not analyze the relation between several frames

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IR-based IPS
 Experimentally proven
– Centimeter scale positioning
– Both static and moving beacon
– Mean positioning error is limited to 6 cm
 Further improvements in the future
– Real-time image analysis
• Dynamic exposure period and threshold instead of fixed
ones
– Multiple cameras
• Increased accuracy + coverage behind obstacles
– Interframe positioning algorithm
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PERFORMANCE OF OCC
• Focus and Light Metering with Additional
Illumination LEDs
• Wide Orientation Transmission with
Illumination

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Performance of OCC
 Data rate is only one performance factor
 There are performance factors important to OCC
– Camera automatically obtains the optimum
light metering based on its focus
• LED / screen is flickering  camera
– Strict orientation of the camera (receiver)
 Performance enhancements of OCC is important
for indoor environments
– Practical schemes are required
– Maintain illumination provision is also preferred
– OCC is either investigated for LOS only or NLOS only

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I-OCC Scheme
 Employs additional white illumination LEDs
– References for both focus and light metering
• Help focus the camera while the transmitting LEDs
are flickering
– Ensuring the illumination provision
• Illumination is not affected by the transmitting LEDs
LED
driver
PC
Smartphone
ServerDot matrix
LED array

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Block Diagram of I-OCC
Rx Rotation
compen-
sation
Smartphone
camera
Data
evalua-
tion
Demap
-ping
Tx
Mapping
LED driver +
dot matrix LED
Data
genera-
tion
Optical channel

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Keyframe Structure
84
 Rotation marker
 Alignment marker
(𝒌 − 𝟏) framesKF
𝒌 frames
(𝒌 − 𝟏) framesKF
𝒌 frames
- - - -
𝑵 − 𝟏 framesKF
𝑵 frames (full transmission frames
Keyframe 𝑭
(1 frame)
Keyframe 𝑭 𝟏
(1 frame)
Keyframe 𝑭 𝒏
(1 frame)
Aperiodic
Periodic

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Alleviating the Blooming Effect
85
Misfocused Correctly focused

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Experimental Parameters
Parameters Values
Capture devices
2013 Android-based smartphone (Cam 1)
2010 iOS mobile device (Cam 2)
Video capture resolution
Cam 1: 1920×1080 pixels
Cam 2: 1280×720 pixels
Capture rate
Cam 1: 60 fps, variable capture rate
Cam 2: 30 fps, constant capture rate
Total captured frame
25440 frames for Cam 1, and
11160 frames for Cam 2
Frame period 25, 50, 67, and 100 ms
Experimented distances 5 cm, 10 cm, 20 cm, and 30 cm
Ambient illumination 6 lx
Illumination LED 3.143 V, 22.37 mA
Dot matrix LED 4.31 V, 7.44 mA
86

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System Laboratory
Achievable Data Rate (𝐷 𝑅)
 𝐿 𝑁: number of LEDs for data transmission
 𝑡 𝑟: LED flickering rate (LFR)
 𝐹𝑝: reduction of data rate due to keyframe
insertion
 T: transmission period
87
𝐷 𝑅 = 𝐿 𝑁 𝑡 𝑟 − 𝐹𝑝
𝐹𝑝 =
𝐿 𝑁
𝑇
, 𝑎𝑝𝑒𝑟𝑖𝑜𝑑𝑖𝑐 𝑘𝑒𝑦𝑓𝑟𝑎𝑚𝑒
10𝐿 𝑁, 𝑝𝑒𝑟𝑖𝑜𝑑𝑖𝑐 𝑘𝑒𝑦𝑓𝑟𝑎𝑚𝑒

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System Laboratory
Results of Simulation and Experiment
 Experimented data rate of 1280 bit/s
– 30 fps camera capture rate
88

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System Laboratory
Results of Experiment (BER)
89
Distance LFR Cam 1 Cam 2
5 cm
10
14
20
0.0
0.0
0.0
0.0
0.0
0.0
10 cm
10
14
20
0.0
0.0
0.0
0.0
0.0
0.0
20 cm
10
14
20
0.0
0.0
0.0
0.0
0.0
0.0
30 cm
10
14
20
0.0016
0.0047
0.0813
-
-
-

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Transmission
System Laboratory
Data Detection
 Region-of-Interest is set initially by identifying
keyframe
 Differential detection threshold
– Quantized intensity  binary thresholding
90
Data RoI
Red Color
Channel
Quantized
Intensity

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Transmission
System Laboratory
Illuminance Measurement
91
Distance
Illumination
(lx)
Dot matrix
(lx)
Illumination +
dot matrix (lx)
5 cm 2330 - 2340 206 - 254 2190 – 2240
10 cm 1312 - 1313 146 – 161 1369 – 1389
20 cm 597 – 598 116 – 126 624 - 631
30 cm 303-304 96-100 305-312
 Large difference of the illuminance level
– Dot matrix LEDs (flickering red light)
do not effect illumination (white light)

