Crosstalk optimization in low extinction-ratio switch fabrics

Qian, Yi; Mehrvar, Hamid; Ma, Huixiao; Yang, Xiaoling; Zhu, Kun; Fu, H. Y.; Geng, Dongyu; Goodwill, Dominic; Dumais, Patrick; Bernier, Éric

doi:10.1364/ofc.2014.th1i.4

Cited by 13 publications

(5 citation statements)

References 10 publications

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“…The efficiency of these algorithms originates in their topology dependence, which allows for a faster and more effective evaluation of the multistage networks. In contrast, generalpurpose routing algorithms do not provide scalable solutions, as the computational complexity increases rapidly [11], [12], [13]. This is caused by the exponential growth of the control states N st in the network, which depends on the number of switches M as N st = 2 M .…”

Section: Hw Abstractionmentioning

confidence: 99%

Automatic Management of N × N Photonic Switch Powered by Machine Learning in Software-Defined Optical Transport

Khan

Tunesi

Masood

et al. 2021

IEEE Open J. Commun. Soc.

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Optical networking is fast evolving towards the applications of the Software-defined Networking (SDN) paradigm down to the (Wavelength-division Multiplexing) WDM transport layer for cost-effective and flexible infrastructure management. Optical SDN requires each network element's software abstraction to enable full control by the centralized network controller. Nowadays, modern network elements, especially photonic switching systems, are developed by exploiting the fast-emerging technology of Photonic Integrated Circuit (PIC) that consists of complex fabrics of elementary units that can be driven individually using a large set of elementary controls. In this work, we focus on modeling the elementary control states of the topological structures behind PIC N×N switches under a fully blind approach based on Machine Learning (ML) techniques. The ML agent's training and testing datasets are obtained synthetically by software simulation of the photonic switch structure. The proposed technique's scalability and accuracy are validated by considering different dimensions N and applying it to two different switching topologies: the Honey-Comb Rearrangeable Optical Switch and the Beneš network. Excellent results in terms of prediction of the control states are achieved for both of the considered topologies.

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Section: Hw Abstractionmentioning

confidence: 99%

Automatic Management of N × N Photonic Switch Powered by Machine Learning in Software-Defined Optical Transport

Khan

Tunesi

Masood

et al. 2021

IEEE Open J. Commun. Soc.

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“…The following table summarizes the values corresponding to each topology. Note that an architecture's total crosstalk power could be slightly reduced by introducing intelligent algorithms [18].…”

Section: Cumulative Crosstalk Power Termsmentioning

confidence: 99%

Comprehensive Model for Evaluating the Performance of Mach-Zehnder-Based Silicon Photonic Switch Fabrics in Large Scale

2020

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Building a large-scale Mach-Zehnder-based silicon photonic switch circuit (LS-MZS) requires an appropriate choice of architecture. In this work, we propose, for the first time to our knowledge, a single metric that can be used to compare different topologies. We propose an accurate analytical model of the signal-to-crosstalk ratio (SCR) that highlights the performance limitations of the main building blocks: Mach-Zehnder interferometers (MZI) and waveguide crossings. It is based on the cumulative crosstalk and total insertion loss of the LS-MZS. Four different architectures: Beneš, dilated Beneš, switch and select, double-layer network were studied for the reason that they are mainly referenced in the literature. We compared them using our developed SCR indicator. With reference to the state-of-the-art technology, the analysis of the four architectures using SCR showed that, on a large scale, a high number of waveguide crossings significantly affects the performance of the switch matrix. Moreover, better performance was reached using the double-layer-network architecture. Then, we presented a 2 × 2 MZI using two electro-optic phase shifters and a waveguide crossing realized in LETI’s silicon photonics technology. Measured performances were quite good: the switch circuit had a crosstalk of −31.3 dB and an insertion loss estimated to be less than 1.31 dB.

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“…Analysis of the trade-offs of this solution and developing fast optimal scheduling algorithms will be the focus of future work. Another route to increase the scalability is implementing routing algorithms through the switch fabric which optimize the crosstalk [56].…”

Section: Challenges and Opportunitiesmentioning

confidence: 99%

Scaling silicon photonic switch fabrics for data center interconnection networks

Nikolova¹,

Rumley²,

Calhoun³

et al. 2015

Opt. Express

119

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With the rapidly increasing aggregate bandwidth requirements of data centers there is a growing interest in the insertion of optically interconnected networks with high-radix transparent optical switch fabrics. Silicon photonics is a particularly promising and applicable technology due to its small footprint, CMOS compatibility, high bandwidth density, and the potential for nanosecond scale dynamic connectivity. In this paper we analyze the feasibility of building silicon photonic microring based switch fabrics for data center scale optical interconnection networks. We evaluate the scalability of a microring based switch fabric for WDM signals. Critical parameters including crosstalk, insertion loss and switching speed are analyzed, and their sensitivity with respect to device parameters is examined. We show that optimization of physical layer parameters can reduce crosstalk and increase switch fabric scalability. Our analysis indicates that with current state-of-the-art devices, a high radix 128 × 128 silicon photonic single chip switch fabric with tolerable power penalty is feasible. The applicability of silicon photonic microrings for data center switching is further supported via review of microring operations and control demonstrations. The challenges and opportunities for this technology platform are discussed.

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Crosstalk optimization in low extinction-ratio switch fabrics

Abstract: Intelligently setting nominally-idle cells in a PIC photonic switch reduces crosstalk. 100Gb/s DP-QPSK simulation shows 0.3dB OSNR improvement, for 13dB extinction ratio of a practical photonic switch cell. The method operates correctly in a 10Gb/s NRZ test-bed.

Cited by 13 publications

References 10 publications

Automatic Management of N × N Photonic Switch Powered by Machine Learning in Software-Defined Optical Transport

Automatic Management of N × N Photonic Switch Powered by Machine Learning in Software-Defined Optical Transport

Comprehensive Model for Evaluating the Performance of Mach-Zehnder-Based Silicon Photonic Switch Fabrics in Large Scale

Scaling silicon photonic switch fabrics for data center interconnection networks

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