11 Apr
2016
11 Apr
'16
4:22 p.m.
From: Max <msuraev(a)sysmocom.de>
Add python utility to generate .c code with state/output tables for
convolutional encoder/decoder based on polynomial description of the
code. If argument given it'll be interpreted as intended output
directory, otherwise current working directory is used. Note: only
necessary tables are generated. Corresponding header files with actual
osmo_conv_code instance (including puncturing etc) have to be added
manually.
Fixes: OS#1629
---
utils/conv_gen.py | 359 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
1 file changed, 359 insertions(+)
create mode 100755 utils/conv_gen.py
diff --git a/utils/conv_gen.py b/utils/conv_gen.py
new file mode 100755
index 0000000..52c1ab3
--- /dev/null
+++ b/utils/conv_gen.py
@@ -0,0 +1,359 @@
+#!/usr/bin/python
+
+license ="""
+/*
+ * Copyright (C) 2011-2016 Sylvain Munaut <tnt(a)246tNt.com>
+ * Copyright (C) 2016 sysmocom s.f.m.c. GmbH
+ *
+ * All Rights Reserved
+ *
+ * This program is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation; either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License along
+ * with this program; if not, write to the Free Software Foundation, Inc.,
+ * 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ */
+"""
+
+import sys, os
+
+class ConvolutionalCode(object):
+
+ def __init__(self, block_len, k, polys, name = "call-me", description =
"LOL"):
+ # Save simple params
+ self.block_len = block_len
+ self.k = k
+ self.rate_inv = len(polys)
+
+ # Infos
+ self.name = name
+ self.description = description
+
+ # Handle polynoms (and check for recursion)
+ self.polys = [(1, 1) if x[0] == x[1] else x for x in polys]
+
+ rp = [x[1] for x in self.polys if x[1] != 1]
+ if rp:
+ if not all([x == rp[0] for x in rp]):
+ raise ValueError("Bad polynoms: Can't have multiple different divider
polynoms !")
+ if not all([x[0] == 1 for x in polys if x[1] == 1]):
+ raise ValueError("Bad polynoms: Can't have a '1' divider with a non
'1' dividend in a recursive code")
+ self.poly_divider = rp[0]
+ else:
+ self.poly_divider = 1
+
+ @property
+ def recursive(self):
+ return self.poly_divider != 1
+
+ def _combine(self, src, sel, nb):
+ x = src & sel
+ fn_xor = lambda x, y: x ^ y
+ return reduce(fn_xor, [(x >> n) & 1 for n in range(nb)])
+
+ @property
+ def _state_mask(self):
+ return ((1 << (self.k - 1)) - 1)
+
+ def next_state(self, state, bit):
+ nb = self._combine(
+ (state << 1) | bit,
+ self.poly_divider,
+ self.k,
+ )
+ return ((state << 1) | nb) & self._state_mask
+
+ def next_term_state(self, state):
+ return (state << 1) & self._state_mask
+
+ def next_output(self, state, bit, ns = None):
+ # Next state bit
+ if ns is None:
+ ns = self.next_state(state, bit)
+
+ src = (ns & 1) | (state << 1)
+
+ # Scan polynoms
+ rv = []
+ for p_n, p_d in self.polys:
+ if self.recursive and p_d == 1:
+ o = bit # No choice ... (systematic output in recursive case)
+ else:
+ o = self._combine(src, p_n, self.k)
+ rv.append(o)
+
+ return rv
+
+ def next_term_output(self, state, ns = None):
+ # Next state bit
+ if ns is None:
+ ns = self.next_term_state(state)
+
+ src = (ns & 1) | (state << 1)
+
+ # Scan polynoms
+ rv = []
+ for p_n, p_d in self.polys:
+ if self.recursive and p_d == 1:
