Turbo product decoding of cubic tensor codes

TL;DR

This paper explores the construction and decoding of cubic tensor codes, aiming to develop more powerful low-rate error correction codes that can outperform traditional LDPC codes in certain applications.

Contribution

It introduces a novel approach to constructing and decoding cubic tensor codes, expanding the design space beyond square product codes for improved error correction.

Findings

Cubic tensor codes show potential for more powerful low-rate coding.

Decoding methods for cubic tensor codes are developed and analyzed.

Performance comparisons indicate advantages over existing product codes.

Abstract

Long, powerful soft detection forward error correction codes are typically constructed by concatenation of shorter component codes that are decoded through iterative Soft-Input Soft-Output (SISO) procedures. The current gold-standard is Low Density Parity Check (LDPC) codes, which are built from weak single parity check component codes that are capable of producing accurate SO. Due to the recent development of SISO decoders that produce highly accurate SO with codes that have multiple redundant bits, square product code constructions that can avail of more powerful component codes have been shown to be competitive with the LDPC codes in the 5G New Radio standard in terms of decoding performance while requiring fewer iterations to converge. Motivated by applications that require more powerful low-rate codes, in the present paper we explore the possibility of extending this design space by considering the construction and decoding of cubic tensor codes.