Bar product

In information theory, the bar product of two linear codes C2  C1 is defined as

C_1 \mid C_2 = \{ (c_1\mid c_1+c_2) : c_1 \in C_1, c_2 \in C_2 \},

where (a | b) denotes the concatenation of a and b. If the code words in C1 are of length n, then the code words in C1 | C2 are of length 2n.

The bar product is an especially convenient way of expressing the Reed–Muller RM(d, r) code in terms of the Reed–Muller codes RM(d1, r) and RM(d1, r1).

The bar product is also referred to as the | u | u+v | construction[1] or (u | u + v) construction.[2]

Properties

Rank

The rank of the bar product is the sum of the two ranks:

\operatorname{rank}(C_1\mid C_2) = \operatorname{rank}(C_1) + \operatorname{rank}(C_2)\,

Proof

Let  \{ x_1, \ldots , x_k \} be a basis for C_1 and let \{ y_1, \ldots , y_l \} be a basis for C_2. Then the set

\{ (x_i\mid x_i) \mid 1\leq i \leq k \} \cup \{ (0\mid y_j) \mid 1\leq j \leq l \}

is a basis for the bar product C_1\mid C_2.

Hamming weight

The Hamming weight w of the bar product is the lesser of (a) twice the weight of C1, and (b) the weight of C2:

w(C_1\mid C_2) = \min \{ 2w(C_1) , w(C_2) \}. \,

Proof

For all c_1 \in C_1,

(c_1\mid c_1 + 0 ) \in C_1\mid C_2

which has weight 2w(c_1). Equally

 (0\mid c_2) \in C_1\mid C_2

for all c_2 \in C_2 and has weight w(c_2). So minimising over c_1 \in C_1, c_2 \in C_2 we have

w(C_1\mid C_2) \leq \min \{ 2w(C_1) , w(C_2) \}

Now let c_1 \in C_1 and c_2 \in C_2, not both zero. If c_2\not=0 then:


\begin{align}
w(c_1\mid c_1+c_2) &= w(c_1) + w(c_1 + c_2) \\
& \geq w(c_1 + c_1 + c_2) \\
& = w(c_2) \\
& \geq w(C_2)
\end{align}

If c_2=0 then

\begin{align}
w(c_1\mid c_1+c_2) & = 2w(c_1) \\
& \geq 2w(C_1)
\end{align}

so

w(C_1\mid C_2) \geq \min \{ 2w(C_1) , w(C_2) \}

See also

References

  1. F.J. MacWilliams; N.J.A. Sloane (1977). The Theory of Error-Correcting Codes. North-Holland. p. 76. ISBN 0-444-85193-3.
  2. J.H. van Lint (1992). Introduction to Coding Theory. GTM 86 (2nd ed.). Springer-Verlag. p. 47. ISBN 3-540-54894-7.
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