BIT FLIPPING ALGORITHM FOR PROVIDING SOFT INFORMATION DURING HARD DECISION HARD DECODING

Abstract

A method for using a first decoder operating in a hard decision hard decoding mode to generate soft information for a second decoder operating in a hard decision soft decoding mode includes: generating a look-up table (LUT) linking a number of failed check nodes to a log-likelihood ratio (LLR) value; in a first iteration of the first decoder, inputting the number of failed check nodes to the LUT table to generate an LLR value; and outputting the LLR value to the second decoder.

Claims

1. A method for using a first decoder operating in a hard decision hard decoding mode to generate soft information for a second decoder operating in a hard decision soft decoding mode, the method comprising: generating a look-up table (LUT) linking a number of failed check nodes to a log-likelihood ratio (LLR) value; in a first iteration of the first decoder, inputting the number of failed check nodes to the LUT table to generate an LLR value; and outputting the LLR value to the second decoder.

2. The method of claim 1, wherein the first decoder and the second decoder both utilize a bit flipping algorithm for decoding.

3. The method of claim 1, wherein the LUT is generated utilizing the equation LLR_i=Max LLR*((column_weight+1−i)/column weight +1), wherein i is a number of failed check nodes.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The FIGURE illustrates a parity check matrix H and a Tanner graph.

DETAILED DESCRIPTION

[0012] As detailed in the background, soft information is information relating to how reliable a codeword at the variable node is. One example of soft information is a log-likelihood ratio (LLR) value, which is used by the variable nodes in hard decision soft decoding and soft decision soft decoding. The LLR values are determined by a posteriori probabilities and are related to how many check nodes fail (i.e. how reliable the codeword at the variable node is) as well as a number of error bits in the system. An illustration of the relationship between failed check nodes, error bits and LLR values is provided in Table 1 and Table 2 below.

TABLE-US-00001 TABLE 1 posterior probabilities Error # Failed Check Node 5 15 25 35 45 55 65 0 0 0 0 0 0 0.00001 0.00002 1 0 0 0 0.00001 0.00005 0.00011 0.00022 2 0 0.00009 0.0003 0.00044 0.00106 0.00157 0.0022 3 0.02391 0.02092 0.0211 0.02108 0.02114 0.02132 0.02151 4 0.992 0.93359 0.60861 0.51252 0.31132 0.23141 0.18 5 1 0.9999 0.99157 0.9803 0.90399 0.80908 0.68508

TABLE-US-00002 TABLE 2 LLR values Failed Check Error # Node 5 15 25 35 45 55 65 Fix 1 Fix 0 63 63 63 63 63 63 63 63 63 1 63 63 63 63 63 63 63 63 53 2 63 63 63 59 55 52 49 50 42 3 30 31 31 31 31 31 31 31 31 4 −39 −13 −4 2 6 10 12 20 21 5 −63 −57 −38 −26 −18 −12 −6 10 10

[0013] wherein the LLR values are calculated as shown below.

LLR_i=Max LLR*((column_weight+1−i)/column_weight+1)

[0014] In the above, the value i is the number of failed check nodes. Using Table 1 and Table 2, a look-up table (LUT) can be generated which directly links the number of failed check nodes to the LLR values . The look-up table is illustrated below as Table 3.

TABLE-US-00003 TABLE 3 Fail Check Node Log-likelihood Ratio (LLR) 0 63 1 53 2 42 3 31 4 21 5 10

[0015] Therefore, even when the LDPC decoder is operating in hard decision hard decoding mode, soft information can be generated by using the LUT.

[0016] In an exemplary embodiment of the present invention, a first decoder using a bit flipping algorithm in hard decision hard decoding mode generates LLR values in a first iteration by determining the number of failed check nodes and inputting this information to the LUT to output an LLR value. The first decoder then passes the LLR values to an N2 decoder, which operates in a hard decision soft decoding mode.

[0017] Therefore, in the first iteration of the bit flipping decoder, information will also be provided for a soft decode as well as for the hard decode.

[0018] Those skilled in the art will readily observe that numerous modifications and alterations of the device and method may be made while retaining the teachings of the invention. Accordingly, the above disclosure should be construed as limited only by the metes and bounds of the appended claims.