Jordan Choudhari presented a seminar on indoor positioning algorithms based on Light Fidelity (Li-Fi). The presentation included an introduction to Li-Fi, the aim to study different Li-Fi indoor positioning algorithms, and a literature survey of 8 papers on Li-Fi positioning techniques. It also compared Wi-Fi and Li-Fi, analyzed different algorithms, discussed applications and misconceptions of Li-Fi, and concluded Li-Fi provides a better alternative to Wi-Fi for indoor positioning.

1. Seminar III Presentation
On
“Study of Indoor Positioning Algorithms based
on Light Fidelity ”
By
Jordan Choudhari
(SY ME-IT)
Guide
Dr. R . N. Phursule
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2.  Introduction
 Aim and Objectives
 Literature Survey
 Comparative Study
 Comparison Analysys
 Applications
 Common Misconceptions
 Conclusion
 References
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3. Moving comfortably in new environment is not possible because we
are new to it.
If we are having knowledge about that environment than it may be
possible, Hence to overcome this factor we are proposing a new
concept(rather than Wi-Fi) in which we can track our location with the
help of our smartphone.
Our location would be traced with the help of Li-Fi system.
Introduction
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4. Introduction
Figure 1: VLC frequency spectrum [1]
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5. Aim : To study different algorithms for Indoor Positioning system using
light –Fidelity (Li-Fi).
Objectives :
i. Study various proposed algorithms for LiFi
ii. Provide real time location and guide users to their destination within
reasonable distance using Light Fidelity (Li-Fi).
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6. Paper 1: Indoor Positioning System Using Wi-Fi & Bluetooth
Low Energy Technology
 INDOOR POSITIONING SYSTEM
Wireless indoor positioning system is a system to locate objects or people inside a building
using radio waves, magnetic fields, acoustic signals, or other sensory information collected
by mobile devices
 RSS SCHEME FOR INDOOR NAVIGATION
It is most common for positioning schemes to estimate the unknown receiver’s position by
exploiting the geometric relations between transmitters and the receiver. Estimating
Received Signal Strength (RSS), Angle of Arrival (AoA) and timing information such as
Time of Arrival (ToA), Time Difference of Arrival (TDoA).
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7. Paper 1: Indoor Positioning System Using Wi-Fi & Bluetooth
Low Energy Technology
 WI-FI BASED INDOOR POSITIONING
Figure 2: Trilateration[2]
By using dense network
of access points, taking
RSSI measurements over
Wi-Fi signals,
determining distance of
user’s device from
individual access points,
and finally applying
trilateration
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8. Literature Survey(1/8)
1. Visible Light communications based indoor positioning via compressed sensing [2]
Author: Kristina Gligorić´, Manisha Ajmani, Dejan Vukobratović´ andSinan Sinanovic´
Year and Publication: IEEE COMMUNICATIONS LETTERS, VOL. 22, NO. 7, JULY
2018
Methodology:
LEDs transmitting their positional information simultaneously and at the user's
device, installed at a fixed location inside the infrastructure and continuously
transmit their location.
Mobile optical receiver comes in the vicinity of the LED transmitter, it receives
an optical signal and it decodes the LED position to locate its own position.
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9. Literature Survey(2/8)
2. Indoor Position by LED Visible Light communication and Image Sensors
[3]
Author: Mohammad Shaifur Rahman, Md. Mejbaul Haque, Ki-Doo Kim
Year and Publication: International Journal of Electrical and Computer
Engineering (IJECE), December 2017.
Methodology:
They proposed high precision indoor positioning using lightning LEDs.
LEDs from array transmit their 3D coordinate (x, y, and z) information
At receiver side sensor used for receiving the light signal and each pixel can act
as an individual photosensor and multiple signals calculated and an unknown 3D
coordinate of the point is estimated
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10. Literature Survey(3/8)
Fig 3 . Procedure of POSITIONAL
ALGORITHM WITH IMAGE SENSORS [3]
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11. Literature Survey(4/8)
3. Epsilon: A Visible Light Based Positioning System [4]
Author: Liqun Li, Microsoft Research, Beijing; Pan Hu, University of
Massachusetts Amherst; Chunyi Peng
Year and Publication: 11th USENIX Symp. Apr. 2018.
Methodology:
Fig 4. Localization in Elpson
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12. Literature Survey(5/8)
4. TDoA Based Indoor Visible Light Positioning Systems [5]
Author: Qu Wang, Trong-Hop Do, Junho Hwang, Myungsik Yoo
Year and Publication: ICUFN 2018
Fig.5. TDoA Based Positioning
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13. Literature Survey(6/8)
5. Two-Phase Framework for Indoor Positioning Systems Using Visible
Light [6]
Author: Gregary B. Prince and Thomas D. C. Little
Year and Publication: Sensors Article, Published: 12 June 2018 .
Methodology:
They proposed an algorithmic framework for indoor positioning.
These framework works have two phases;
A. Coarse Phase – estimate weighted proximity as less as one beacons within
Mobile Terminals (MTs).
