#!/usr/bin/python2 mod_license = """ /* * Copyright (C) 2011-2016 Sylvain Munaut * 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, math from functools import reduce class ConvolutionalCode(object): def __init__(self, block_len, polys, name, description = None, puncture = [], term_type = None): # Save simple params self.block_len = block_len self.k = 1 self.puncture = puncture self.rate_inv = len(polys) self.term_type = term_type # Infos self.name = name self.description = description # Handle polynomials (and check for recursion) self.polys = [(1, 1) if x[0] == x[1] else x for x in polys] # Determine the polynomial degree for (x, y) in polys: self.k = max(self.k, int(math.floor(math.log(max(x, y), 2)))) self.k = self.k + 1 self.poly_divider = 1 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 polynomials: " "Can't have multiple different divider polynomials!") if not all([x[0] == 1 for x in polys if x[1] == 1]): raise ValueError("Bad polynomials: " "Can't have a '1' divider with a non '1' dividend " "in a recursive code") self.poly_divider = rp[0] @property def recursive(self): return self.poly_divider != 1 @property def _state_mask(self): return (1 << (self.k - 1)) - 1 def next_state(self, state, bit): nb = 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 polynomials rv = [] for p_n, p_d in self.polys: if self.recursive and p_d == 1: # No choice ... (systematic output in recursive case) o = bit else: o = 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 polynomials 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 = combine(src, self.poly_divider, self.k) else: o = 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, fi, num_states, pack = False): items = [] for state in range(num_states): if pack: x = pack(self.next_term_output(state)) else: x = self.next_term_state(state) items.append(x) # Up to 12 numbers should be placed per line print_formatted(items, "%3d, ", 12, fi) def _print_x(self, fi, num_states, pack = False): items = [] for state in range(num_states): if pack: x0 = pack(self.next_output(state, 0)) x1 = pack(self.next_output(state, 1)) else: x0 = self.next_state(state, 0) x1 = self.next_state(state, 1) items.append((x0, x1)) # Up to 4 blocks should be placed per line print_formatted(items, "{ %2d, %2d }, ", 4, fi) def _print_puncture(self, fi): # Up to 12 numbers should be placed per line print_formatted(self.puncture, "%3d, ", 12, 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) fi.write("static const uint8_t %s_state[][2] = {\n" % self.name) self._print_x(fi, num_states) fi.write("};\n\n") fi.write("static const uint8_t %s_output[][2] = {\n" % self.name) self._print_x(fi, num_states, pack) fi.write("};\n\n") if self.recursive: fi.write("static const uint8_t %s_term_state[] = {\n" % self.name) self._print_term(fi, num_states) fi.write("};\n\n") fi.write("static const uint8_t %s_term_output[] = {\n" % self.name) self._print_term(fi, num_states, pack) fi.write("};\n\n") if len(self.puncture): fi.write("static const int %s_puncture[] = {\n" % self.name) self._print_puncture(fi) fi.write("};\n\n") # Write description as a multi-line comment if self.description is not None: fi.write("/**\n") for line in self.description: fi.write(" * %s\n" % line) fi.write(" */\n") # Print a final convolutional code definition fi.write("const struct osmo_conv_code %s_%s = {\n" % (pref, self.name)) fi.write("\t.N = %d,\n" % self.rate_inv) fi.write("\t.K = %d,\n" % self.k) fi.write("\t.len = %d,\n" % self.block_len) fi.write("\t.next_output = %s_output,\n" % self.name) fi.write("\t.next_state = %s_state,\n" % self.name) if self.term_type is not None: