OSA's Digital Library

Journal of Lightwave Technology

Journal of Lightwave Technology


  • Vol. 30, Iss. 17 — Sep. 1, 2012
  • pp: 2863–2869

An Efficient Implementation of Modified Regularized Sparse Recovery for Real-Time Optical Power Monitoring

Zhu Liang Yu, Wei Zhou, Zhenghui Gu, Ya Yang, and Gordon Ning Liu

Journal of Lightwave Technology, Vol. 30, Issue 17, pp. 2863-2869 (2012)

View Full Text Article

Acrobat PDF (1073 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

  • Export Citation/Save Click for help


The regularized sparse recovery (RSR) method proposed for optical power monitoring (OPM) has high performance in practice. However, due to its implementation based on interior point method (IPM), it has high computational complexity for real-time OPM system, especially when the number of monitored channels is large. In this paper, we modify the RSR method and propose an efficient implementation of the modified RSR based on the separable surrogate functions (SSF) technique. The resulting algorithm can be realized by simple hardware structure with low computational complexity. Simulation results confirm that accurate and fast optical power spectrum estimation can be achieved with a low-cost tunable optical filter (TOF) by using the proposed method.

© 2012 IEEE

Zhu Liang Yu, Wei Zhou, Zhenghui Gu, Ya Yang, and Gordon Ning Liu, "An Efficient Implementation of Modified Regularized Sparse Recovery for Real-Time Optical Power Monitoring," J. Lightwave Technol. 30, 2863-2869 (2012)

Sort:  Year  |  Journal  |  Reset


  1. Y. Chung, "Performance monitoring in optical networks (tutorial)," Proc. APOC (2003) pp. 5282-46.
  2. M. D. Salik, C. Nicolas, A. Carre, S. J. Caracci, "Fiber fabry-perot interferometer for optical channel monitoring," Proc. ECOC (2002) pp. 1-2.
  3. M. Li, G. J. Pendock, R. J. Evans, "Spectral recovery for low-resolution optical spectrum monitors," IEEE Photon. Technol. Lett. 20, 1109-1111 (2008).
  4. Z. L. Yu, G. N. Liu, S. Qiu, Y. Wei, S. Shen, Q. Xiong, "Regularized sparse recovery for optical power monitoring with low-cost tunable optical filters," IEEE Photon. Technol. Lett. 22, 697-699 (2010).
  5. C. Che, R. J. Evans, R. J. Tucker, "Signal processing for optical power spectrum monitoring," Proc. ACSSC (2006) pp. 559-563.
  6. M. Li, G. J. Pendock, R. J. Evans, "Regularization techniques for extracting osnr from low resolution wdm channel monitors," J. Lightw. Technol. 27, 1162-1171 (2009).
  7. S. Boyd, L. Vandenberghe, Convex Optimization (Cambridge Univ., 2004).
  8. M. Elad, B. Matalon, M. Zibulevsky, "Coordinate and subspace optimization methods for linear least squares with non-quadratic regularization," Appl. Comput. Harmon. Anal. 23, 346-367 (2007).
  9. R. T. Rockafellar, "Monotone operators and the proximal point algorithm," SIAM J. Control Optim. 14, 877-898 (1976).
  10. M. Lobo, L. Vandenberghe, S. Boyd, H. Lebret, "Applications of second-order cone programming," Linear Algebra and Its Applications 284, 193-228 (1998).

Cited By

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited