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Enhanced absolute added correlative coding for low earth orbit optical intersatellite links

  • Amrita Gill ORCID logo EMAIL logo , Gnanam Gnanagurunathan and Nafizah Khan
Published/Copyright: January 31, 2025
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Abstract

This paper presents the polarization division multiplexed absolute added correlative coding (PDM-AACC) in an optical intersatellite link (OISL). It is modeled to operate in a low Earth orbit (LEO) satellite broadband constellation network, and its receiver front-end (RFE) comprises avalanche photodiodes (APDs). Its performance is then comparatively investigated against two other OISLs adopting the absolute added correlative coding (AACC) and the 4-pulse amplitude modulation (4-PAM) formats, respectively. When transmitting 20 Gbps over the maximum LEO-LEO link distance of 6,000 km, the 4-PAM and AACC needed a minimum transmitter laser power of 36 dBm and 29 dBm to meet the bit-error rate (BER) requirement of less than 10−9, whereas the PDM-AACC required 27 dBm. It also supported longer transmission ranges, narrower telescope pointing error angles, and smaller telescope aperture diameter sizes in comparison to the 4-PAM and the AACC. The modeled PDM-AACC modulated OISL further improved on the receiver sensitivities of the latter two by 10 dBm and 2 dBm in addition to increasing its spectral efficiencies. The bit rate of all three links were then doubled to 40 Gbps. While the 4-PAM and AACC sustained it for distances of 2,800 km and 4,800 km, the PDM-AACC met the BER requirement for distances of up to 6,200 km.


Corresponding author: Amrita Gill, Department of Electrical and Electronic Engineering, University of Nottingham Malaysia Campus, Jalan Broga, 43500, Semenyih, Malaysia, E-mail:
Amrita Gill contributed equally to this work and share first authorship. Gnanam Gnanagurunathan and Nafizah Khan contributed equally to this work and share senior authorship.
  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Received: 2024-09-21
Accepted: 2025-01-14
Published Online: 2025-01-31

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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