+ # Systematic output are replaced when in 'termination' mode
+ o = self._combine(src, self.poly_divider, self.k)
+ else:
+ o = self._combine(src, p_n, self.k)
+ rv.append(o)
+
+ return rv
+
+ def next(self, state, bit):
+ ns = self.next_state(state, bit)
+ nb = self.next_output(state, bit, ns = ns)
+ return ns, nb
+
+ def next_term(self, state):
+ ns = self.next_term_state(state)
+ nb = self.next_term_output(state, ns = ns)
+ return ns, nb
+
+ def _print_term(self, pref, fi, num_states, pack, is_state = True):
+ s = "state" if is_state else "output"
+ print >>fi, "\n/* .next_term_%s */" % s
+ print >>fi, "const uint8_t %s_%s_term_%s[] = {" % (pref,
self.name, s)
+ d = []
+ for state in range(num_states):
+ if is_state:
+ x = self.next_term_state(state)
+ else:
+ x = pack(self.next_term_output(state))
+ d.append("%d, " % x)
+ print >>fi, "\t%s\n};" % ''.join(d)
+
+ def _print_x(self, pref, fi, num_states, pack, is_state = True):
+ s = "state" if is_state else "output"
+ print >>fi, "\n/* .next_%s */" % s
+ print >>fi, "const uint8_t %s_%s_%s[][2] = {" % (pref,
self.name, s)
+ for state in range(num_states):
+ if is_state:
+ x0 = self.next_state(state, 0)
+ x1 = self.next_state(state, 1)
+ else:
+ x0 = pack(self.next_output(state, 0))
+ x1 = pack(self.next_output(state, 1))
+ print >>fi, "\t{ %2d, %2d }," % (x0, x1)
+ print >>fi, "};"
+
+ def gen_tables(self, pref, fi):
+ pack = lambda n: sum([x << (self.rate_inv - i - 1) for i, x in enumerate(n)])
+ num_states = 1 << (self.k - 1)
+ print >>fi, "\n/* %s */" % self.description
+ #print >>fi, "const int %s_%s_length = %d;" % (pref,
self.name, self.block_len)
+ #print >>fi, "const int %s_%s_K = %d;" % (pref,
self.name, self.k)
+ self._print_x(pref, fi, num_states, pack)
+ self._print_x(pref, fi, num_states, pack, False)
+
+ if self.recursive:
+ self._print_term(pref, fi, num_states, pack)
+ self._print_term(pref, fi, num_states, pack, False)
+
+poly = lambda *args: sum([(1 << x) for x in args])
+
+xcch = ConvolutionalCode(
+ 224, 5,
+ [
+ ( poly(0, 3, 4), 1 ),
+ ( poly(0, 1, 3, 4), 1 ),
+ ],
+ name = "xcch",
+ description =""" *CCH convolutional code:
+ 228 bits blocks, rate 1/2, k = 5
+ G0 = 1 + D3 + D4
+ G1 = 1 + D + D3 + D4
+"""
+)
+
+tch_afs_12_2 = ConvolutionalCode(
+ 250, 5,
+ [
+ ( 1, 1 ),
+ ( poly(0, 1, 3, 4), poly(0, 3, 4) ),
+ ],
+ name = 'tch_afs_12_2',
+ description = """TCH/AFS 12.2 convolutional code:
+ 250 bits block, rate 1/2, punctured
+ G0/G0 = 1
+ G1/G0 = 1 + D + D3 + D4 / 1 + D3 + D4
+"""
+)
+
+tch_afs_10_2 = ConvolutionalCode(
+ 210, 5,
+ [
+ ( poly(0, 1, 3, 4), poly(0, 1, 2, 3, 4) ),
+ ( poly(0, 2, 4), poly(0, 1, 2, 3, 4) ),
+ ( 1, 1 ),
+ ],
+ name = 'tch_afs_10_2',
+ description = """TCH/AFS 10.2 kbits convolutional code:
+ G1/G3 = 1 + D + D3 + D4 / 1 + D + D2 + D3 + D4
+ G2/G3 = 1 + D2 + D4 / 1 + D + D2 + D3 + D4
+ G3/G3 = 1
+"""
+)
+
+tch_afs_7_95 = ConvolutionalCode(
+ 165, 7,
+ [
+ ( 1, 1 ),
+ ( poly(0, 1, 4, 6), poly(0, 2, 3, 5, 6) ),
+ ( poly(0, 1, 2, 3, 4, 6), poly(0, 2, 3, 5, 6) ),
+ ],
+ name = 'tch_afs_7_95',
+ description = """TCH/AFS 7.95 kbits convolutional code:
+ G4/G4 = 1
+ G5/G4 = 1 + D + D4 + D6 / 1 + D2 + D3 + D5 + D6
+ G6/G4 = 1 + D + D2 + D3 + D4 + D6 / 1 + D2 + D3 + D5 + D6
+"""
+)
+
+tch_afs_7_4 = ConvolutionalCode(
+ 154, 5,
+ [
