DH-PIM Employing LMSE Equalisation For Indoor Optical Wireless Communications
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Transcript of DH-PIM Employing LMSE Equalisation For Indoor Optical Wireless Communications
Prof. Z. Ghassemlooy ICEE 2006, Iran
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DH-PIM Employing LMSE Equalisation For Indoor Optical
Wireless Communications
Z. Ghassemlooy, W. O. Popoola, and N. M. Aldibbiat
Optical Communications Research Group, School of Engineering and Technology,
The University of Northumbria, Newcastle, U.K.
Web site: http://soe.unn.ac.uk/ocr
Prof. Z. Ghassemlooy ICEE 2006, Iran
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Contents
Overview of Optical Wireless Communications (OWC)
Modulation Techniques
ISI and Equalisation
Simulation Results
Concluding Remarks
Prof. Z. Ghassemlooy ICEE 2006, Iran
3Optical Wireless –What Does It Offer ?
High data rate (in particular line of sight)
Immunity to electromagnetic interference
Abundant unregulated bandwidth
High security compared with RF
Absence of multipath fading (due to the use of IM/DD)
Complementary to RF Etc.
Prof. Z. Ghassemlooy ICEE 2006, Iran
4OWC Links – Types
Diffuse Uses single or multiple source and detector
- No requirement for alignment between them Robust to blocking and shadowing Allows roaming Multiple paths (reflections)
- Result in inter-symbol interference (ISI). Limited bandwidth
- Due to large capacitance of the large area detectors
Line of sight Uses single or multiple source and detector
- Requires alignment between them High bandwidth and no multipath induced ISI Allows roaming Suffers from blocking and shadowing
Prof. Z. Ghassemlooy ICEE 2006, Iran
5Diffuse Systems – How to Combat Noise and Dispersion
Noise Filtering: Optical or electrical
Match Filtering: Maximises SNR, the optimum detection method in the presence
of noise. (Time reversed copy of received pulse convolved with received data stream)
Coding: Block codes, convolution codes (MLSD), turbo codes. Increase
performance by adding redundant data!
Equalisation: Channel distortion compensating filters: - Zero Forcing Equaliser (ZFE)- Minimum Mean Square Equaliser (MMSE)- Decision Feedback Equaliser (DFE)
Prof. Z. Ghassemlooy ICEE 2006, Iran
6Modulation Tree
DifPAM
Pulse Modulation
Analogue Digital
Pulse Time Pulse Shape Pulse Time
Isochronous Anisochronous Isochronous Anisochronous
PSMPAM
PIMPIWMPFMSWFM
PWMPPM
DPPMMPPMDPWMPCM
DPIMDPIWMdifPPMDH-PIM
RZRBAMIManchester
NRZNRZ(L)NRZ(I)Miller code
Prof. Z. Ghassemlooy ICEE 2006, Iran
7Digital PTM Schemes
Symbol1
Symbol2
Symbol3
OOK
PPM
PIM
DH-PIM
Time
bT
sT2sT
A
0 0 0 0 0111 1 11 1
H2H1
Redundantspace
M = 4 bits
L = 24=16 slots
( = 2)
Info.
L1Info.
Info.
(2) (10) (15)
OOK Simple to implement High average power requirement Suitable for Bit Rate greater tha 30Mb/s Performance detoreaites at higher bit ratesPPM Complex to implement Lower average power requirement Higher transmission bandwidth Requires symbol and slot synchronisationDPIM Higher average power requirement compared with PPM Higher throughput Built in symbol synchronisation Performance midway between PPM and OOKDH-PIM The highest symbol throughput Lower transmission bandwidth than PPM and DPIM Built in symbol synchronisation Higher average power requirement compared with PPM and DPIM
Digital PTM Schemes
DH-PIM- Frame Structure
0
Nawras,2005
Prof. Z. Ghassemlooy ICEE 2006, Iran
10DH-PIM – Characteristics
3 4 5 6 7 80
4
8
12
16
20
24
28
32
M [bit]
Nor
mal
ised
ban
dwid
th re
quire
men
ts
DH-PIM1 DH-PIM2
DH-PIM3
