Abasahl, Banafsheh

Bogaerts, Wim

English

Ghent University Academic Bibliography

Evaluation of Stability of Silicon-Photonics-Based Optical Switch NetworkArchitectures against Parasitic Errors in Switch ElementsBanafsheh Abasahl , Wim BogaertsGhent University - Imec, Technologiepark 126, 9052 Ghent, BelgiumCenter of Nano-and Biophotonics, Ghent University, Ghent, Belgium e-mail: banafsheh.abasahl@imec.beABSTRACTThe performance of MEMS-based optical switch networks against losses and parasitic effects in tunableelements for different architectures are simulated. A comparison between those architectures is provided con-sidering the fact that the parasitic effects of MEMS switches are highly depend on their status.Keywords: optical switch networks, MEMS switches, Benesˇ, PILOSS, cross-bar, optical circuit simulation,stochastic analysis, errors.1 INTRODUCTIONOptical switch networks are essential platforms for all-optical communication networks. The power con-sumption and cost of communication networks drop dramatically if low-power and high performance siliconphotonic integrated circuits with tunable components are incorporated in such networks. In order to maintainthe performance of these networks in larger scales, the choice of switch architecture (i.e. the connectivitynetwork inside the switch) is crucial. The performance of these switch networks not only depend on componentslosses, but also on parasitic coupling effects. These effects can give rise to distortion in the output signals, non-uniformity and crosstalk due to multi-path interference. In this work, we provide a comparison between differentarchitectures that can be implemented in a photonic integrated circuit (PIC). Three non-blocking architectures forN×N switch networks, namely cross-bar, path-independent loss (PILOSS) [1] and Benesˇ [2] are implemented.A schematic representation of these networks is shown in Fig. 1. We consider a silicon photonics technologyplatform, but as switching elements we introduce the use of of optical MEMS [3], [4], because these switches,as opposed to optical switches based on electric heating [5], offer almost zero electric power loss at the expenseof low switching speed.2 IMPLEMENTATION OF SWITCH NETWORK ARCHITECTURESThe switch elements in this work are based on MEMS directional couplers (DC) where the spacing betweenthe waveguides can be mechanically adjusted. For these tunable DCs, in the bar state, the two waveguides areFigure 1. Switch network architectures under consideration: (a) Benesˇ, (b) PILOSS, and (c) Cross-bar. (d) two types of switchimplementations for the cross-bar architecture, (e) a schematic representation of a MEMS directional coupler with comb actuation. Althoughthe calculations are performed on 16×16 networks, here for the sake of clarity, 8×8 networks are presented for cross-bar and PILOSSarchitectures.Figure 2. Distribution of the transmission (top) and cross talk (bottom) of 100-cycle Monte Carlo simulations with σcross = 5% for16×16 networks with (a) cross-bar(I), (b) cross-bar (II), (c) PILOSS and (d) Benesˇ architectures.sufficiently far apart that no coupling occurs. On the other hand, the two waveguides are brought close togetherin the cross state and the DC becomes more sensitive to the coupling distance and therefore it introduces highererror levels and wavelength dependence in the coupling.The cross-bar architecture comprises of a matrix of N×N switches. The switches are always in the bar stateexcept for the switches SEmn, where the input mth is to be routed to the output nth. In contrast to the cross-bar architecture where the number of switches (Nswitch) and crossovers (Ncrossover) depend on the requestedmapping, the PILOSS architecture offers a solution where these numbers are always constant. In each routing,only one switch is in the bar state, and the the rest are in cross states, which is not conducive for low lossesand errors. In order to benefit from the performance of the DCs in the bar state, a combination of a DC and across over, like the switch shown for cross-bar type(I), is used. In this case, the 100% transmission correspondto cross state. For each of these two architectures N2 switches are needed, which results in a large footprintand an accumulation of errors and losses.A more compact solution is a routine proposed by Benesˇ where N = 2p inputs-outputs are routed ina layered architecture. In this case, the number of switches per routing decreases dramatically. The physicalproperties of the three architectures as a function of the number of input-outputs (N ) are provided in Table 1.The simulations are performed for N = 16 using the Caphe circuit simulator by Luceda Photonics, extendedwith our own variability analysis routines [6]. In order to study the effect of stochastic imperfections of switches,in a 100-loop Monte-Carlo set of simulations, the coupling values assigned to each DC is randomly deviatedfrom its ideal setting of 0 (bar) or 1 (cross), with a normal probability distribution and a standard deviationof σbar and σcross. In each case, the σcross is considered to be one order of magnitude larger than σbar. Theinsertion loss for the bar and cross states are considered to be 0.3 dB and 0.4 dB, respectively. For the cross-bararchitecture, the performance is evaluated by incorporating two types of switch nodes, shown Fig. 1a: