Next: Bounds on the size
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We start to look at bounds on the size of codes.
Definition 1.11.1
We define
to be the maximum number of code words in a linear code over
of length
and minimum weight
.
is the maximum number of code words in any arbitrary code over
of length
and minimum weight
.
Theorem 1.11.2
Sphere Packing Bound
where
.
Proof.
Let

be a code over

(possibly nonlinear) of length

and minimum distance

such that

contains

codewords. By Theorem 1.11.2, the spheres of radius

about these distinct codewords are disjoint. Define
Then,

is the total number of vectors. Then,

cannot be bigger than the number

of vectors in

. Hence, we must have
or
which is precisely the sphere packing bound.
Definition 1.11.3
Let
be a
code and
. If the spheres of radius
are pairwise disjoint and their union is the entire space
, then the code
is said to be perfect.
Example: 1.12.2 in the book.
We know that
over
is an
code where
and
(
). Then,
Hence, the Hamming codes are perfect.
Theorem 1.11.4
- (i)
- There exist perfect single error-correcting codes over
which are not linear and all codes have parameters corresponding to Hamming codes.
- (ii)
- The only non-trivial perfect multiple error-correcting codes have the same length, number of codewords, and minimum distance as either the
Golay code or the
ternary Golay code.
- (iii)
- Any binary possibly nonlinear code with
(respectively
) vectors containing the
vector with length
(resp.
) and minimum distance
(resp.
) is equivalent to the [23,12,7] binary (resp. [11,6,5] ternary) Golay code.
Note that
and
if and only if
is perfect
Definition 1.11.6
We say that
is quasi-perfect if
.
Theorem 1.11.7
Let
be linear and
a parity check matrix.
- (i)
-
is the weight of the coset of largest weight.
- (ii)
-
is the smallest number such that every nonzero syndrome is a combination of
or fewer columns of
, i.e., there exists a syndrome requiring
columns.
Theorem 1.11.8
Let
code,
the extension of
, and
be the puncturing of
on any coordinate. Then,
- (i)
-
.
- (ii)
-
is either
or
.
- (iii)
-
is either
or
.
- (iv)
- If
, then
.
- (v)
- Assume
is a coset leader of
. If
, all of whose nonzero entries agree with
, then
is also a coset leader of
. In particular, if there exists a coset with weight
, there exists a coset of any weight less than
.
Proof.
Part

. Let

be a coset leader; then define

. It is enough to show that

is a coset leader. Let

and

be its extension.
If the weight of

is even, then
where the last inequality is because

is a coset leader (

for all codewords).
If the weight of

is odd, then
By Theorem 1.4.3, we get that the

is odd if and only if

is even. In particular, the

. Therefore,
and
Thus, the
for all

. Hence,

is a coset leader.
Example 1.12.7: Let
be generated by
. Then,
,
.
However, let
. Note that each vector is less than two away from an element of
, so
.
Now, let's consider the extension of
,
. This is generated by
:
Here,
and
. We can tell that
because
. Suppose that
is not within
of
and
. By exhaustion, we can see that this cannot happen.
Wednesday, 6-15-2005:
Next: Bounds on the size
Up: Basic concepts of linear
Previous: Encoding, Decoding, and Shannon's
Brian Bockelman
2005-06-29