mic-cpe2010, jordan optimizing the performance of digital pulse interval modulation with guard slots...
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MIC-CPE2010, Jordan
Optimizing the Performance of Digital Pulse Interval Modulation with Guard Slots for
Diffuse Indoor Optical Wireless Links
Z. Ghassemlooy and S RajbhandariOptical Communication Research Group,
School of CEIS, Northumbria University, Newcastle upon Tyne, UKhttp://soe.unn.ac.uk/ocr/
MIC-CPE2010, Jordan
Outline
Indoor optical wireless communication Modulation techniques DPIM Techniques to reduce ISI Decoding Scheme for DPIM(nGS) Scheme
Threshold decoding Hybrid decoding scheme Maximizing the likelihood (ML) of a pulse
Results and discussions Conclusions
MIC-CPE2010, Jordan
Optical Wireless System: Overview
1 M. Kavehrad, Scientific American Magazine, July 2007, pp. 82-87.
Typical optical wireless system components
Optical wireless connectivity 1
Uses light beams (visible and infrared) propagating through the atmosphere or space to carry information.
Optical transmitter- Light emitting diodes- Laser diodes
Optical receiver- p-i-n photodiodes- Avalanche photodiodes
Links- Line-of-sight (LOS)- Non-LOS- Hybrid
MIC-CPE2010, Jordan
Digital Modulation Schemes
On-off keying (OOK)
Pulse position modulation (PPM)
Digital pulse interval modulation (DPIM)
Dual-header pulse interval modulation (DH-PIM)
Subcarrier modulation
MIC-CPE2010, Jordan
Digital Pulse Modulation Schemes
DPIM
MIC-CPE2010, Jordan
The DPIM Scheme
An anisochronous modulation technique A symbol is composed of a pulse of one slot duration followed
by a series of empty slots:
where dj-1 is j empty slot(s), j = 0, ..., D and D is the decimal value of ai.
DPIM signal is defined as:
p(t) - rectangular pulse shape, Ts - slot duration
bi - set of random variables representing a pulse/no pulse in the nth Ts
𝑺ij=1 {𝒅 j −1 }
s (t )= ∑i=−∞
∞
bi p ( t −i T s )
MIC-CPE2010, Jordan
Why DPIM ?
An excellent compromise between the bandwidth and the power efficiencies.
Higher bandwidth efficiency than PPM.
Higher power efficiency than OOK.
Easy to implement compared to more complex modulation scheme like DH-PIM.
2 3 4 5 6 7 80
5
10
15
20
25
30
Bit resolution
Nor
mal
ized
ban
dwid
th r
equi
rem
ent
PPM
DH-PIM1
DPIM
DH-PIM2
OOK
2 3 4 5 6 7 8-16
-14
-12
-10
-8
-6
-4
-2
0
Bit Resolution, M
Nor
mal
ized
Pow
er R
equi
rem
ent (
dB)
DH-PIM2
PPM
DH-PIM1
DPIM
MIC-CPE2010, Jordan
Indoor Optical Wireless Links
The key issues:
- Eye safety- shift from 900 nm to 1550 nm - eye retina is less
sensitive to optical radiation- power efficient modulation techniques
- Mobility and blocking- is a problem in diffuse configurations (i.e. Non-
LOS), thus resulting in: - reduced data rates- increased path loss- multipath induced inter-symbol-interference (ISI)
MIC-CPE2010, Jordan
Indoor OWC - Diffuse Links
Pulse spreading due to the different path delays leading to intersymbol interference (ISI)
ISI is the limiting factor in achieving higher data rates
Diffuse links are characterised by RMS delay spread
The impulse response in the Ceiling bounce model is:
LOS
Diffuse
Diffuse shadowed
LOS shadowed
)(1.06
)( 7
6
1.0tu
t
Dth
rms
rms
D
where u(t) is the unit step function
Fig. Impulse response of indoor optical wireless channel
MIC-CPE2010, Jordan
Techniques to Reduce ISI
Maximum likelihood sequence detection The optimum solution to reduce ISI Difficult to implement due to high complexity and large delay Practical implementation is not feasible for DPIM due to variable
symbol length
Equalization Trade-off between complexity and performance Preferred due to lower complexity compared to MLSD Channel estimation is necessary
Guard slots (GSs) Simple to implement without additional complexity Effective in moderately dispersive channel Ineffective in highly dispersive channel
MIC-CPE2010, Jordan
DPIM with Guard Slots to Reduces ISI
The postcursor slot immediately following a pulse is most severely effected due to ISI.
Adding GSs immediately following a pulse can be effective in reducing the ISI.
Clear overlapping in the constellation of DPIM(0GS). Hence difficult to assign a fixed threshold level.
The constellation of 0s and 1s are clearly separated for DPIM(1GS). However, distance is clearly reduced.
