Terminated and Tailbiting Spatially-Coupled Codes with Optimized Bit Mappings for Spectrally Efficient Fiber-Optical Systems

TL;DR

This paper investigates the design of spectrally efficient fiber-optical systems using spatially coupled FEC codes, optimizing bit mappings to enhance performance, especially for tailbiting codes, with density evolution analysis guiding the optimization.

Contribution

It introduces optimized bit allocation strategies for terminated and tailbiting spatially coupled codes, improving tailbiting code performance with lower overhead compared to baseline methods.

Findings

Optimized bit mappings significantly improve tailbiting SC code performance.

Performance of tailbiting codes approaches that of terminated codes with optimization.

Sequential allocation is nearly optimal for terminated SC codes, with marginal gains from optimization.

Abstract

We study the design of spectrally efficient fiber-optical communication systems based on different spatially coupled (SC) forward error correction (FEC) schemes. In particular, we optimize the allocation of the coded bits from the FEC encoder to the modulation bits of the signal constellation. Two SC code classes are considered. The codes in the first class are protograph-based low-density parity-check (LDPC) codes which are decoded using iterative soft-decision decoding. The codes in the second class are generalized LDPC codes which are decoded using iterative hard-decision decoding. For both code classes, the bit allocation is optimized for the terminated and tailbiting SC cases based on a density evolution analysis. An optimized bit allocation can significantly improve the performance of tailbiting SC codes codes over the baseline sequential allocation, up to the point where they have a comparable gap to capacity as their terminated counterparts, at a lower FEC overhead. For the considered terminated SC codes, the optimization only results in marginal performance improvements, suggesting that in this case a sequential allocation is close to optimal.