Efficient Coding Architectures for Reed–Solomon and Low-Density Parity-Check Decoders for Magnetic and Other Data Storage Systems

High-performance error correction codes are used in high-density data storage devices to overcome noise and channel impairments. In this paper, we develop novel and efficient decoding architectures for Reed–Solomon (RS) and low-density parity-check (LDPC) codes that are used in almost all data storage devices. First, we present a high-speed low-latency hard-decision-based pipelined RS decoder architecture that computes the error locator polynomial in exactly $2t$ clock cycles without parallelism. The RS decoder is a two-stage pipelined engine operating at the least latency possible, thereby, significantly reducing the size of the delay buffer. The RS decoder is implemented using Cadence tools and Kintex-7 field programmable gate array (FPGA). The technology-scaled normalized throughput of the pipelined RS decoder is almost two times compared with the existing decoders. The overall processing latency is reduced by almost 80% compared with the existing designs. Second, we design a high-throughput LDPC decoder using layered and non-layered min-sum algorithm based on non-uniform quantization (NUQ) on an FPGA kit. Unlike the standard state-of-the-art uniform quantization used in virtually all decoder circuits, our NUQ technique: 1) achieves a slight performance improvement of ~0.1 dB in the signal-to-noise ratio using equal number of bits and 2) yields 20% area savings (using 1 bit less) for the block RAMs used for storing intermediate check node and variable node messages.