Terabit elastic optical networking (EON) is foreseen as a viable solution to extend the lifetime of a network exploiting the available bandwidth in previously deployed optical fibers. EON is based on bandwidth-variable transponders capable of supporting multiple bit rates and/ or modulation formats according to traffic requirements and node architectures that route arbitrary channel bandwidths. Thus, EON increases the heterogeneity of the network, which may create the need for autonomic adaptive and/or cognitive techniques. In this context, the software-defined networking (SDN) paradigm emerges as an opportunity to enable such techniques thanks to the centralized view of the network by decoupling the control plane and the data plane. This paper surveys different activities carried out at the Optical Technologies Division in Centro de Pesquisa e Desenvolvimento em Telecomunicações, Brazil. We review an optical transport SDN controller for virtual optical networks that supports two adaptive algorithms. First, the autonomic flexible transponder reconfigures the transmission modulation format according to a threshold level. Second, the adaptive global spectrum equalization reconfigures the wavelengths' attenuation profiles applied at the optical nodes to improve the signals' optical signal-to-noise ratio (OSNR) at reception. Finally, we report experimental results of an in-band OSNR monitor for advanced modulation formats.
Resumo-Este artigo apresenta uma análise da influência do ruído térmico e filtragem elétrica na estimativa de OSNR utilizando técnicas de processamento digital de sinais. É apresentada uma complementação ao modelo para monitoração de OSNR, em que o ruído térmico do fotodetector é considerado na estimativa, de modo que é alcançado um ganho de estimação de até 10 dB. Também é analisado o impacto da potência de entrada do sinal no sistema de monitoração e a largura de banda do filtro elétrico na estimação de OSNR.
Palavras-Chave-Monitoração, OSNR, DSP, ruído térmico, largura de banda.Abstract-This article show an analysis of thermal noise and electrical filtering on OSNR estimation using digital signal processing techniques. We expand OSNR estimation model to considering the thermal noise that influence significantly the OSNR calculation, and we reached an estimation gain about 10 dB. Also we examine the impact of input power and electrical filter bandwidth on OSNR estimation.
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