Coherent Detection for Optical Coherent Detection for Optical Communications using Digital Signal Communications using Digital Signal
ProcessingProcessing
Michael G. Taylor
Optical Networks Group, University College London
and
Atlantic Sciences
e-mail: [email protected]
Atlantic Sciences
2
OutlineOutline
Why use coherent detection? Why is coherent detection feasible now? – arrival of real-time DSP Burst mode coherent detection experiments Constraints imposed by parallel digital processing – phase estimation Future developments & summary
3
Benefits of coherent detectionBenefits of coherent detection
Optical gain Only light in close neigbourhood of local oscillator wavelength is seen by coherent
detection acts like an ultra-narrow WDM filter behaves as a tunable filter if tunable LO is used
Phase encoded modulation formats can be detected e.g. binary (BPSK) & quadrature (QPSK) modulation formats have 3dB better
sensitivity than on-off formats QPSK carries 2 bits/symbol
Equalisation of propagation impairments in electrical domain is equivalent to electric field equalisation compensate for chromatic dispersion in IF using microstrip line
4
Difficulties with coherent detectionDifficulties with coherent detection
More complex receiver To get best sensitivity and detect high bit rate signals homodyne detection must
be used LO phase locked to incoming signal
Polarisation management needed to match SOP of LO to incoming signal active polarisation control or polarisation diversity or polarisation switching
To achieve best sensitivity synchronous detection needed electronics to lock to wandering phase
5
Sampled coherent detectionSampled coherent detection Apply real time digital signal processing technology to coherent detection
already used in receivers for impairment compensation after direct detection "Hard" part of coherent detection will be done by a digital processor
polarisation management phase estimation equalisation of propagation impairments
Very flexible solution, since DSP can be reconfigured under software control inadequacies of transmitter/receiver hardware can be compensated in DSP
All benefits of coherent detection available simultaneously detects phase- & polarisation-encoded formats allows many bits/symbol best possible receiver sensitivity ultra-narrow WDM etc.
Transceiver can re-use transmit laser as local oscillator in receiver
6
Quadrature samplingQuadrature sampling
Phase diverse apparatus used to combine signal & LO DSP unit processes a digitised representation of detected signals in two arms Polarisation tracking done by two 90° hybrids in polarisation diverse topology
Local oscillator can be nominally same frequency as signal but not phase locked to it
incoming signal
localoscillator
extra phaseshift by 90°
photo-detector
A/Dconverter
DSP
90° hybrid - passive unit
sin(LOt)
cos(LOt)
tPitP
tPitPet
yy
xxti
21
21E
Coherent detection experimentsCoherent detection experiments
8
Proof of principle experimentProof of principle experiment
Continuous sample 4s long recorded on scope, then processed later offline by PC BPSK modulation format Polarisation of LO matched only approximately to signal by manipulation of fiber coils 90° phase shift achieved by coincidental difference in length between arms
multiple samples recorded and then best result chosen
variable attenuator
photo-detector
arrangement of fiber pigtailed passive
splitters
tunable laser
tunable laser
phase modulator
pattern generator10.7 Gb/s
real time sampling
scope20 GSa/sEDFA
noise loading apparatus
1nm filter
9
How data from experiment is processedHow data from experiment is processed
Two waveforms downloaded from oscilloscope.
Equalisation filter applied to each channel - reverses non-flat frequency response of electronics. Same filter applied to all data sets.
Clock frequency (10.66GHz) & beat envelope (about 100MHz) recovered.
Channels retimed to sample rate of 2 x clock frequency (alternate samples at bit centre).
For measurements over fiber, CD equalisation is applied.
Q factor calculated using decision threshold method (based on samples at bit centres).
Two channels combined to give complex electric field.
Smooth waveform by interpolating points in between half bit times, and hence generate eye diagram.