A. Fine phase- where the positioning algorithm performs beacons within MTs
FoV- Triangulation Based Positioning Using AoA and Trilateration Based
Positioning Using ToF or RSS are evaluated.
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14. Literature Survey(7/8)
Fig 6. Coarse Phase
proximity method
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15. Literature Survey(8/8)
Fig 7. Fine phase
trilateration Framework
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16. Parameter Wi-Fi Li-Fi
Spectrum Used RF Visible Light
Standard IEEE 802.11 IEEE 802.15.7
Range Based on Radio
propagation & interference
( < 300 m)
Based on Light
Intensity (< 10m)
Data Transfer Rate* Low(100 Mbps – 1 Gbps) Very High (224 Gbps)
Power Consumption High Low
Cost High Low
Bandwidth Limited Unlimited
16
Table 1: Comparison of Wi-Fi and Li-Fi
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17. COMPARISON ANALYSIS
Features [2] [3] [5] [6] [7] [8]
Transmitter N LED sources Array of 4 LEDs Visible light LED Single LED LED panel
anchor (LED)
luminaries
Receiver
User device with
photodiode (PD)
Image sensors Mobile phone
smartphone with
a light sensor
inexpensive photo
diode
VLC-capable MT
Positioning type 2D 3D 2D 3D 2D 2D
Positioning algorithm
CS-based VLC
positioning
geometric
relations of the
LED image
Distances.
trilateration
algorithm
RSSI
,LIPOS algorithm
TDoA algorithm
Two phase
algorithm (Fine
phase& coarse
phase
Simulation -
Matlab
Simulation
moderate-scale
model-based
Simulations.
Model based
Simulation
Matlab Simulation
Monte Carlo
simulation,
CandLES
simulation
Synchronization needed Y Y Y Y N Y
Accuracy
MPE ∼ 0.4m to ∼
0.27m,
0-0.15m if pixel
size is 36´10-6
m.
~0.4m 1.8m avg 3.59 cm
OOK: 57.5 cm,
2-PPM: 56.5 cm,
and 4-PAM: 56.3
cm
Table 2. Comparison between different literature papers
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18.  Airplanes
 Hospitals
 Petrochemical industry
 Nuclear power plants
 In home and office appliances
 Smart lighting
 Vehicle and traffic lights:
 Underwater
 In health surveillance
Figure 5 :Some of viable applications for LiFi [9]
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19.  Lights cannot be dimmed
 The flickering light is disturbing for human eye
 VLC is unidirectional downlink
 Existing lights have to be replaced
 This is exclusively a LoS (line-of-sight) technology
 Interference from Sunlight
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20. Conclusion
Visible light frequency based Light Fidelity (Li-Fi) provides a better
alternative for traditional technologies for Indoor Positioning System. This
technology is not only widely available but also license free. Thus, this
comparative study provides us better insight on the Li-Fi technology
Li-Fi system provides a better alternative solution to Wi-Fi based
positioning system with accuracy in indoor positioning with low energy
consumption and provide real time location and guide users to their
destination within reasonable distance using Light Fidelity (Li-Fi).
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21. References
[1]V. Varshney, R. K. Goel and M. A. Qadeer, "Indoor positioning system using Wi-Fi &
Bluetooth Low Energy technology," 2016 Thirteenth International Conference on Wireless and
Optical Communications Networks (WOCN), Hyderabad, 2016, pp. 1-6.
[2]K. Gligorić, M. Ajmani, D. Vukobratović and S. Sinanović, "Visible Light Communications-
Based Indoor Positioning via Compressed Sensing," in IEEE Communications Letters, vol. 22, no.
7, pp. 1410-1413, July 2018.
[3] M. S. Rahman, M. M. Haque, and K.-D. Kim. Indoor positioning by led visible light
communication and image sensors. International Journal of Electrical and Computer Engineering
(IJECE), 1(2), 2011.
[4] L. Li P. Hu C. Peng G. Shen F. Zhao "Epsilon: A visible light based positioning system" Proc.
11th USENIX Symp. NSDI pp. 331-343 Apr. 2014 [online] Available:
[5] Q. Wang, H. Luo, A. Men, F. Zhao, X. Gao, J. Wei, Y. Zhang, and Y. Huang, “Light
positioning: A high-accuracy visible light indoor positioning system based on attitude
identification and propagation model,” Int. J. of Distributed Sensor Networks, vol. 14, no. 2, pp.
1–15, Jan. 2018.
[6] D. Trong-Hop H. Junho Y. Myungsik "TDoA based indoor visible light positioning systems"
2013 Fifth Int. Conf. on Ubiquitous and Future Networks (ICUFN) pp. 456-458 2013. [8] G.
Prince and T. Little, “Two-Phase Framework for Indoor Positioning Systems Using Visible
Light,” Sensors, vol. 18, no. 6, p. 1917, 2018.
[7] L. I. Albraheem, L. H. Alhudaithy, A. A. Aljaser, M. R. Aldhafian and G. M. Bahliwah,
"Toward Designing a Li-Fi-Based Hierarchical IoT Architecture," in IEEE Access, vol. 6, pp.
40811-40825,2018.
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