DPIM
PPM
Prof. Z. Ghassemlooy ICEE 2006, Iran
11DH-PIM – Characteristics
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-120
-100
-80
-60
-40
-20
0
20
40
Normalised frequency
Pow
er S
pect
rum
Den
sity
(dB
)
Synchronisation
2 3 4 5 6 7 8 9 100.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
M [bit]
Nor
mal
ised
pac
ket t
rans
mis
sion
rate
DH-PIM3
DH-PIM1
DH-PIM2
DPIM
PPM
Higher packet transmissionthroughput
Prof. Z. Ghassemlooy ICEE 2006, Iran
12DH-PIM System
DH-PIMencoder
Transmitterfilterp(t)
Multipathchannel
h(t)
n(t)
n-slotDH-PIMsequence
Unit energyfilter r(t)
(matched top(t))
R3
4 aveavePL
Equaliser
Compute Ps in(n-1)th slot
Optimumthresholddetector
Prof. Z. Ghassemlooy ICEE 2006, Iran
13OWC - Channel
Channel(ceiling bounce
Model)t -2T –T 0 T 2T 3T 4T 5T 6T 7T 8T
y(t)ISI constituent
Developed by Carruthers and Kahn - Channel impulse response is fixed for a given position of Tx, Rx and intervening reflectors
rmsDa
tuat
aHath
1311
7
6
12
)(6)0(),(
nsDrms 151 rmsD RMS delay spread
H(0) = path lossa = 2H/c, H = height of ceiling above Tx and Rx, c is the speed of lightu(t) = unit step function
Prof. Z. Ghassemlooy ICEE 2006, Iran
14OWC –Equalisation
Linear Lattice Transversal
- Zero Forcing - LMS- Fast RLS- Square-root RLS
Non-Linear DFE ML Symbol detector MLS
Linear Equaliser: Traversal filter structure that has a computational complexity which is a linear function of the channel dispersion length.
Prof. Z. Ghassemlooy ICEE 2006, Iran
15OWC - Equalisation – contd.
Tx Filter Multipathchannel Rx Filter Equaliser
Cj
yk
Equaliser output (estimate)
Noise nk
Ik kI
Discrete equivalent of the convolution of the Tx filter, channel and Rx filter with the information sequence Ik
....3,2,1,00
knfIIy k
knn
nknkk
ISI Noise
k
kjjkjk ycI
Where {cj} are the 2K +1 complex-valued tap weight/coefficients of the filter.
Prof. Z. Ghassemlooy ICEE 2006, Iran
16Linear Zero ForcingEqualiser
- With a frequency response = h(t)-1. - Able to reduce ISI term at sampling points
kn jjkjnknkk ncqIIqI 0
ˆ {qn} is simply the convolution of {cn} and {fn}.
Signal ISI Noise
Equaliser with infinite number of taps, tap weights could be selected such that the ISI component is reduced to zero.For practical case: j = k
elsewhere
nfcq
jjnjn 0
01
Simple to implement, but not effective with noise.Compensate for the channel distortion at the expense of noise due a
large gain in the frequency range where attenuation is high
Prof. Z. Ghassemlooy ICEE 2006, Iran
17Least Mean Square Error Equaliser
Relaxing the zero ISI by selecting Cj such that the combined power of the residual ISI and additive noise at the equaliser output is minimised . I.e. minimising the mean error square:
kk II ˆ
The MSE for the equaliser2K+1 taps is
22ˆ)(
k
kjjkjkkk ycIEIIEkJ
The LMSE solution is obtained by dJ(k)/d{cj}.
KkkRkjRc iy
k
kjyj
3,2,1,0),()(
Autocorrelation matrix cross-correlation vector IyR
yyRT
iy
Ty
.
.
yT is the transpose of matrix yk-j and I represents the training signal.
Prof. Z. Ghassemlooy ICEE 2006, Iran
18LMSEE – contd.
In contrast to zero-forcing equaliser, the LMSEs solution depend on the statistical properties of the noise as well as the channel induced ISI
Autocorrelation matrix cross-correlation vector IyR
yyRT
iy
Ty
.
.
yT is the transpose of matrix yk-j and I represents the training signal.
Where
Prof. Z. Ghassemlooy ICEE 2006, Iran
19Simulation Process
EnterRb and Drms
1<Drms<15ns
Last ?
Stop
Out=Cm*hk*I + No
Enter No_symbGen L-DH-PIM
EvaluateCm, hk; No
Error = Error + 1 Error = Error Outk = Ik?
Last slot ?
Last Drms ?