0 0.2 0.4 0.6 0.8 1
0 0.2 0.4 0.6 0.8 1
Fig. Scatter plots of received signals at DT = 0.3 for DPIM(0GS). red= 0, blue =1
0 0.2 0.4 0.6 0.8 1
0 0.2 0.4 0.6 0.8 1
Fig. Scatter plots of received signals at DT = 0.3 for DPIM(1GS). red= 0, blue =1
MIC-CPE2010, Jordan
Decoding Scheme for DPIM(nGS) Scheme
DPIMencoder
ai bi ib̂Transmitter filterp(t)
n(t)
v(t)
R
z(t)Decoder
1/Ts-DPIM
y(t) yiMatched filter r(t)
x(t) Multipathchannelh(t)
s(t) φ(t)
avgDPIMPL
Decoding schemes:
Threshold decoding
Hybrid decoding scheme
Maximizing the likelihood (ML) of a pulse
Fig. The block diagram of the DPIM system.
MIC-CPE2010, Jordan
Threshold Decoding
A threshold level set at half the peak amplitude is non-optimum in diffuse channel.
ISI reduces the minimum Euclidean distance dmin.
Threshold level needs to be adjusted accordingly.
The optimum threshold level is given by:
where ci is the channel taps
Error probability can be approximated as :
-8 -6 -4 -2 0 2 4 610
-6
10-5
10-4
10-3
10-2
10-1
100
SNR (dB)S
ER
8-DPIM (D
T = 0.01, simulation)
8-DPIM (DT = 0.01, theory)
8-DPIM (DT = 0.1, simulation)
8-DPIM (DT = 0.1, theory)
16-DPIM (DT = 0.01, simulation)
16-DPIM (DT = 0.01, theory)
16-DPIM (DT = 0.1, simulation)
16-DPIM (DT = 0.1, theory)
The predicted and simulated SER against the SNR for the 8 and 16- DPIM schemes at Dt= 0.01 and 0.1.
𝛼 th=(c− 1+c1 )+dmin
2=c−1+c0+c1
2
P seDPIM ≤Q(√ c0− (c−1+c1 ) E2N 0
)
MIC-CPE2010, Jordan
Hybrid Decoding Scheme
Soft decoding is difficult to implement due to non-uniform symbol length.
Valid DPIM(1GS) symbol always has a 010 sequence except for the all zero sequence.
Unique slot sequence in DPIM(1GS) can be exploit for hybrid decoding.
The decoding algorithm can be summarised as:
Valid DPIM(1GS) sequence
000
0010
010
0100
P ( b̂i=1|bi=1)=P ( y i≥𝛼∨b i=1 ) P ( y i> y i+1 ) P ( y i> y i−1 )
if yi>&yi> (yi-1,yi+1)else
The probability of correctly decoding a pulse is given by:
MIC-CPE2010, Jordan
Maximizing the Likelihood (ML) of a Pulse
In DPIM scheme with n GSs, a pulse should always be followed by n empty slots.
Taking two slots into consideration (00, 01, 10) are the only valid DPIM(1GS) sequence.
The approach taken here is to maximize a-Posterior probability of a pulse.
i.e. If the posterior probability of sequence (10) is greater than posterior probabilities of (00) and (01) sequence, decode the bit sequence as (10) else decode present bit as 0.
if
;else .
MIC-CPE2010, Jordan
Results and Discussions
A fixed threshold level of 0.5 demonstrates the worst performance.
The ML detection scheme offers the best performance.
All other decoding approaches show improved performance compared to the DPIM (0GS).
The optimum threshold decoding offer significantly improved performance compared to a fixed threshold decoding.
10-2
10-1
100
-2
0
2
4
6
DT
NO
PR
NGS
1 GS ( = 0.5)
1GS (opt
)
1GS (Hybrid)
1GS (ML)
Fig. The NOPRs against the normalized delay spreads for 8-DPIM (0 &1GS) for different decoding algorithms and a SER of 10-6.
MIC-CPE2010, Jordan
Results and Discussions
Hybrid decoding offers improved performance compared to the optimum threshold level.
The advantage of the ML detection scheme can be observed at higher values of DT .
A difference of ~ 3.4 dB and ~ 2.8 dB can be observed between the ML detection and the hybrid decoding at DT = 0.4 for 8 and 16-DPIM(1GS), respectively.
10-2
10-1
100
-4
-2
0
2
4
6
DT
NO
PR
NGS
1 GS ( = 0.5)
1GS (opt
)
1GS (Hybrid)
1GS (ML)
Fig. The NOPRs against the normalized delay spreads for 16-DPIM (0 &1GS) for different decoding algorithms and a SER of 10-6.
MIC-CPE2010, Jordan
Conclusion
A number of decoding approaches has been proposed and studied for DPIM(1GS)
The decoding algorithm exploits the unique slot sequence of DPIM(1GS)
The fixed threshold based decoding schemes is the non-optimum for diffuse links.
A hybrid decoding scheme surpasses the performance of the optimum thresholding.
The ML decoding of a pulse offered the best performance.
The system complexity using the ML detection scheme is not significantly higher than that of a threshold detector, ML detection is practically recommendable.
MIC-CPE2010, Jordan
Questions?
Thank you!