High-throughput applications for optical links spured great interest in low-complexity decoding of product codes. Several novel algorithms rely on passing hard messages and careful use of soft channel information to strike the balance between memory efficiency, computational complexity and error-correcting performance. New ideas for component decoding [2] [3] and attempts to go beyond pure iterative decoding [1][4] are of special interest.

The task of the student is to review and understand algorithms for decoding of product codes. After successful completion of the seminar the student will have a comprehensive overview of research in the field of high-throughput decoder design and analysis.

[1] C. Häger and H. D. Pfister, "Approaching Miscorrection-Free Performance of Product Codes With Anchor Decoding," in IEEE Transactions on Communications, vol. 66, no. 7, pp. 2797-2808, July 2018.

(Online: ieeexplore.ieee.org/abstract/document/8316914 )

[2] A. Sheikh, A. Graell i Amat, G. Liva and A. Alvarado, "Refined Reliability Combining for Binary Message Passing Decoding of Product Codes," J. Lightwave Technol., vol. 39, no. 15, pp. 4958-4973, August 2021.

(Online: arxiv.org/pdf/2006.00070 )

[3] A. Sheikh, A. Graell i Amat and A. Alvarado, "Novel High-Throughput Decoding Algorithms for Product and Staircase Codes based on Error-and-Erasure Decoding," J. Lightwave Technol., vol. 39, no. 15, pp. 4909-4922, August 2021.

(Online: arxiv.org/pdf/2008.02181 )

[4] S. Miao, L. Rapp and L. Schmalen, "Improved Soft-Aided Decoding of Product Codes With Dynamic Reliability Scores," J. Lightwave Technol., vol. 40, no. 22, pp. 7279-7288, November 2022.

(Online: arxiv.org/pdf/2204.00466 )

Recommended: Channel Codes for Iterative Decoding and/or Codes on Graphs

Additional: Channel Coding, Information Theory