SER = Error No of slots
Yes
YesNo
No No
No
Yes
Yes
Gen. Rand. {OOK} Start
Enter; SNR
-70<<-30 dBm
Prof. Z. Ghassemlooy ICEE 2006, Iran
20Simulation Parameters
P P Parameter ValueAverage optical power -70 (dBm) ≤ ≤-30 (dBm)Photodetector responsivity R 1Threshold factor 0.5Normalised delay spread DT 0.001 to 1.5
Bit rate Rb 1, 10, 50, 100, &150 Mbps
Alpha α 1 and 2Number of OOK bits/symbol M 3 and 4Background light current Ib 200 µA
Number of equaliser filter taps 3No of OOK symbols 300,000
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Unequalised Equalised
Results –Eye Diagrams
-0.4 -0.2 0 0.2 0.4
0
2
4
6
8
10
12
14
16
18
x 10-20
Time
Am
plitu
de
-0.4 -0.2 0 0.2 0.4
-1
0
1
2
3
4
5
6
7x 10
-20
Time
Am
plitu
de
8-DH-PIM2 at Rb = 100 Mbps, Drms = 15 ns and
P
= -30 dBm.
Prof. Z. Ghassemlooy ICEE 2006, Iran
22Results –Slot Error Rate vs SNR
-20 -15 -10 -5 0 5 10
10-5
10-4
10-3
10-2
10-1
Electrica l SNR (dB)
Prob
abili
ty o
f slo
t err
or (S
ER)
8-DH-PIM2, Drms =10ns
Rb=1MbpsRb=10MbpsRb=50MbpsRb=100MbpsRb=1MbpsRb=10MbpsRb=50MbpsRb=100Mbps
Unequalised
Equalised
10-4
Significant improvement -37.5 and -35.5 dBm
of average optical power
@ SER of10-4
Prof. Z. Ghassemlooy ICEE 2006, Iran
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-46 -44 -42 -40 -38 -36 -3410
-4
10-3
10-2
10-1
Average optical power requirement (dBm)
Pro
babi
lity
of s
lot e
rror
(SE
R)
8-DH-PIM2 Rb=100Mbps; 3-Tap LMSE
Drms=2nsDrms=4nsDrms=6nsDrms=10nsDrms=2nsDrms=4nsDrms=6nsDrms=10ns
Unequalised
Equalised
Results – Slot Error Rate vs Avg. Optical Power
Prof. Z. Ghassemlooy ICEE 2006, Iran
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-15 -10 -5 0 5 10 15
10-6
10-5
10-4
10-3
10-2
10-1
Electrical SNR (dB)
Prob
abili
ty o
f Slo
t err
or (S
ER)
Rb=100Mbps; 3-tap L-ZFE; DT=1
8-DH-PIM28-DH-PIM18-DPIMOOK8-PPM
Results –Slot Error Rate vs SNR
Prof. Z. Ghassemlooy ICEE 2006, Iran
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10-2
10-1
100
0
0.2
0.4
0.6
0.8
1
1.2
Normalised Delay Spread DT
Pow
er p
enal
ty to
ach
ieve
SER
=10
-3 (d
B)Power penalty to achieve SER= 10-3 ;Rb=100Mbps; 3-tap L-ZFE
8-DH-PIM2OOK8-DPIM8-DH-PIM18-PPM
DT = DrmsRb
Results –Power Penalty vs DT
Prof. Z. Ghassemlooy ICEE 2006, Iran
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10-2
10-1
100
0
0.2
0.4
0.6
0.8
1
1.2
Normalised delay spread DT
Pow
er p
enal
ty to
ach
ieve
SE
R=1
0-3
LMSE and L-ZFE equalisers Rb=100Mbps
10-2
10-1
100
0
0.2
0.4
0.6
0.8
1
1.2
Normalised delay spread DT
LMSE and L-ZFE equalisers Rb=100Mbps
8-DH-PIM2OOK8-DH-PIM1OOK8-DH-PIM28-DH-PIM1
L-ZFE
LMSE
Results –Power Penalty vs DT
similar performance in very dispersive
environment
LMSE is better in less dispersive channels (DT <
0.2). LMSE compensates for
both dispersion and noise (dominant)
DT = DrmsRb
3-taps
Employing equalisation in DH-PIM leads to:- Reduced optical power level requirement at high data rate and highly dispersive channels- Improve error performance in a dispersive channel
LMSE offered similar performance to LZEF, at highly dispersive channel, but better performance in less dispersive channels (line of sight) DH-PIM with equalisation is an attractive modulation scheme for OWC where there is a need for high throughput
Concluding Comments
Prof. Z. Ghassemlooy ICEE 2006, Iran
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Thank you!
Prof. Z. Ghassemlooy ICEE 2006, Iran
29OWC – Issues + Solutions
Shadowing in non-line of sight links - Diversity schemes
Limited power (safety reason) - Power efficient modulation techniques
Noise due to the ambient light sources- Optical/electrical filtering- Modulation scheme with no or very little frequency
components at the low frequency bands Dispersion (due to multipath)
- Equalisation SNR variation with the distance and ambient noise