-
galois.ReedSolomon.decode(codeword: ndarray | FieldArray, errors: False =
False
) ndarray | FieldArray - galois.ReedSolomon.decode(codeword: ndarray | FieldArray, errors: True) Tuple[ndarray | FieldArray, integer | ndarray]
Decodes the Reed-Solomon codeword \(\mathbf{c}\) into the message \(\mathbf{m}\).
- Parameters¶
- codeword: ndarray | FieldArray¶
The codeword as either a \(n\)-length vector or \((N, n)\) matrix, where \(N\) is the number of codewords. For systematic codes, codeword lengths less than \(n\) may be provided for shortened codewords.
- errors: False =
False
¶ - errors: True
Optionally specify whether to return the number of corrected errors. The default is
False
.
- Returns¶
The decoded message as either a \(k\)-length vector or \((N, k)\) matrix.
Optional return argument of the number of corrected symbol errors as either a scalar or \(n\)-length vector. Valid number of corrections are in \([0, t]\). If a codeword has too many errors and cannot be corrected, -1 will be returned.
Notes¶
The codeword vector \(\mathbf{c}\) is defined as \(\mathbf{c} = [c_{n-1}, \dots, c_1, c_0] \in \mathrm{GF}(q)^n\), which corresponds to the codeword polynomial \(c(x) = c_{n-1} x^{n-1} + \dots + c_1 x + c_0\). The message vector \(\mathbf{m}\) is defined as \(\mathbf{m} = [m_{k-1}, \dots, m_1, m_0] \in \mathrm{GF}(q)^k\), which corresponds to the message polynomial \(m(x) = m_{k-1} x^{k-1} + \dots + m_1 x + m_0\).
In decoding, the syndrome vector \(\mathbf{s}\) is computed by \(\mathbf{s} = \mathbf{c}\mathbf{H}^T\), where \(\mathbf{H}\) is the parity-check matrix. The equivalent polynomial operation is the codeword polynomial evaluated at each root of the generator polynomial, i.e. \(\mathbf{s} = [c(\alpha^{c}), c(\alpha^{c+1}), \dots, c(\alpha^{c+2t-1})]\). A syndrome of zeros indicates the received codeword is a valid codeword and there are no errors. If the syndrome is non-zero, the decoder will find an error-locator polynomial \(\sigma(x)\) and the corresponding error locations and values.
For the shortened \(\textrm{RS}(n-s, k-s)\) code (only applicable for systematic codes), pass \(n-s\) symbols into
decode()
to return the \(k-s\)-symbol message.Examples¶
Encode a single message using the \(\textrm{RS}(15, 9)\) code.
In [1]: rs = galois.ReedSolomon(15, 9) In [2]: GF = rs.field In [3]: m = GF.Random(rs.k); m Out[3]: GF([ 2, 14, 13, 11, 11, 9, 1, 0, 6], order=2^4) In [4]: c = rs.encode(m); c Out[4]: GF([ 2, 14, 13, 11, 11, 9, 1, 0, 6, 12, 13, 11, 11, 10, 14], order=2^4)
Corrupt \(t\) symbols of the codeword.
In [5]: e = GF.Random(rs.t, low=1); e Out[5]: GF([14, 9, 5], order=2^4) In [6]: c[0:rs.t] += e; c Out[6]: GF([12, 7, 8, 11, 11, 9, 1, 0, 6, 12, 13, 11, 11, 10, 14], order=2^4)
Decode the codeword and recover the message.
In [7]: d = rs.decode(c); d Out[7]: GF([ 2, 14, 13, 11, 11, 9, 1, 0, 6], order=2^4) In [8]: np.array_equal(d, m) Out[8]: True
Decode the codeword, specifying the number of corrected errors, and recover the message.
In [9]: d, e = rs.decode(c, errors=True); d, e Out[9]: (GF([ 2, 14, 13, 11, 11, 9, 1, 0, 6], order=2^4), 3) In [10]: np.array_equal(d, m) Out[10]: True
Encode a single message using the shortened \(\textrm{RS}(11, 5)\) code.
In [11]: rs = galois.ReedSolomon(15, 9) In [12]: GF = rs.field In [13]: m = GF.Random(rs.k - 4); m Out[13]: GF([ 6, 15, 4, 2, 5], order=2^4) In [14]: c = rs.encode(m); c Out[14]: GF([ 6, 15, 4, 2, 5, 1, 10, 13, 4, 10, 11], order=2^4)
Corrupt \(t\) symbols of the codeword.
In [15]: e = GF.Random(rs.t, low=1); e Out[15]: GF([ 7, 13, 10], order=2^4) In [16]: c[0:rs.t] += e; c Out[16]: GF([ 1, 2, 14, 2, 5, 1, 10, 13, 4, 10, 11], order=2^4)
Decode the codeword and recover the message.