10
Experiment resultsExperiment results
Example of measured data: OSNR = 31dB data point
waveforms at two outputs of 90° hybrid eye diagram
11
4
6
8
10
12
14
5 10 15 20 25 30
OSNR in 0.1nm (dB)
Q
Experiment resultsExperiment results
Each measured data point comes from a 4s sample Q calculated by decision threshold method
Typical IM-DD result from Taylor et al., ECOC 2002 Theoretical sensitivity from Yamamoto, J. Quantum Electron.,
QE-16, p. 1251, 1980
theoretical limit
typical 10G IM-DD transmitter-receiver
2.5dB 4.5dB
12
Experiment resultsExperiment results
Equalisation done by convolution with 9 element vector (FIR filter – fractional spacing) vector determined by simple adaptive process to give best Q
without equalisation with equalisation
Q = 8.3 Q = 12.7
13
Why 2.5dB penalty?Why 2.5dB penalty?
Early experiment showed sensitivity 2.5dB from theoretical minimum Penalty contributions are
single element phase modulator was used instead of MZ modulator driven through 2V – some wasted energy in quadrature component
SOP of LO did not exactly match signal shape of transmit pulses not adjusted for zero intersymbol interference
Receiver noise did not contribute to 2.5dB penalty By fixing contributors above it should be possible to demonstrate near
theoretical sensitivity using sampled coherent detection with or without propagation impairments
Combined with appropriate FEC, Shannon limits should be achievable
14
4
6
8
10
12
14
5 10 15 20 25 30
OSNR in 0.1nm (dB)
QExperiment results: CD equalisationExperiment results: CD equalisation
Chromatic dispersion compensation applied by simple convolution with vector (FIR filter) vector is impulse response of CD transfer function for 89km NDSF, truncated to 7
elements
Penalty from chromatic dispersion is reduced to zero
back-to-back
89km NDSF
89km NDSFwith CD equalisation
-0.3 -0.2 -0.1 0 0.1 0.2 0.3
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
time (ns)
realimaginary
FIR filter
15
Experiment results: CD equalisationExperiment results: CD equalisation
0.96 0.98 1 1.02 1.04 1.06 1.08 1.1 1.12-3
-2
-1
0
1
2
3
time (ns)
0.96 0.98 1 1.02 1.04 1.06 1.08 1.1 1.12-3
-2
-1
0
1
2
3
time (ns)
-3 -2 -1 0 1 2 3-3
-2
-1
0
1
2
3
-3 -2 -1 0 1 2 3-3
-2
-1
0
1
2
3
89km NDSFwithout CDequalisation
OSNR = 27dBQ = 5.3
89km NDSFwith CD
equalisationOSNR = 27dBQ = 12.3
16
2500km PM-QPSK transmission experiment2500km PM-QPSK transmission experiment
4x10.7Gb/s polarisation multiplexed QPSK signal transmitted over 2480km NDSF Polarisation diverse (and phase diverse) coherent receiver Polarisation demultiplexing performed in digital domain, as well as phase estimation &
impairment compensation
NRZ-DQPSK Tx
PC
10Gb/s PPG PRBS length=29-1
10/9080km SMF
PC
delay~10ns TX AOM
LOOP AOM
DA
TA
______ Delayed DATA
PBS
PIN
PIN
PIN
PIN
PBS
PC
PC
Tek
ron
ix T
DS
6154
C
LO
20Gb/s QPSK
40Gb/s PMQPSK
50GHz AWG
1554.94 nmΔλ=2MHz
1554.94 nmΔλ=100kHz
DSP(applied offline)
x
y
Launch power=-5dBm
17
2500km PM-QPSK transmission experiment2500km PM-QPSK transmission experiment
PMD compensation performed using four adaptive FIR filters cross terms interact between polarisations tap coefficients updated using stochastic gradient constant modulus algorithm – no
training sequence Bit error rate after 2480km = 9.5x10-4 (average), 1.6x10-3 (worst quadrature)
1.5dB penalty compared to back-to-back
y
hxx
hxy
hyx
hyy
+
+
Carrier recovery
Frequency offset
Decision circuitry
Ch1
Ch2
Ch3
Ch4
CD comp
CD comp
x
Carrier recovery
Frequency offset
Decision circuitry
128 tap FIR 13 tap FIR
18
Other published results using sampled coherent Other published results using sampled coherent detectiondetection
