Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 25,
  • Issue 3,
  • pp. 787-798
  • (2007)

Maximizing the Transmission Performance of Adaptively Modulated Optical OFDM Signals in Multimode-Fiber Links by Optimizing Analog-to-Digital Converters

Not Accessible

Your library or personal account may give you access

Abstract

Based on a comprehensive theoretical model of a recently proposed novel technique known as adaptively modulated optical orthogonal frequency-division multiplexing (AMOOFDM), investigations are undertaken into the impact of an analog-to-digital converter involved in the AMOOFDM modem on the transmission performance of AMOOFDM signals in unamplified intensity-modulation and direct-detection (IMDD) multimode-fiber (MMF)-based links. It is found that signal quantization and clipping effects are significant in determining the maximum achievable transmission performance of the AMOOFDM modem. A minimum quantization bit value of ten and optimum clipping ratio of 13 dB are identified, based on which, the transmission performance is maximized. It is shown that 40-Gb/s-over-220-m and 32-Gb/s-over-300-m IMDD-AMOOFDM signal transmission at 1550 nm with loss margins of about 15 dB is feasible in the installed worst case 62.5-µm MMF links having 3-dB effective bandwidths as small as 150 MHz · km. Meanwhile, excellent performance, robustness to fiber types, and variation in launch conditions and signal bit rates is observed. In addition, discussions are presented of the potential of 100-Gb/s AMOOFDM signal transmission over installed MMF links.

© 2007 IEEE

PDF Article
More Like This
Extensive Comparisons of Optical Fast-OFDM and Conventional Optical OFDM for Local and Access Networks

E. Giacoumidis, A. Tsokanos, C. Mouchos, G. Zardas, C. Alves, J. L. Wei, J. M. Tang, C. Gosset, Y. Jaouën, and I. Tomkos
J. Opt. Commun. Netw. 4(10) 724-733 (2012)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.