Coding gain explained

In coding theory, telecommunications engineering and other related engineering problems, coding gain is the measure in the difference between the signal-to-noise ratio (SNR) levels between the uncoded system and coded system required to reach the same bit error rate (BER) levels when used with the error correcting code (ECC).

Example

If the uncoded BPSK system in AWGN environment has a bit error rate (BER) of 10−2 at the SNR level 4 dB, and the corresponding coded (e.g., BCH) system has the same BER at an SNR of 2.5 dB, then we say the coding gain =, due to the code used (in this case BCH).

Power-limited regime

\rho\le2

[b/2D or b/s/Hz], i.e. the domain of binary signaling), the effective coding gain

\gammaeff(A)

of a signal set

A

at a given target error probability per bit

Pb(E)

is defined as the difference in dB between the

Eb/N0

required to achieve the target

Pb(E)

with

A

and the

Eb/N0

required to achieve the target

Pb(E)

with 2-PAM or (2×2)-QAM (i.e. no coding). The nominal coding gain

\gammac(A)

is defined as

\gammac(A)=

2
d(A)
min
4Eb

.

This definition is normalized so that

\gammac(A)=1

for 2-PAM or (2×2)-QAM. If the average number of nearest neighbors per transmitted bit

Kb(A)

is equal to one, the effective coding gain

\gammaeff(A)

is approximately equal to the nominal coding gain

\gammac(A)

. However, if

Kb(A)>1

, the effective coding gain

\gammaeff(A)

is less than the nominal coding gain

\gammac(A)

by an amount which depends on the steepness of the

Pb(E)

vs.

Eb/N0

curve at the target

Pb(E)

. This curve can be plotted using the union bound estimate (UBE)

Pb(E)

K
b(A)Q\left(\sqrt{2\gammac(A)Eb
N0
}\right),

where Q is the Gaussian probability-of-error function.

C

with parameters

(n,k,d)

, the nominal spectral efficiency is

\rho=2k/n

and the nominal coding gain is kd/n.

Example

The table below lists the nominal spectral efficiency, nominal coding gain and effective coding gain at

Pb(E)10-5

for Reed–Muller codes of length

n\le64

:
Code

\rho

\gammac

\gammac

(dB)

Kb

\gammaeff

(dB)
- [8,7,2] 1.75 7/4 2.43 4 2.0 - [8,4,4] 1.0 2 3.01 4 2.6 - [16,15,2] 1.88 15/8 2.73 8 2.1 - [16,11,4] 1.38 11/4 4.39 13 3.7 - [16,5,8] 0.63 5/2 3.98 6 3.5 - [32,31,2] 1.94 31/16 2.87 16 2.1 - [32,26,4] 1.63 13/4 5.12 48 4.0 - [32,16,8] 1.00 4 6.02 39 4.9 - [32,6,16] 0.37 3 4.77 10 4.2 - [64,63,2] 1.97 63/32 2.94 32 1.9 - [64,57,4] 1.78 57/16 5.52 183 4.0 - [64,42,8] 1.31 21/4 7.20 266 5.6 - [64,22,16] 0.69 11/2 7.40 118 6.0 - [64,7,32] 0.22 7/2 5.44 18 4.6 -

Bandwidth-limited regime

In the bandwidth-limited regime (

\rho>2~b/2D

, i.e. the domain of non-binary signaling), the effective coding gain

\gammaeff(A)

of a signal set

A

at a given target error rate

Ps(E)

is defined as the difference in dB between the

SNRnorm

required to achieve the target

Ps(E)

with

A

and the

SNRnorm

required to achieve the target

Ps(E)

with M-PAM or (M×M)-QAM (i.e. no coding). The nominal coding gain

\gammac(A)

is defined as

\gammac(A)={(2\rho-

2
1)d
min

(A)\over6Es}.

This definition is normalized so that

\gammac(A)=1

for M-PAM or (M×M)-QAM. The UBE becomes

Ps(E)Ks(A)Q\sqrt{3\gammac(A)SNRnorm

},

where

Ks(A)

is the average number of nearest neighbors per two dimensions.

See also

References

MIT OpenCourseWare, 6.451 Principles of Digital Communication II, Lecture Notes sections 5.3, 5.5, 6.3, 6.4