+ ( poly(0, 1, 3, 4), poly(0, 1, 2, 3, 4) ),
+ ( poly(0, 2, 4), poly(0, 1, 2, 3, 4) ),
+ ( 1, 1 ),
+ ],
+ name = 'tch_afs_7_4',
+ description = """TCH/AFS 7.4 kbits convolutional code:
+ G1/G3 = 1 + D + D3 + D4 / 1 + D + D2 + D3 + D4
+ G2/G3 = 1 + D2 + D4 / 1 + D + D2 + D3 + D4
+ G3/G3 = 1
+"""
+)
+
+tch_afs_6_7 = ConvolutionalCode(
+ 140, 5,
+ [
+ ( poly(0, 1, 3, 4), poly(0, 1, 2, 3, 4) ),
+ ( poly(0, 2, 4), poly(0, 1, 2, 3, 4) ),
+ ( 1, 1 ),
+ ( 1, 1 ),
+ ],
+ name = 'tch_afs_6_7',
+ description = """TCH/AFS 6.7 kbits convolutional code:
+ G1/G3 = 1 + D + D3 + D4 / 1 + D + D2 + D3 + D4
+ G2/G3 = 1 + D2 + D4 / 1 + D + D2 + D3 + D4
+ G3/G3 = 1
+ G3/G3 = 1
+"""
+)
+
+tch_afs_5_9 = ConvolutionalCode(
+ 124, 7,
+ [
+ ( poly(0, 2, 3, 5, 6), poly(0, 1, 2, 3, 4, 6) ),
+ ( poly(0, 1, 4, 6), poly(0, 1, 2, 3, 4, 6) ),
+ ( 1, 1),
+ ( 1, 1),
+ ],
+ name = 'tch_afs_5_9',
+ description = """TCH/AFS 5.9 kbits convolutional code:
+ 124 bits
+ G4/G6 = 1 + D2 + D3 + D5 + D6 / 1 + D + D2 + D3 + D4 + D6
+ G5/G6 = 1 + D + D4 + D6 / 1 + D + D2 + D3 + D4 + D6
+ G6/G6 = 1
+ G6/G6 = 1
+"""
+)
+
+tch_afs_5_15 = ConvolutionalCode(
+ 109, 5,
+ [
+ ( poly(0, 1, 3, 4), poly(0, 1, 2, 3, 4) ),
+ ( poly(0, 1, 3, 4), poly(0, 1, 2, 3, 4) ),
+ ( poly(0, 2, 4), poly(0, 1, 2, 3, 4) ),
+ ( 1, 1 ),
+ ( 1, 1 ),
+ ],
+ name = 'tch_afs_5_15',
+ description = """TCH/AFS 5.15 kbits convolutional code:
+ G1/G3 = 1 + D + D3 + D4 / 1 + D + D2 + D3 + D4
+ G1/G3 = 1 + D + D3 + D4 / 1 + D + D2 + D3 + D4
+ G2/G3 = 1 + D2 + D4 / 1 + D + D2 + D3 + D4
+ G3/G3 = 1
+ G3/G3 = 1
+"""
+)
+
+tch_afs_4_75 = ConvolutionalCode(
+ 101, 7,
+ [
+ ( poly(0, 2, 3, 5, 6), poly(0, 1, 2, 3, 4, 6) ),
+ ( poly(0, 2, 3, 5, 6), poly(0, 1, 2, 3, 4, 6) ),
+ ( poly(0, 1, 4, 6), poly(0, 1, 2, 3, 4, 6) ),
+ ( 1, 1 ),
+ ( 1, 1 ),
+ ],
+ name = 'tch_afs_4_75',
+ description = """TCH/AFS 4.75 kbits convolutional code:
+ G4/G6 = 1 + D2 + D3 + D5 + D6 / 1 + D + D2 + D3 + D4 + D6
+ G4/G6 = 1 + D2 + D3 + D5 + D6 / 1 + D + D2 + D3 + D4 + D6
+ G5/G6 = 1 + D + D4 + D6 / 1 + D + D2 + D3 + D4 + D6
+ G6/G6 = 1
+ G6/G6 = 1
+"""
+)
+
+tetra_rcpc = ConvolutionalCode(
+ 288, 5,
+ [
+ ( poly(0,1,4), 1 ),
+ ( poly(0,2,3,4), 1 ),
+ ( poly(0,1,2,4), 1 ),
+ ( poly(0,1,3,4), 1 ),
+ ],
+ name = 'tetra_rcpc',
+ description = """TETRA RCPC code
+ G1 = 1 + D + D4
+ G2 = 1 + D2 + D3 + D4
+ G3 = 1 + D + D2 + D4
+ G4 = 1 + D + D3 + D4
+"""
+)
+
+tetra_rcpc_tch = ConvolutionalCode(
+ 288, 5,
+ [
+ ( poly(0, 1, 2, 3, 4), 1 ),
+ ( poly(0, 1, 3, 4), 1 ),
+ ( poly(0, 2, 4), 1 ),
+ ],
+ description = """TETRA RCPC TCH code
+"""
+)
+
+def gen_c(path, prefix, code):
+ f = open(os.path.join(path, 'conv_' + code.name + '_gen.c'),
'w')
+ print >>f, license
+ print >>f, "#include <stdint.h>"
+ code.gen_tables(prefix, f)
+
+if __name__ == '__main__':
+ print >>sys.stderr, "Generating convolutional codes..."
+ prefix = "osmo_conv_gsm0503"
+ path = sys.argv[1] if len(sys.argv) > 1 else os.getcwd()
+ gen_c(path, prefix, xcch)
+ gen_c(path, prefix, tch_afs_12_2)
+ gen_c(path, prefix, tch_afs_10_2)
+ gen_c(path, prefix, tch_afs_7_95)
+ gen_c(path, prefix, tch_afs_7_4)
+ gen_c(path, prefix, tch_afs_6_7)
+ gen_c(path, prefix, tch_afs_5_9)
+ gen_c(path, prefix, tch_afs_5_15)
+ gen_c(path, prefix, tch_afs_4_75)
+ print >>sys.stderr, "\tdone."
--
2.8.1