Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 33,
  • Issue 5,
  • pp. 1037-1043
  • (2015)

Twin-Wave-Based Optical Transmission With Enhanced Linear and Nonlinear Performances

Not Accessible

Your library or personal account may give you access

Abstract

We review recent progresses on the use of twin-wave-based diversity schemes to enhance optical transmission performances in both nonlinear and linear regimes. Phase-conjugated twin waves with and without spectral redundancy are presented. The implications to perturbation-based fiber nonlinearity compensation are discussed. Performance enhancement techniques for real-valued orthogonal frequency-division multiplexed (OFDM) signals with a built-in Hermitian symmetry, as well as positive-valued OFDM twin signals suitable for cost-effective intensity modulation and direct detection, are also discussed.

© 2014 IEEE

PDF Article
More Like This
Generation of 1.024-Tb/s Nyquist-WDM phase-conjugated twin vector waves by a polarization-insensitive optical parametric amplifier for fiber-nonlinearity-tolerant transmission

Xiang Liu, Hao Hu, S. Chandrasekhar, R. M. Jopson, A. H. Gnauck, M. Dinu, C. Xie, and P. J. Winzer
Opt. Express 22(6) 6478-6485 (2014)

Modified phase-conjugate twin wave schemes for fiber nonlinearity mitigation

Yukui Yu and Jian Zhao
Opt. Express 23(23) 30399-30413 (2015)

Nonlinear performance of multi-granularity orthogonal transmission systems with frequency division multiplexing

Fan Zhang, Chuanchuan Yang, Xi Fang, Tingting Zhang, and Zhangyuan Chen
Opt. Express 21(5) 6115-6130 (2013)

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.