A Channel-Aware Combinatorial Approach to Design High Performance Spatially-Coupled Codes for Magnetic Recording Systems

TL;DR

This paper introduces a novel channel-aware combinatorial approach to design high-performance spatially-coupled codes specifically optimized for magnetic recording channels with memory, significantly improving error rates and SNR performance.

Contribution

It extends the OO-CPO optimization framework to channels with memory, particularly magnetic recording channels, and demonstrates substantial performance improvements over existing codes.

Findings

Up to 3 orders of magnitude FER improvement over prior SC codes.

Approximately 1.1 dB SNR gain compared to previous designs.

Outperforms structured block codes of the same length and rate in FER and SNR.

Abstract

Because of their capacity-approaching performance and their complexity/latency advantages, spatially-coupled (SC) codes are among the most attractive error-correcting codes for use in modern dense data storage systems. SC codes are constructed by partitioning an underlying block code and coupling the partitioned components. Here, we focus on circulant-based SC codes. Recently, the optimal overlap (OO), circulant power optimizer (CPO) approach was introduced to construct high performance SC codes for additive white Gaussian noise (AWGN) and Flash channels. The OO stage operates on the protograph of the SC code to derive the optimal partitioning that minimizes the number of graphical objects that undermine the performance of SC codes under iterative decoding. Then, the CPO optimizes the circulant powers to further reduce this number. Since the nature of detrimental objects in the graph of a code critically depends on the characteristics of the channel of interest, extending the OO-CPO approach to construct SC codes for channels with intrinsic memory is not a straightforward task. In this paper, we tackle one relevant extension; we construct high performance SC codes for practical 1-D magnetic recording channels, i.e., partial-response (PR) channels. Via combinatorial techniques, we carefully build and solve the optimization problem of the OO partitioning, focusing on the objects of interest in the case of PR channels. Then, we customize the CPO to further reduce the number of these objects in the graph of the code. SC codes designed using the proposed OO-CPO approach for PR channels outperform prior state-of-the-art SC codes by up to around 3 orders of magnitude in frame error rate (FER) and 1.1 dB in signal-to-noise ratio (SNR). More intriguingly, our SC codes outperform structured block codes of the same length and rate by up to around 1.8 orders of magnitude in FER and 0.4 dB in SNR.