Minimizing the Number of Detrimental Objects in Multi-Dimensional Graph-Based Codes

The increasing demand for access to data has led to dramatic increases in data storage densities, and as densities increase, new sources of error appear. Multi-dimensional (MD) graph-based codes are capable of mitigating error sources like interference and channel non-uniformity in dense storage devices. A recent innovation improves the performance of MD spatially-coupled codes that are based on circulants by carefully relocating some circulants to minimize the number of short cycles. However, cycles become more detrimental when they combine together to form more advanced objects, e.g., absorbing sets, including low-weight codewords. In this paper, we show how MD relocations can be exploited to minimize the number of detrimental objects in the graph of an MD code. Moreover, we demonstrate the savings in the number of relocation arrangements earned by focusing on objects rather than their constituent cycles. Our technique is applicable to a wide variety of one-dimensional (OD) codes. Simulation results demonstrate significant lifetime gains achieved by the proposed MD codes on an industry-recommended model for Flash systems, and signal-to-noise ratio gains on an industry-recommended model for magnetic recording systems, both with respect to OD codes with similar parameters. The second order analysis of MD relocations relies on conditions and options for an object, called a pattern, to form a bigger cycle after MD relocations, which are discussed in this paper.

Duke Scholars

Author Robert Calderbank Computer Science