BCH Codes
Overview
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Table of Contents
6.8.3 BCH Codes
Bose–Chadhuri–Hocquenghem (BCH) codes are a generalization of Hamming
codes that allow multiple error correction. They are a powerful class of cyclic codes
that provide a large selection of block lengths, code rates, alphabet sizes, and errorcorrecting
capability. Table 6.4 lists some code generators g(x) commonly used for
the construction of BCH codes [8] for various values of n, k, and t, up to a block
length of 255. The coefficients of g(x) are presented as octal numbers arranged so
that when they are converted to binary digits the rightmost digit corresponds to the
zero-degree coefficient of g(x). From Table 6.4, one can easily verify a cyclic code
property—the generator polynomial is of degree n − k. BCH codes are important
because at block lengths of a few hundred, the BCH codes outperform all other
block codes with the same block length and code rate. The most commonly used
BCH codes employ a binary alphabet and a codeword block length of n = 2m − 1,
where m = 3, 4, . . . .
The title of Table 6.4 indicates that the generators shown are for those BCH
codes known as primitive codes. The term “primitive” is a number-theoretic concept
requiring an algebraic development [7, 10–11], which is presented in Section
8.1.4. In Figures 6.21 and 6.22 are plotted error performance curves of two BCH
codes (127, 64) and (127, 36), to illustrate comparative performance. Assuming
hard decision decoding, the PB versus channel error probability is shown in Figure
6.21. The PB versus Eb/N0 for coherently demodulated BPSK over a Gaussian
channel is shown in Figure 6.22. The curves in Figure 6.22 seem to depart from our
expectations. They each have the same block size, yet the more redundant (127, 36)
code does not exhibit as much coding gain as does the less redundant (127, 64)
code. It has been shown that a relatively broad maximum of coding gain versus
code rate for fixed n occurs roughly between coding rates of 1/3 and 3/4 for BCH codes
[12]. Performance over a Gaussian channel degrades substantially at very high or
very low rates [11].
Figure 6.23 represents computed performance of BCH codes [13] using coherently
demodulated BPSK with both hard- and soft-decision decoding. Soft-decision
decoding is not usually used with block codes because of its complexity. However,
whenever it is implemented, it offers an approximate 2-dB coding gain over harddecision
decoding. For a given code rate, the decoded error probability is known
to improve with increasing block length n [4]. Thus, for a given code rate, it is

Figure 6.23 PB versus Eb/N0 for coherently demodulated BPSK over a Gaussian channel
using BCH codes. (Reprinted with permission
from L. J. Weng, “Soft and Hard Decoding Performance Comparisons for BCH Codes,”
Proc. Int. Conf. Commun., 1979, Fig. 3, p. 25.5.5. © 1979 IEEE.)


interesting to consider the block length that would be required for the harddecision-
decoding performance to be comparable to the soft-decision-decoding performance.
In Figure 6.23, the BCH codes shown all have code rates of approximately 1/2.
From the figure [13] it appears that for a fixed code rate, the hard-decision-decoded
BCH code of length 8 times n or longer has a better performance (for PB of about 10-6 or less)
than that of a soft-decision-decoded BCH code of length n. One special subclass
of the BCH codes (the discovery of which preceded the BCH codes) is the particularly
useful nonbinary set called Reed-Solomon codes. They are described in Section 8.1.
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