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Transmission
System Laboratory
Wide Receiver Orientation (WRO)
 Existing OCC researches consider either
LOS only or NLOS only
 WRO scheme proposes a wide orientation for
both LOS and NLOS
– A specially designed transmitter
– Utilizing diffuse reflection for the NLOS link
– RSD based demodulation for reception
– Illumination is still provided
92
Source: T. Nguyen, A. Islam, T. Hossan and Y. M. Jang, “Current Status and
Performance Analysis of Optical Camera Communication Technologies for 5G
Networks,” in IEEE Access, vol. 5, pp. 4574-4594, 2017.

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Wide Receiver Orientation (WRO)
93

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System Laboratory
Block Diagram of The WRO Scheme
94
Tx MCU
(Modulation)
Proposed
transmitter
Data packet
generation
Rx Offline
demodulation
Smartphone
camera
Retrieved data
packet

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Transmission
System Laboratory
Experimental Setup
95
Photo of the
chamber
Wall
materials

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Transmission
System Laboratory
Specially Designed Transmitter
96
 4 directional LEDs (angled)
– Distribute illumination equally to all direction
 1 central LED
 Diffuser: polymorph plastic
– Blend the light emission

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Transmission
System Laboratory
Intensity of Each Pixel (𝑁𝑝)
 𝐾 : Calibration constant
 𝑓𝑠 : lens aperture
 𝑆 : ISO sensitivity of the camera
 𝐸𝜌/𝜋 : a total amount of luminance entering the camera
from a diffused reflection
 𝐸 : illuminance that falls on the sensor surface
 𝜌 : reflectance of a surface causing diffuse reflection
97
𝑁𝑝 = 𝐾
𝑡𝑆
𝑓𝑠
2
𝐸𝜌
𝜋

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Transmission
System Laboratory
Adaptive Blooming Mitigation (ABM)
98

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ABM: Filtered Pixel Rows
99

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Normalized Intensity
100
 Output of ABM
 Final algorithm is MLE

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Transmission
System Laboratory
Experimental Parameters
Parameter Values
Chamber dimension 40 cm × 40 cm × 40 cm
LED flickering rate 4 KHz ( 2 bits / cycle)
Data rate
6.72 Kbit/s (fixed)
Excluding the header bits and zero gap
Camera capture resolution 1920×1080 pixels (video capture)
ISO value 2700
Exposure period 1/6000 s
101

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System Laboratory
Experimental Parameters
Parameter Values
MCU ATMega328P with an operating clock of 16 MHz
Center LED
Rated power: 3 W
Operating voltage: 3.4 V
Color temperature: 6000K
Directional LEDs
Rated power: 3 W
Operating voltage: 3.4 V
Color temperature: 6000K
Smartphone camera
LG V10 (F600L)
Operating system: Android 7.0
Lens aperture: f/1.8
FOV: 78°
102

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System Laboratory
Illumination Distribution
103

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System Laboratory
Illumination Distribution
104

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System Laboratory
Illumination Distribution
105
 Equally distributed
illuminance of 80 lx
and 70 lx
– Distance of 60 cm and
70 cm

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System Laboratory
Reflectance
 𝜌 : ratio of the reflected illuminance to incident
illuminance
 𝐸𝑟: reflected illuminance
 𝐸𝑖: incident illuminance
106
𝜌 =
𝐸𝑟
𝐸𝑖

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Transmission
System Laboratory
Measured Reflectance
Material Illuminance reflectance
White wood panel 0.5771
White paper 0.6129
Glossy PVC wallpaper 0.4158
107
 Higher reflectance: more diffused reflection
– White paper has the highest reflectance
– Measurement distance: 10 cm from the wall
– Both incident and reflection angles are 45°

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Experiments
108

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Results: Multiple Height
109

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System Laboratory
Results: Multiple Orientations
110

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System Laboratory
Results: Multiple Orientations
111

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System Laboratory
Results: Moving Receiver
112

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System Laboratory113
CONCLUSIONS
and
FUTURE SCOPE

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System Laboratory
Conclusions
 The present study has considered the two
critical issues of rate and performance for OCC
to evolve further.
 The data rate has been investigated on both
downlink and uplink channel. We have obtained a
higher data rate than the existing OCC schemes
– ≈ 10 times the data rate of existing schemes
for downlink  Mbit/s rate
– Up to 6.72 Kbit/s for uplink
 Performance improvements have also been
investigated in terms of focus and light metering as
well as wide orientation transmission.
114

