Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 42,
  • Issue 9,
  • pp. 3118-3127
  • (2024)

Deployment of Ultrasmall-Size Cluster-Assisting Lookup Tables in IM/DD Systems

Not Accessible

Your library or personal account may give you access

Abstract

In the C-band high-speed long-reach optical intensity modulation direct detection (IM/DD) communication system, severe signal distortion, including chromatic dispersion and device bandwidth limitations, making the size of lookup tables (LUTs) required by equalizers too large to be operated. In this paper, we propose a cluster-assisting lookup table (CLUT) approach to reduce the table size significantly. In addition, we also propose multiplication-free CLUT-based decision-feedback equalizer (CLUT-DFE) and CLUT-based log-maximum a posteriori estimation with a fixed number of surviving states (CLUT-FS-MAP) to effectively compensate for channel distortions. Using the k-means clustering algorithm, the proposed CLUT significantly shortens the table size by reducing the number of independent variable values input. The table size of traditional LUTs increases exponentially with the filter tap number, making it impossible for LUTs to replace filters with tap numbers greater than 20. The CLUT breaks this limitation. The proposed schemes are experimentally performed in a C-band 61-Gb/s IM/DD optical on-off keying (OOK) system featuring a 3.65-GHz 3-dB bandwidth over a 100-km standard single mode fiber (SSMF). Compared to traditional LUT, CLUT reduces table size by about 10 orders of magnitude with the same performance. To the best of our knowledge, this study represents the first deployment of ultrasmall-size CLUT in equalization.

PDF Article

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.