Low-Complexity Error Correction Algorithms for Data Communication and Storage Systems

Benefit

Traditional error correction often requires a tradeoff between accuracy and hardware cost: highly redundant coding schemes improve reliability but demand significant chip area, power, and processing overhead. This invention addresses that tradeoff by using randomized "noisy" perturbations to reliability metrics, a technique inspired by noisy gradient-descent bit-flipping algorithms. By nudging the decoder's confidence values with controlled randomness tied to the channel's noise characteristics, the system is statistically more likely to escape local error patterns and converge on the globally correct data output, rather than getting trapped by a plausible-but-wrong solution — a common failure mode in simpler bit-flipping decoders.

Because the entire process can be implemented with straightforward semiconductor gate logic (shift registers, counters, summers, and sign comparators) rather than complex iterative message-passing hardware, the design is well-suited to high-throughput, area- and power-constrained applications. The specification explicitly references potential use in standards like 10GBASE-T Ethernet, positioning this technology for markets including high-speed wired networking, wireless communications, optical/fiber links, and data storage — anywhere engineers need robust error correction without the die size or power budget for fully redundant coding schemes.