2.5b/s/Hz spectral density demonstrated bu U. Tokyo group (Tsukamoto et al., paper PD29, OFC 2005) 10Gbaud QPSK, two polarisations muxed, 16GHz spaced record information spectral density
19
Other published results using sampled coherent Other published results using sampled coherent detectiondetection
Real time (not burst mode) coherent receiver demonstrated by U. Paderborn (Pfau et al., paper CThC5, COTA 2006) 400Mbaud QPSK 1MHz wide DFB lasers for transmitter & LO
2.2Gbaud QPSK real time receiver built by Alcatel Lucent using Atmel A/D converters, Xilinx FPGA (Leven et al., paper OThK4, OFC 2007)
20
Other published results using sampled coherent Other published results using sampled coherent detectiondetection
CoreOptics/Siemens/Eindhoven U. systems experiment (Fludger et al., OFC 2007, paper PDP22) 10 WDM channels x 111Gb/s (28Gbaud), 50GHz spaced, over 2375km NDSF
Alcatel-Lucent systems experiment (Charlet et al., OFC 2007, paper PDP17) 40 WDM channels x 40Gb/s (10Gbaud) PM-QPSK, 100GHz spaced, over
4080km post-detection compensation for 100ps mean PMD
Nortel systems experiment (Laperle et al., OFC 2007, paper PDP16) 40 WDM channels x 40Gb/s (10Gbaud) PM-QPSK, 50GHz spaced, over
3200km NDSF without inline DCF post-detection compensation of chromatic dispersion & 33ps mean PMD
How parallel computation architecture How parallel computation architecture impacts DSP – phase estimationimpacts DSP – phase estimation
22
Parallel DSP architecturesParallel DSP architectures
The DSP must operate in parallel because maximum clock speed < symbol rate parallel operation is eqiuvalent to a delay in computing a result result n-1 is not available to compute result n algorithms employing feedback are compromised
Phase estimation algorithms typically use feedback resolution is to reduce phase noise by employing low linewidth lasers DFB lasers and miniature external cavity lasers may have too large
linewidth to use for sampled coherent detection
s
Ls
long delay
23
Open loop Wiener phase estimateOpen loop Wiener phase estimate
Neglecting high order noise terms, applying small angle approximation
= 2 + (additive noise component)
Estimation theory says that best linear estimate of is Wiener filter applied to
arg( )
÷2( )2
Wiener filter
complex signal
phase estimate
exp( )
Gaussian noisequantity we want
Gaussian random walk
d ei + p ei2 + p`
quantity observed
24
Wiener filter responsesWiener filter responses
Finite lag Wiener filter is best, because it sees D symbols ahead in time as well as the past
zz
z
z
D
k
kkDD
11
1
11ˆ
Zero lag Wiener filter Finite lag Wiener filter
zz
z
11
1ˆ
2
2222
2
42
p
pwwpw
25
Look-ahead computationLook-ahead computation
But the Wiener filters involve feedback to immediately preceding result – not allowed! Either Wiener filter can be written as
To resolve, apply look-ahead computation so these relationships refer to a distant past result, L symbols ago multiply numerator and denominator by polynomial
now uses feedback to L symbols ago, at expense of more feedforward taps
11 z
LL
L
k
kk
L
k
kk
L
k
kk
z
z
z
z
z
11
1
01
0
1
01
L symbols past
feedback from previous result
26
ExperimentExperiment
DFB lasers used for signal and LO laser combined linewidth = 48MHz
Low symbol rate 1.5Gbaud s = 0.032
Long measurement burst 1ms duration, contains 1.5x106 symbols statistically significant number of bit errors & cycle slips seen
Optical SNR = -5dB, in 0.5nm resolution bandwidth
variable attenuator
photo-detectors
polarisation controllers
DFB
MZ modulator (biased at
null)
pattern generator1.5 Gb/s
real time sampling
scope
EDFAs
1.2nm filter
var. atten.
