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Blind equalization

digital signal processing technique in which the transmitted signal is inferred (equalized) from the received signal, while making use only of the transmitted signal statistics

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Record originEnglish Wikipedia
Text licenseCC BY-SA 4.0
Source revisionOct 26, 2025
Entity authorityQ4926640 ↗
Source-derived summary

Blind equalization is a digital signal processing technique in which the transmitted signal is inferred (equalized) from the received signal, while making use only of the transmitted signal statistics. Hence, the use of the word blind in the name.

Blind equalization is essentially blind deconvolution applied to digital communications. Nonetheless, the emphasis in blind equalization is on online estimation of the equalization filter, which is the inverse of the channel impulse response, rather than the estimation of the channel impulse response itself. This is due to blind deconvolution common mode of usage in digital communications systems, as a means to extract the continuously transmitted signal from the received signal, with the channel impulse response being of secondary intrinsic importance.

The estimated equalizer is then convolved with the received signal to yield an estimation of the transmitted signal.

Problem statement

Noiseless model

Assuming a linear time invariant channel with impulse response

{

h

[

n

]

}

n

=

−

∞

∞

{\displaystyle \{h[n]\}_{n=-\infty }^{\infty }}

, the noiseless model relates the received signal

r

[

k

]

{\displaystyle r[k]}

to the transmitted signal

s

[

k

]

{\displaystyle s[k]}

via

r

[

k

]

=

∑

n

=

−

∞

∞

h

[

n

]

s

[

k

−

n

]

{\displaystyle r[k]=\sum _{n=-\infty }^{\infty }h[n]s[k-n]}

The blind equalization problem can now be formulated as follows; Given the received signal

r

[

k

]

{\displaystyle r[k]}

, find a filter

w

[

k

]

{\displaystyle w[k]}

, called an equalization filter, such that

s

^

[

k

]

=

∑

n

=

−

∞

∞

w

[

n

]

r

[

k

−

n

]

{\displaystyle {\hat {s}}[k]=\sum _{n=-\infty }^{\infty }w[n]r[k-n]}

where

s

^

{\displaystyle {\hat {s}}}

is an estimation of

s

{\displaystyle s}

.

The solution

s

^

{\displaystyle {\hat {s}}}

to the blind equalization problem is not unique. In fact, it may be determined only up to a signed scale factor and an arbitrary time delay. That is, if

{

s

~

[

n

]

,

h

~

[

n

]

}

{\displaystyle \{{\tilde {s}}[n],{\tilde {h}}[n]\}}

are estimates of the transmitted signal and channel impulse response, respectively, then

{

c

s

~

[

n

+

d

]

,

h

~

[

n

−

d

]

/

c

}

{\displaystyle \{c{\tilde {s}}[n+d],{\tilde {h}}[n-d]/c\}}

give rise to the same received signal

r

{\displaystyle r}

for any real scale factor

c

{\displaystyle c}

and integral time delay

d

{\displaystyle d}

.

Editorial summary

This brief starts where responsible research should: with the source description of “Blind equalization” as digital signal processing technique in which the transmitted signal is inferred (equalized) from the received signal, while making use only of the transmitted signal statistics. Everything that follows is an evidence route, not borrowed authority.

Editorial reviewA practical starting point whose main value is the path it opens into stronger specialist and primary sources. The current 410-word lead offers orientation but no explicit four-digit date, so chronology should not be assumed. The selected authority fields contribute no independent date. The account is most persuasive where Blind, equalization and digital can be independently traced.
Editorial analysis

Why this record matters

The subject matters to the general reference register because the source frames it as digital signal processing technique in which the transmitted signal is inferred (equalized) from the received signal, while making use only of the transmitted signal statistics. Its deeper value depends on whether names, dates, institutions and citations support that framing.

Evidence profile

Vocabulary and entity names are the principal evidence signals here, because they determine the precision of every later search. The source revision retrieved here is dated Oct 26, 2025. The linked authority identifier is Q4926640. None of the 0 selected statements returned an explicit reference.

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Source & attribution

This entry incorporates text from “Blind equalization” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.