In [17]: d = rs.decode(c); d Out[17]: GF([ 6, 15, 4, 2, 5], order=2^4) In [18]: np.array_equal(d, m) Out[18]: True
Decode the codeword, specifying the number of corrected errors, and recover the message.
In [19]: d, e = rs.decode(c, errors=True); d, e Out[19]: (GF([ 6, 15, 4, 2, 5], order=2^4), 3) In [20]: np.array_equal(d, m) Out[20]: True
Encode a matrix of three messages using the \(\textrm{RS}(15, 9)\) code.
In [21]: rs = galois.ReedSolomon(15, 9) In [22]: GF = rs.field In [23]: m = GF.Random((3, rs.k)); m Out[23]: GF([[ 3, 3, 12, 12, 4, 0, 3, 12, 1], [13, 2, 10, 5, 6, 10, 14, 0, 13], [11, 10, 10, 6, 13, 8, 11, 12, 15]], order=2^4) In [24]: c = rs.encode(m); c Out[24]: GF([[ 3, 3, 12, 12, 4, 0, 3, 12, 1, 0, 15, 6, 4, 2, 1], [13, 2, 10, 5, 6, 10, 14, 0, 13, 15, 2, 0, 15, 0, 11], [11, 10, 10, 6, 13, 8, 11, 12, 15, 10, 7, 1, 13, 6, 2]], order=2^4)
Corrupt the codeword. Add one error to the first codeword, two to the second, and three to the third.
In [25]: c[0,0:1] += GF.Random(1, low=1) In [26]: c[1,0:2] += GF.Random(2, low=1) In [27]: c[2,0:3] += GF.Random(3, low=1) In [28]: c Out[28]: GF([[10, 3, 12, 12, 4, 0, 3, 12, 1, 0, 15, 6, 4, 2, 1], [14, 11, 10, 5, 6, 10, 14, 0, 13, 15, 2, 0, 15, 0, 11], [ 4, 11, 14, 6, 13, 8, 11, 12, 15, 10, 7, 1, 13, 6, 2]], order=2^4)
Decode the codeword and recover the message.
In [29]: d = rs.decode(c); d Out[29]: GF([[ 3, 3, 12, 12, 4, 0, 3, 12, 1], [13, 2, 10, 5, 6, 10, 14, 0, 13], [11, 10, 10, 6, 13, 8, 11, 12, 15]], order=2^4) In [30]: np.array_equal(d, m) Out[30]: True
Decode the codeword, specifying the number of corrected errors, and recover the message.
In [31]: d, e = rs.decode(c, errors=True); d, e Out[31]: (GF([[ 3, 3, 12, 12, 4, 0, 3, 12, 1], [13, 2, 10, 5, 6, 10, 14, 0, 13], [11, 10, 10, 6, 13, 8, 11, 12, 15]], order=2^4), array([1, 2, 3])) In [32]: np.array_equal(d, m) Out[32]: True
Encode a matrix of three messages using the shortened \(\textrm{RS}(11, 5)\) code.
In [33]: rs = galois.ReedSolomon(15, 9) In [34]: GF = rs.field In [35]: m = GF.Random((3, rs.k - 4)); m Out[35]: GF([[ 5, 12, 11, 8, 15], [12, 14, 2, 3, 0], [13, 1, 15, 9, 14]], order=2^4) In [36]: c = rs.encode(m); c Out[36]: GF([[ 5, 12, 11, 8, 15, 9, 10, 6, 4, 11, 10], [12, 14, 2, 3, 0, 2, 4, 7, 8, 0, 11], [13, 1, 15, 9, 14, 14, 9, 12, 6, 5, 0]], order=2^4)
Corrupt the codeword. Add one error to the first codeword, two to the second, and three to the third.
In [37]: c[0,0:1] += GF.Random(1, low=1) In [38]: c[1,0:2] += GF.Random(2, low=1) In [39]: c[2,0:3] += GF.Random(3, low=1) In [40]: c Out[40]: GF([[ 4, 12, 11, 8, 15, 9, 10, 6, 4, 11, 10], [13, 11, 2, 3, 0, 2, 4, 7, 8, 0, 11], [ 4, 10, 8, 9, 14, 14, 9, 12, 6, 5, 0]], order=2^4)
Decode the codeword and recover the message.
In [41]: d = rs.decode(c); d Out[41]: GF([[ 5, 12, 11, 8, 15], [12, 14, 2, 3, 0], [13, 1, 15, 9, 14]], order=2^4) In [42]: np.array_equal(d, m) Out[42]: True
Decode the codeword, specifying the number of corrected errors, and recover the message.
In [43]: d, e = rs.decode(c, errors=True); d, e Out[43]: (GF([[ 5, 12, 11, 8, 15], [12, 14, 2, 3, 0], [13, 1, 15, 9, 14]], order=2^4), array([1, 2, 3])) In [44]: np.array_equal(d, m) Out[44]: True