type (I)with a single DC and a crossover, as those considered for the other two architectures, and type (II) built of twoDCs and one crossover suggested in [4]. The resulting distribution for the outputs of 16×16 networks with thethese architectures are shown in Fig. 2a-d for a σcross = 5% and σbar = 0.5%. The simulator evaluates theS-parameter between each input-output pair, from which the transmission and the crosstalk values are inferred.In Table 1, the outcomes of Monte-Carlo simulations, averaged over the 100 cycles and the 16 outputs, arepresented.TABLE 1. COMPARISON BETWEEN PROPERTIES OF THE THREE SWITCH NETWORK ARCHITECTURES. THE VALUES IN RED ARE FOR A16×16 NETWORK. THE AVERAGE VALUES CALCULATED FOR σcross = 5% AND σbar = 0.5% ARE PRESENTED IN BLUE.Cross bar (I) Cross bar (II) PILOSS BenesˇNDC ; Ncrossover N2;N2 2N2;N2 N2;N2 + (N − 1)2 (2× log2N − 1)× N2 ;∑log2 Nm=0 (N22m−N)256; 256 512; 256 256; 225 56; 88Nswitch per path 1 to 2N − 1 1 to 2N − 1 N 2 log2N − 11 to 33 1 to 33 16 7Nrs 4 4 4 -4 4 4 1 to 29 (Average= 10)Transmission -2.83 dB -3.11 dB -2.96 dB -1.75 dBCrosstalk -17.68 dB -45.04 dB -19.22 dB -10.38 dBFigure 3. Average transmission (a) and cross talk (b) of the 16 channels as a function of σcross, when σbar = 0.1σcross for the fourarchitectures of Fig. 1.3 DISCUSSIONAmong the the mentioned architectures, the Benesˇ network with the smallest Nswitche and Ncrossover offersthe minimum footprint, the lowest insertion loss and therefore the highest transmission, as can be seen in Fig. 3a.On the other hand, based on Fig. 3b, it suffers from the highest crosstalk due to the number of switches inthe cross state being dependent on the requested map. In addition, Benesˇ network is indeed rearrangably non-blocking, i.e. when two sets of input-output are altered, at least one more switch must be altered. This causesa cutoff period in the other outputs which are still mapped to the same inputs. Our calculations show that for a16×16 Benesˇ architecture depending on the rearrangement, Nrs=1 to 29 switches (with an average of 10) areneeded to alter for an alteration of two input-output sets. For cross-bar and PILOSS architectures, Nrs=4 andthe outputs experience no cutoff unless they are altered.The number of switches and crossovers for the path between each input-output pairs is constant for Benesˇand PILOSS configurations, regardless of the requested mapping. For the PILOSS configuration, as can beinferred from 2c, since there is always only one switch in the cross state per path, the signal and cross talklevels show the most independence to the requested mapping. On the other hand, for the cross-bar architectures,the number of elements in each path differs for each input-output combination and it can range from one switchand one crossover (when the last input is mapped to the first output) to 2N − 1 switches and crossovers (whenthe first input is mapped to the last output). In Fig. 2a and b, the average transmission level varies from,respectively, -0.8 dB and -1.2 dB in the second channel to, respectively, -5.7 dB and -5.8 dB in the last channel.For the Benesˇ network in Fig. 2d, transmission varies from -1.34 dB to -2.22 dB, while this variation reduces to0.15 dB for the PILOSS architecture in Fig.2c. Among the studied architectures in this work, cross bar type (II)presents the lowest cross talk, due to its switch design. In fact, the errors in the DCs are bypassed to terminalsand are prevented to propagate in the network. The terminals are considered to be connected to light sinks witha negligible back-reflection.ACKNOWLEDGEMENTThis work has received funding from the European Union’s Horizon 2020 research and innovation pro-gramme under grant agreement No 780283 (MORPHIC).The authors would like to thank Dr. Cristina LermaArce for the fruitful discussions.REFERENCES[1] K. Suzuki, K. Tanizawa, T. Matsukawa, G. Cong, S.-H. Kim, S. Suda, M. Ohno, T. Chiba, H. Tadokoro, M. Yanagihara, Y. Igarashi,M. Masahara, S. Namiki, and H. Kawashima, “Ultra-compact 8 8 strictly-non-blocking Si-wire PILOSS switch,” Optics Express 22,3887–3894 (2014).[2] H. NAKAJIMA, “Development on Guided-Wave Switch Arrays,” IEICE Trans. Electronics E 82, 297–304 (1999).[3] U. Shah, M. Sterner, and J. Oberhammer, “High-Directivity MEMS-Tunable Directional Couplers for 10–18-GHz Broadband Appli-cations,” IEEE Transactions on Microwave Theory and Techniques 61, 3236–3246 (2013).[4] N. Quack, T. J. Seok, S. Han, R. S. Muller, and M. C. Wu, “Scalable Row/Column Addressing of Silicon Photonic MEMS Switches,”IEEE Photonics Technology Letters 28, 561–564 (2016).[5] Y. Sun, Y. Cao, Y. Yi, L. Tian, Y. Zheng, J. Zheng, F. Wang, and D. Zhang, “A low-power consumption MZI thermal optical switchwith a graphene-assisted heating layer and air trench,” RSC Advances 7, 39922–39927 (2017).[6] W. Bogaerts, U. Khan, and Y. Xing, “Layout-Aware Yield Prediction of Photonic Circuits,” IEEE International Conference on GroupIV Photonics pp. 93–94 (2018).

Evaluation of stability of silicon-photonics-based optical switch network architectures against parasitic errors in switch elements

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Evaluation of stability of silicon-photonics-based optical switch network architectures against parasitic errors in switch elements

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