![Page 1: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/1.jpg)
An Experimental Receiver DesignFor Diffuse IR Channels Based on
Wavelet Analysis & Artificial Intelligence
R J Dickenson and Z Ghassemlooy
Optical Communication Research GroupSheffield Hallam University
www.shu.ac.uk/ocr
![Page 2: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/2.jpg)
Contents
• Diffuse IR indoor multipath channel• Compensating schemes• Traditional receivers• Wavelet and AI based receiver• Proposed receiver• Simulation results• Conclusions
![Page 3: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/3.jpg)
Diffuse IR System - Major Performance Limiting Factors
Inter Symbol Interference
Noise Power Limitations
Tx Rx
![Page 4: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/4.jpg)
Compensating Methods
Modulation Schemes– DH-PIM – DPIM – PPM
Diversity– Angle – Multi-beam
Tx
Rx Rx Rx
Rx Rx
Rx
![Page 5: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/5.jpg)
Traditional Receiver Concepts
ZFE DFE Coding
- Block- Convolutional- Turbo
10-3
10-2
10-1
100
-10
-8
-6
-4
-2
0
2
4
6
8
10
12
DT
Nor
mal
ised
opt
ical
pow
er re
quire
men
ts (d
B)
OOK-NRZ
32-DH-PIM2
32-DH-PIM1
32-DPIM
32-PPM
Normalised optical power requirements Vs. normalised delay spread for various modulation schemes
![Page 6: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/6.jpg)
Alternative Techniques - Wavelet Analysis & Artificial Intelligence
De-noising Image Compression Earthquake Electrical Fault Detection Mechanical Plant Fault Prediction Apple Ripeness Communications
![Page 7: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/7.jpg)
What Is A Wavelet?
Simple Description:
A finite duration waveform
Has an average value of zero
Is a basis function, just like a sine wave in Fourier analysis
![Page 8: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/8.jpg)
Fourier Analysis And The Wavelet Transform
3 sine waves at different frequencies and times.
Frequency spectrum The peaks will remain statically
located regardless of where in time the frequencies occur
![Page 9: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/9.jpg)
Fourier Analysis And The Wavelet Transform
Wavelet resultsIn the wavelet domain we have both a representation of frequency (scale), and also an indication of where the
frequency occurs in time.
![Page 10: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/10.jpg)
Neural Networks
Loosely based on biological neuron
Neural networks come in many flavours
Used extensively as classifiers
Supervised and unsupervised learning
Input Layer
Hidden Layer 1
Hidden Layer 2
Output
Σ F
x 2
w 1 x 1
x n
w 2
w n
Out
![Page 11: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/11.jpg)
Channel Model & Receiver Structure
• Input data format: OOK NRZ • Channel: Carruthers & Kahn Channel Model, with impulse
response of:
1 0 1 0... …1 0 1 0 Tx CHANNEL
NOISE
Rx Filter WAVELET ANALYSIS
NEURAL NETWORK
Feature Extraction
Pattern Recognition
Thresholder
Receiver
)(6),( 7
6
tuataath
where u(t) is the unit step function
![Page 12: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/12.jpg)
Simulation Flow Chart
Incoming Data n bits long.
Low Pass Filter
Decimate Stream it to 5 Bit windows
CWT at 4 scales on every
window
Decimate each set of
coefficients to 100 sample
points
Pack samples into a 100xn
matrix
Offer each column to the
neuronal classifier
Threshold the output to 1 or 0
• ANN: - 4 layers with 176 neurons - 3 different activation functions, trained to detect the value of the centre bit from a 5 bit length window
• CWT:- 5 bit sliding window - coif1 mother wavelet- Operating scales of 60,
80, 100 and 120 using
Bit To Detect
5 Bit Window
![Page 13: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/13.jpg)
Simulation Results – BER V. SNR
Data rate: 40 and 50 Mb/s Normalised delay spread: 0.44
and 0.55• for BER of 10-5 the wavelet-AI
scheme offers SNR improvement of:- ~ 8 dB at 40 Mbps - ~ 15 dB at 50 Mbps
over the filtered threshold scheme• For the wavelet-AI scheme the
penalty for increasing the data rate by 10 Mbps is ~ 5dB whilst it is around 15dB for the basic scheme.
![Page 14: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/14.jpg)
Conclusions
A novel technique to combat multipath dispersion
Improvement of ~ 8 dB in SNR compared with the threshold based detection scheme
Promising results, however, significant further work is required.
Not intended to replace coding methods
![Page 15: An Experimental Receiver Design For Diffuse IR Channels Based on Wavelet Analysis & Artificial Intelligence](https://reader036.vdocuments.site/reader036/viewer/2022062521/56816851550346895dde5927/html5/thumbnails/15.jpg)
Any Questions?
• Thank you for your kind attention. • I will attempt to answer any questions you
have.