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Conclusions
 In addition, an infrared based indoor
positioning scheme has been investigated.
– Novel approach using infrared
– Non-disruptive and practical positioning with
centimeter-scale accuracy
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Future Scope – OCC vision
 Rapid development of smartphone camera.
 Higher data rate for OCC in the future is
envisioned.
 NPU (or NN) implemented on smartphones.
 OCC is expected to be very viable and
pragmatic short-range indoor wireless
communication.
 IEEE standard will be announced in
January 2019.
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Future Scope – Further works
 Channel model formulations through
experiments
 Increasing efficiency of the existing
modulations
 Investigating multiple camera schemes
– Beneficial for increasing data rate and robustness
 Investigating advanced selective capture
– Improvement of the split-frame technique
117

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LIST OF PUBLICATIONS

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Transmission
System Laboratory
Journal Papers (1st Authorship)
 Willy Anugrah Cahyadi and Yeon Ho Chung, “Wide Receiver
Orientation Using Diffuse Reflection in Camera-based Indoor
Visible Light Communication,” Optics Communications, vol. 431,
pp. 19-28, 2018. (SCI)
 Willy Anugrah Cahyadi and Yeon Ho Chung, “Smartphone
Camera based Device-to-device Communication Using Neural
Network Assisted High-density Modulation,” Optical
Engineering, vol. 57, no. 9, p. 096102, 2018. (SCI)
 Willy Anugrah Cahyadi and Yeon Ho Chung, “Experimental
Demonstration of Indoor Uplink Near-infrared LED Camera
Communication,” Optics Express, vol. 26, No. 15, pp. 19657-
19664, 2018. (SCI)

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Journal Papers (1st Authorship)
 Willy Anugrah Cahyadi and Yeon Ho Chung, “Experimental
Demonstration of VLC based Road Wetness Detection
Techniques for Preventing Danger of Hydroplaning,” The Journal
of Korean Institute of Communications and Information Science
s (J-KICS), vol. 42, no. 08, Sept 2017.
 Willy Anugrah Cahyadi, Yong-hyeon Kim, and Yeon-ho Chung,
“Dual Camera based Split Shutter for High-rate and
Long-distance Optical Camera Communications,” Optical
Engineering, vol. 55, no. 11, p. 110504, 2016. (SCI)
 Willy Anugrah Cahyadi, Yong Hyeon Kim, Yeon Ho Chung, and
Chang-Jun Ahn, “Mobile Phone Camera-Based Indoor Visible
Light Communications with Rotation Compensation,”
IEEE Photonics Journal, vol. 8, no. 2, pp. 1-8, 2016. (SCIE)

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Journal Papers (2nd Authorship)
 Tahesin Samira Delwar, Willy Anugrah Cahyadi, and Yeon-ho Chung, “
Visible Light Signal Strength Optimization Using Genetic Algorithm In
Non-line-of-sight Optical Wireless Communication,” Optics Communic
ations, vol. 426, pp. 511-518, 2018. (SCI)
 Shivani Teli, Willy Anugrah Cahyadi, and Yeon-ho Chung, “High-Speed
Optical Camera V2V Communications Using Selective Capture,” Photo
nic Network Communications, pp. 1-7, 2018. (SCI)
 Shivani Teli, Willy Anugrah Cahyadi, and Yeon Ho Chung, “Trained Ne
urons-based Motion Detection in Optical Camera Communications,”
Optical Engineering, vol. 57, no. 4, p. 040501, 2018. (SCI)
 Arsyad Ramadhan Darlis, Willy Anugrah Cahyadi, and Yeon Ho Chung,
“Shore-to-Undersea Visible Light Communication,” Wireless Personal
Communications, pp. 1-14, December 2017. (SCIE)

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Journal Papers (2nd Authorship)
 Shivani Teli, Willy Anugrah Cahyadi, and Yeon Ho Chung, “Optical Ca
mera Communication: Motion Over Camera,” IEEE Communications
Magazine, vol. 55, no. 8, pp. 156-162, August 2017. (SCI)
 Yong Hyeon Kim, Willy Anugrah Cahyadi, and Yeon Ho Chung, “Experi
mental Demonstration of VLC-Based Vehicle-to-Vehicle Communicatio
ns Under Fog Conditions,” IEEE Photonics Journal, vol. 7, no. 6, pp. 1-9
, 2015. (SCIE)
 Durai Rajan Dhatchayeny, Willy Anugrah Cahyadi, and Yeon Ho Chung
, “An Assistive VLC Technology for Smart Home Devices Using EOG,”
Wireless Personal Communications, pp. 1-9, August 2017. (SCIE)
 Trio Adiono, A. Pradana, Rachmad V. W. Putra, Willy Anugrah Cahyadi
, and Yeon Ho Chung, “Physical Layer Design with Analog Front End
for Bidirectional DCO-OFDM Visible Light Communications,” Optik, Int
ernational Journal for Light and Electron Optics, March 2017. (SCI)

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Thank You
+
Q & A