Nonlinearity Equalization Techniques for DML- Transmission Impairments
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1 Nonlinearity Equalization Techniques for DML- Transmission Impairments Johannes von Hoyningen-Huene Christian-Albrechts-Universität zu Kiel Workshop on Optical Communication Systems October nd,
2 Motivation Future Optical Access Networks need to be cost efficient! Only low-cost optical components DML (direct modulated laser), Direct Detection, no DCF, no external modulators, Thus limited performance at high-speed, longer distance, high customer count, Electronic signal processing (cheap CMOS!) may help to overcome these performance limitations We compensate and equalize for impairments of low-cost optics by sophisticated electronic processing DML nonlinearity and chirp, DD nonlinearity, limited bandwidth, Goal: Squeeze maximum performance (e.g.gbit/s, km) from low cost optical equipment (e.g..5gbit/s DML, DD,..) -- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
3 Outline. Motivation. Nonlinear Distortions in Access 3. Post-Compensation at Receiver Side -3- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
4 Distortions in Access Networks Laser/Modulator Low cost DML Chirp Low bandwidth Fiber Long distance e.g. km Optical Front End Direct Detection ONU downlink Rx OLT uplink downlink Tx uplink Rx AWG AWG AWG AWG :N :N ONU... Tx downlink Rx Question: Can we design Gb/s NGA from.5gb/s optics - - Gb/s - - Gb/s - -, etc? uplink Tx -- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
5 Distortions from DML (Direct Modulated Laser) Rate Equations: Model for DML dn I N() t St () = g ( Nt () Nt ) dt e V τ + ε St () ds dt n St () β ΓNt () S( t) = Γg ( Nt () Nt ) + + ε St () τ τ dφ α = Γg ( N() t Nt ) dt τ p System with memory: IM: FM/PM: limited bandwidth nonlinear chirp n p I modulation current - ma N S carrier density photon density V active volume m 3 g gain.7 - m 3 /s N t β carrier density at transparency fraction of spontanious emmision m Γ mode confinement factor. τ p photon lifetime m 3 τ n electron lifetime s ϕ α optical phase linewidth enhancement factor S(t) N(t) P(t) Δf z ΔΦ P(t) e complex envelope of optical field fiber parameters from fit to sample DML -5- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
6 DML Characterization P opt in mw 3 DC characterisation Bookham LC5W5898BA-C3 Experiment Simulation Comparison: measurement/ simulation RF - characterisation Bias = ma 3 I in ma laser GHz GHz Parameters of rate equations fitted to measurement DML behavior depends strongly on bias current 3 GHz LPF to allow for laser packaging Bias = ma GHz GHz -6- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
7 DML Characterization km km no chirp ( switched off ) km SSMF.. in mw rec P.. in mw rec.5 P. in mw Prec in mw. in mw.... P Prec in mw.5 P 3dBm, Bias,5 ma mapp Prec in mw Gb/s.5 rec Chirp + dispersion destroy the eye! 5 Gb/s Prec in mw 3 rec.5 Gb/s Prec in mw.. J. v. Hoyningen-Huene, Workshop Berlin,tOktober in ns nd, -7-
8 Impairments from DML, Fibre & Direct Detection Laser/Modulator DML with nonlinear intensity modulation Chirp Limited bandwidth Fibre (SSMF) with loss and dispersion (Kerr-Nonlinearity neglected here) Different Impairments in Access and Long-haul! Direct Detection at Receiver Loss of phase by operation Nonlinear transducer from opt. to electr. Limited bandwidth -8- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
9 Equalizer Types for Linear Distortions Feed-Forward-Equalizer (FFE) T b T b T b T b e e e e 3 e + N y ( t) = eyt ( nt ) FFE n= n Decision-Feedback-Equalizer (DFE) - + A ^ Goal: Recover symbols (maximize eye opening) b b 3 b b T b T b T b T b DFE A A n n= ( ) ) b y ( k T ) = yk ( T ) bdˆ ( k n T N -9- A J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
10 Equalizers for Nonlinear Distortions yt () f A y ( i T A ) y ([ i- ] T A ) T A () () e e e e + e FFE, linear + quadratisch Nonlinear FFE w y e ( k T S ) + - DFE, lin. + quad. y q ( k T S ) y b ( k T S ) T S T S dk () b b b FFE (linear) DFE (linear) + Nonlinear DFE FFE quadratic DFE quadratic -- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
11 Equalizer Types Maximum-Likelihood-Sequence-Estimator (MLSE) L L = yk ( ) gk ( ) d ( k) = min d µ µ µ k = Select data sequence d µ of limited length, whose channel response most fits to received signal. Efficient implementation with Viterbi Algorithm S ={,} S ={,} S ={,} S ={,} 3 Goal: Recover data sequence -- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
12 Estimation of Equalizer Coefficients Training sequence, which is known to the receiver FFE-DFE: Estimation with Minimum-Mean-Square Error MLSE: Retrieve mean PDF for different trellis branches Adaptive blind optimization of coefficients possible. No return pass required for coefficients estimation Equalizer design parameters Equalizer processing speed (in terms of samples per data bit) Equalizer memory (in terms of number of coefficients or trellis depth) -- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
13 Experimental Setup: Receiver Side Equalization bit pattern generator 5 Gb/s, PRBS - laser controller bias: 6-3 ma DML.5 Gb/s km 5 km PD realtime oscilloscope 5 GS/s synchronization resampling Simple transmitter: bit pattern generator+dml no knowledge about channel required no DSP required Complex receiver: ADC required DSP for clock recovery, channel estimation and EQ FFE-DFE MLSE BERT offline DSP -3- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
14 Linear vs. Nonlinear: FFE/DFE log (BER) Sample/Bit Sample/Bit FFE/DFE-Memory FFE/DFE lin/lin nlin/lin lin/nlin nlin/nlin log (BER) FFE/DFE-Memory FFE/DFE lin/lin nlin/lin lin/nlin nlin/nlin Great advantage with nonlinear FFE Minor advantage with nonlinear DFE reason: reduced value set after slicer in DFE FFE/DFE nlin/lin = best option Experimental: +5 km, Bias=3 ma, -- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
15 Performance depend. on EQ-Length & DML Power -3 sample/bit samples/bit -3 log (BER) dbm - dbm - dbm FFE/DFE-Memory -3 FFE/DFE nlin / lin log (BER) dbm - dbm - dbm FFE/DFE-Memory -3 log (BER) dbm - dbm - dbm MLSE-Memory MLSE -5- log (BER) Experimental: Gb/s, +5 km, Bias=3 ma dbm - dbm - dbm MLSE-Memory J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
16 Measured Signal after lin. and nonlin. EQ, BB linear FFE linear DFE w/o EQ FFE6-DFE6 FFE-DFE bias = 3 ma, opt. launch power: 5.5 dbm, Gb/s sample/bit nonlin. FFE linear DFE BB: no advantage with nonlin. EQ -6- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
17 Measured Signal after lin. and nonlin. EQ, 5km SSMF linear FFE linear DFE -.. w/o EQ FFE6-DFE6 FFE-DFE bias = 3 ma, opt. launch power: 5.5 dbm, Gb/s sample/bit nonlin. FFE linear DFE Dispersive channel: great benefit with nonlin. EQ We compensate for nonlinearities: chirp and DD envelope detection! -7- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
18 Acknowledgement This work was supported by ADVA & German Ministry of Education and Research (BMBF) -8- J. v. Hoyningen-Huene, Workshop Berlin, Oktober nd,
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