ASE source
LO DFB
OSA
polarisation beamsplitter
phase diverse hybrid
27
Results of experimentResults of experiment
Look-ahead computation tested by comparing L = 1 case with L = 32 case found to give identical results
Q-factor of 8.6dB obtained Example of estimated phase vs. time
uses Wiener filter with D = 10
-10
-5
0
5
10
15
20
0 200 400 600 800 1000
time (ns)
unw
rapp
ed p
hase
(ra
d)
Future possibilities for coherent detectionFuture possibilities for coherent detection
29
Coherent optical add/dropCoherent optical add/drop
Inserted signal interferes with input signal to produce desired output signal Modulation on inserted signal must take into account optical phase and SOP of
input signal Can be applied as optical add/drop function, regenerator function
enables add/drop to be implemented with minimal channel spacing
LO in
Ein(t)
from DSP
to DSP laser
Eout(t)- Ein(t)
Eout(t)
modulation subsystem
input monitor
30
Downconversion by analog multiplicationDownconversion by analog multiplication
Symbol rate for digital downconversion operation limited by availability of wideband A/D converters, DSP fabric
Analog multiply can use similar technology to tap weight in tapped delay line Weight input of multiplier must have bandwidth = maximum offset frequency, e.g.
1GHz Symbol rate of e.g. 40Gbaud possible using today’s technology
good solution for 100 GigE
optical signal
local oscillator
sin(t) cos(t)phase estimate DSP
I data out
Q data out
phase diverse hybrid
photodetectorsmultipliers sums
31
ConclusionsConclusions
Coherent detection is the best mode of detection of optical signals offers best receiver sensitivity ultra-narrow WDM compensation of propagation impairments without residual penalty
Introduction of real time DSP can overcome cost issues Sensitivity 2.5dB from theoretical limit demonstrated at 10Gb/s Compensation of chromatic dispersion, PMD over 2500km NDSF demonstrated Phase estimate can be made in a parallel digital processor with wide linewidth
lasers synchronous phase estimation has been performed for an optical signal having
s = 0.032
Additional slidesAdditional slides
33
Phase estimationPhase estimation
Phase is estimated and applied to signal before making 1/0 decision Smoothing function is needed to reduce effect of additive noise and pass actual phase change Errors in the phase estimate lead to
increase in number of bit errors cycle slip errors, i.e. data inversion in case of BPSK
no noise phase noise only phase & amplitude noise
?
34
Optimal phase estimateOptimal phase estimate
Approach to phase estimation problem try to calculate optimal phase estimate try to implement optimal estimate on a parallel digital processor
Best possible estimate of phase is maximum a posteriori (MAP) estimate joint estimate of phase (n) and data d(n) that maximises
r(n) – complex signal
p2 – normalised variance of amplitude noise
MAP estimate was calculated by applying a per survivor method to a group of symbols, and calculating phase by successive Newton's approximation for each symbol group instance
2
2
2 2
1
2 wn p
ni nnendnr
35
Phase unwrappingPhase unwrapping Wiener filter must operate on unwrapped phase, so argument function must include phase unwrapping
(n) = arg(s(n)) + g(n)
g(n) = g(n-1) + 2 f( arg(s(n)) - arg(s(n-1)) )
where f(x) = 1 if x < f(x) = 0 if |x| < f(x) = -1 if x > -
g(n) keeps count of phase cycles However g(n) depends on g(n-1) in expression above – not allowed! Phase unwrapping function can also be recast using look-ahead computation to depend on result L symbols
ago
more computations needed than original version sum function can be calculated in log2(L) steps, so can always be calculated by processor of sufficient
parallelism
1
0
1argarg2L
k
knsknsfLngng
36
Phase estimation methods comparisonPhase estimation methods comparison
1dB penalty point at s = 0.014 1dB penalty point at s = 0.0016
0
1
2
3
4
0 0.001 0.002 0.003 0.004(symbol time).(linewidth)
pe
na
lty (
dB
)
0
1
2
3
4
0 0.01 0.02 0.03(symbol time).(linewidth)
pe
na
lty (
dB
)
PLL (with instant feedback) Wiener filtering, D = 20 Wiener filtering, D = 0
MAP phase estimate differential field detection
BPSK QPSK
