2026-04-13T01:44:39Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/4066712026-01-23T05:16:40Zcom_2072_1033col_2072_452950

urn:hdl:2117/406671 Low-cost all-optical switching nodes for ultra-dense optical metro-access networks Sarmiento Hernández, Samael Lázaro Villa, José Antonio Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telecomunicació òptica Wavelength division multiplexing Optical communications -- Energy consumption Optical metro-access networks Optical cross connect Reconfigurable optical add-drop multiplexer Ultra-dense wavelength division multiplexing Multiplexatge per divisió de freqüència Comunicacions òptiques -- Consum d'energia Optical metro-access networks (OMANs) must enable the connectivity among 5G-based radio stations, edge datacentres, businesses, and home users. In such a heterogenous scenario, greater scalability, higher levels of dynamic connectivity and flexibility, reduced end-to-end latency, and increased energy efficiency are required. Mesh-based ultra-dense wavelength division multiplexing (u-DWDM) OMANs using reconfigurable optical switching nodes are a promising solution. However, the designs of traditional optical switching nodes relay on wavelength-selective switches (WSSs), which provide high network reconfigurability only at a high cost, making them prohibitive for OMANs. Moving away from this design approach, we proposed a novel low-cost and energy-efficient design based on a modular DWDM structure for reconfigurable optical add-drop multiplexer (ROADM) and optical cross-connects (OXC) nodes compatible with mesh-based u-DWDM OMANs. Results show that proposed solutions can provide performance close to that of WSS-based OXCs but with a switching node cost reduction of one order magnitude. This publication is part of the Spanish I+D+i project TRAINER-B (ref. PID2020-118011GB-C22), funded by MCIN/ AEI/10.13039/501100011033. Peer Reviewed Postprint (author's final draft) 2023 Conference report https://ieeexplore.ieee.org/document/10207172 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-118011GB-C22/ES/INVESTIGACION EN FUTURAS REDES TOTALMENTE OPTIMIZADAS MEDIANTE INTELIGENCIA ARTIFICIAL-B/ Open Access Institute of Electrical and Electronics Engineers (IEEE)