Programmable VCSEL-based photonic system architecture for future agile Tb/s metro networks

To deal with the challenging requirements of metropolitan area networks (MANs), it is essential to design costeffective systems that can support high capacity and dynamic adaptation, as well as a synergy of programmability and efficient photonic technologies. This becomes crucial for very large MANs that support 5G, where multi-hop connections will need to be dynamically established at target capacities beyond Tb/s. Programmability, automation and modularity of network elements are key desired features. In this work, a modular photonic system, programmable via a software defined networking (SDN) platform, designed for dynamic 5G-supportive MANs, is described and analyzed. We consider modular sliceable bandwidth/bitrate variable transceivers (SBVTs) based on vertical-cavity surface-emitting laser (VCSEL) technology and dense photonic integration. The proposed system and its programmability are experimentally assessed using VCSEL with 10 GHz bandwidth. The experiments are performed over connections as long as six-hop and 160 km, from low-level aggregation nodes to metro-core nodes, thereby enabling IP off-loading. Furthermore, a numerical model is derived to estimate the performance when adopting higher bandwidth VCSELs (≥ 18 GHz) and integrated coherent receivers, as targeted in the proposed system. The analysis is performed for both 50 GHz and 25 GHz granularities. In the former case, 50 Gb/s capacity per flow can be supported over the targeted connections, for OSNR values above 26 dB. When the granularity is 25 GHz, the filter narrowing effect severely impacts the performance. Nevertheless, 1.2 Tb/s capacity (scalable to higher values if spectral/spatial dimensions are exploited) can be achieved when configuring the S-BVT to enable 40 VCSEL flows. This confirms that the system is promising to support Tb/s connections in future agile MANs.Grant numbers : AURORAS - Autonomic and disaggregated optical networks leveraging edge computing and photonic technologies (RTI2018-099178-B-I00). © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works