Dimensions-reduced volterra digital pre-distortion based on orthogonal basis for band-limited nonlinear opto-electronic components

Hananel Faig, Yaron Yoffe, Eyal Wohlgemuth, Dan Sadot

Research output: Contribution to journalArticlepeer-review


Optical communication systems often include nonlinear components, such as Mach-Zehnder modulators (MZMs). The components' nonlinearity may have a deleterious effect on the system performance, especially when the memory effect is included. One of the most common methods to mitigate the resultant distortion effects is digital predistortion (DPD) based on the Volterra polynomial model. Typically, the DPD coefficients are extracted using the least squares approach. However, naive implementation of the Volterra polynomial model usually introduces significant complexity due to the large number of model coefficients. Here, we propose the use of orthogonal polynomial basis functions for efficient DPD implementation. The orthogonal basis enables the estimation of each coefficient separately, which provides a significant computational gain. Furthermore, the amount of dominant terms in the orthogonal basis representation is significantly lower, which leads to dramatic relaxation in the DPD implementation. In addition to the analytical modeling approach, a nonparametric method is developed by applying eigenvalue decomposition on the correlation matrix, which is required for the case of dependent random variables, or for the case of unknown probability distribution functions. MZM-based lab experiments and simulations were performed, which indicated a potential saving of 50%-80% in the amount of useful dimensions.

Original languageAmerican English
Article number8610139
JournalIEEE Photonics Journal
Issue number1
StatePublished - 1 Feb 2019


  • Fiber optics communication systems
  • Volterra series
  • nonlinear digital pre-distortion
  • orthogonal basis

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering


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