The present invention is directed to data communication systems and methods thereof. According to various embodiments, the present invention provides a communication with a reconfigurable forward-error-correction (FEC) module. The FEC module processes data received from two or more communication lanes, and depending on the mode of operation, the FEC module can combine data from the two or more communication lanes and perform error correction on the combined data, or the FEC module can processes data from the two communications lanes separately and perform error correction independently for the each of the data communication lanes. There are other embodiments as well.

A Reed-Solomon decoder circuit includes: a syndrome calculator circuit to compute syndrome values for a first codeword and a second codeword sequentially supplied to the syndrome calculator circuit, where last symbols of the first codeword overlap with first symbols of the second codeword during an overlap clock cycle between: a first plurality of non-overlap clock cycles during which the first codeword is supplied to the syndrome calculator circuit; and a second plurality of non-overlap clock cycles during which the second codeword is supplied to the syndrome calculator circuit; an error locator and error evaluator polynomial calculator circuit; an error location and error value calculator circuit; an error counter; and an error corrector circuit to correct the errors in the first codeword and the second codeword based on error counts and the error magnitudes computed by an error evaluator circuit.

An application specific integrated circuit (ASIC) tangibly encodes a program of instructions executable by the integrated circuit to perform a method for fast Chase decoding of generalized Reed-Solomon (GRS) codes. The method includes using outputs of a syndrome-based hard-decision (HD) algorithm to find an initial Groebner basis G for a solution module of a key equation, upon failure of HD decoding of a GRS codeword received by the ASIC from a communication channel; traversing a tree of error patterns on a plurality of unreliable coordinates to adjoin a next weak coordinate, where vertices of the tree of error patterns correspond to error patterns, and edges connect a parent error pattern to a child error pattern having exactly one additional non-zero value, to find a Groebner basis for each adjoining error location; and outputting an estimated transmitted codeword when a correct error vector has been found.

Devices, systems, and methods that reduce the latency of detecting that a codeword is uncorrectable are disclosed and described. Such devices, systems, and methods allow the determination that a codeword is uncorrectable prior to determining error locations in the codeword, thus eliminating the need for such an error location search.

An error correction circuit includes: a syndrome calculation block suitable for generating a syndrome based on a data and an error correction code; an error location polynomial generation block suitable for generating an error location polynomial for detecting a location of an error based on the syndrome, where the number of operation stages used for generating the error location polynomial is controlled based on condition information; and a chien search block suitable for correcting an error of the data based on the error location polynomial.

The present invention is directed to data communication systems and methods thereof. According to various embodiments, the present invention provides a communication with a reconfigurable forward-error-correction (FEC) module. The FEC module processes data received from two or more communication lanes, and depending on the mode of operation, the FEC module can combine data from the two or more communication lanes and perform error correction on the combined data, or the FEC module can processes data from the two communications lanes separately and perform error correction independently for the each of the data communication lanes. There are other embodiments as well.

A dual-mode Reed-Solomon decoder is configured to perform error correction for two different encoding schemes. The decoder includes a syndrome calculator block, a key equation solver block, a polynomial evaluation block, and an error correction block. The syndrome calculator block receives encoded input data and calculates syndromes, with the number of calculated syndromes based on the selected decoding mode. The key equation solver block calculates an error locator polynomial and an error evaluator polynomial for the encoded input data, with the degree of the polynomials based on the selected decoding mode. The polynomial evaluation block identifies error locations and magnitudes in the encoded data, with an array of constants input to the block based on the selected decoding mode. The error correction block decodes the encoded input data based on the identified error locations and error magnitudes.

A method may include generating a first computational circuit of a current iteration of a Berlekamp algorithm, the first computational circuit to determine a Berlekamp discrepancy value at least partially based on a current Error-Locator Polynomial (ELP) and observed syndromes; and generating a second computational circuit of the current iteration of the Berlekamp algorithm, the second computational circuit to determine an intermediate value, the intermediate value useable by one or more first computational circuits of one or more subsequent iterations of the Berlekamp algorithm to determine Berlekamp discrepancy values.

Examples disclosed herein relate to very large-scale integration (VLSI) circuit implementations of list decode circuits. In accordance with some examples disclosed herein, a device may include a first and second polynomial evaluation circuit, a field division circuit, a discrepancy filter, and an enhanced error locator polynomial (ELP) circuit. The first and second polynomial evaluation circuits may respectively evaluate a first and second polynomial output from a Berlekamp-Massey algorithm over a plurality of values in a finite field. The field division circuit may divide the outputs from the evaluations to generate a plurality of speculative discrepancy values for an additional iteration of the Berlekamp-Massey algorithm. The discrepancy filter circuit may filter the speculative discrepancy values down to a list of potentially valid discrepancy values that may be used by the enhanced ELP circuit to generate an enhanced ELP.

Examples disclosed herein relate to very large-scale integration (VLSI) circuit implementations of list decode circuits. In accordance with some examples disclosed herein, a list decode circuit may include a syndrome calculation circuit, a symbol erasure circuit, an erasure syndrome calculation circuit and a Berlekamp-Massey algorithm circuit (BMA), and an error locator polynomial (ELP) evaluation circuit. The syndrome calculation circuit may calculate a baseline syndrome and erasure syndrome calculation circuit may calculate erasure syndromes from error locator polynomials calculated by the symbol erasure circuit. The BMA circuit may use the calculated syndromes to generate a series of ELPs, which may be used by the ELP evaluation circuit to identify error locations in a codeword.