fi.write("\t.term = %s,\n" % self.term_type) if self.recursive: fi.write("\t.next_term_output = %s_term_output,\n" % self.name) fi.write("\t.next_term_state = %s_term_state,\n" % self.name) if len(self.puncture): fi.write("\t.puncture = %s_puncture,\n" % self.name) fi.write("};\n\n") poly = lambda *args: sum([(1 << x) for x in args]) def combine(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)]) def print_formatted(items, format, count, fi): counter = 0 # Print initial indent fi.write("\t") for item in items: if counter > 0 and counter % count == 0: fi.write("\n\t") fi.write(format % item) counter += 1 fi.write("\n") # Polynomials according to 3GPP TS 05.03 Annex B G0 = poly(0, 3, 4) G1 = poly(0, 1, 3, 4) G2 = poly(0, 2, 4) G3 = poly(0, 1, 2, 3, 4) G4 = poly(0, 2, 3, 5, 6) G5 = poly(0, 1, 4, 6) G6 = poly(0, 1, 2, 3, 4, 6) G7 = poly(0, 1, 2, 3, 6) CCH_poly = [ ( G0, 1 ), ( G1, 1 ), ] MCS_poly = [ ( G4, 1 ), ( G7, 1 ), ( G5, 1 ), ] conv_codes = [ # xCCH definition ConvolutionalCode( 224, CCH_poly, name = "xcch", description = [ "xCCH convolutional code:", "228 bits blocks, rate 1/2, k = 5", "G0 = 1 + D3 + D4", "G1 = 1 + D + D3 + D4", ] ), # RACH definition ConvolutionalCode( 14, CCH_poly, name = "rach", description = ["RACH convolutional code"] ), # SCH definition ConvolutionalCode( 35, CCH_poly, name = "sch", description = ["SCH convolutional code"] ), # CS2 definition ConvolutionalCode( 290, CCH_poly, puncture = [ 15, 19, 23, 27, 31, 35, 43, 47, 51, 55, 59, 63, 67, 71, 75, 79, 83, 91, 95, 99, 103, 107, 111, 115, 119, 123, 127, 131, 139, 143, 147, 151, 155, 159, 163, 167, 171, 175, 179, 187, 191, 195, 199, 203, 207, 211, 215, 219, 223, 227, 235, 239, 243, 247, 251, 255, 259, 263, 267, 271, 275, 283, 287, 291, 295, 299, 303, 307, 311, 315, 319, 323, 331, 335, 339, 343, 347, 351, 355, 359, 363, 367, 371, 379, 383, 387, 391, 395, 399, 403, 407, 411, 415, 419, 427, 431, 435, 439, 443, 447, 451, 455, 459, 463, 467, 475, 479, 483, 487, 491, 495, 499, 503, 507, 511, 515, 523, 527, 531, 535, 539, 543, 547, 551, 555, 559, 563, 571, 575, 579, 583, 587, -1 ], name = "cs2", description = [ "CS2 convolutional code:", "G0 = 1 + D3 + D4", "G1 = 1 + D + D3 + D4", ] ), # CS3 definition ConvolutionalCode( 334, CCH_poly, puncture = [ 15, 17, 21, 23, 27, 29, 33, 35, 39, 41, 45, 47, 51, 53, 57, 59, 63, 65, 69, 71, 75, 77, 81, 83, 87, 89, 93, 95, 99, 101, 105, 107, 111, 113, 117, 119, 123, 125, 129, 131, 135, 137, 141, 143, 147, 149, 153, 155, 159, 161, 165, 167, 171, 173, 177, 179, 183, 185, 189, 191, 195, 197, 201, 203, 207, 209, 213, 215, 219, 221, 225, 227, 231, 233, 237, 239, 243, 245, 249, 251, 255, 257, 261, 263, 267, 269, 273, 275, 279, 281, 285, 287, 291, 293, 297, 299, 303, 305, 309, 311, 315, 317, 321, 323, 327, 329, 333, 335, 339, 341, 345, 347, 351, 353, 357, 359, 363, 365, 369, 371, 375, 377, 381, 383, 387, 389, 393, 395, 399, 401, 405, 407, 411, 413, 417, 419, 423, 425, 429, 431, 435, 437, 441, 443, 447, 449, 453, 455, 459, 461, 465, 467, 471, 473, 477, 479, 483, 485, 489, 491, 495, 497, 501, 503, 507, 509, 513, 515, 519, 521, 525, 527, 531, 533, 537, 539, 543, 545, 549, 551, 555, 557, 561, 563, 567, 569, 573, 575, 579, 581, 585, 587, 591, 593, 597, 599, 603, 605, 609, 611, 615, 617, 621, 623, 627, 629, 633, 635, 639, 641, 645, 647, 651, 653, 657, 659, 663, 665, 669, 671, -1 ], name = "cs3", description = [ "CS3 convolutional code:", "G0 = 1 + D3 + D4", "G1 = 1 + D + D3 + D4", ] ), # TCH_AFS_12_2 definition ConvolutionalCode( 250, [ ( 1, 1 ), ( G1, G0 ), ], puncture = [ 321, 325, 329, 333, 337, 341, 345, 349, 353, 357, 361, 363, 365, 369, 373, 377, 379, 381, 385, 389, 393, 395, 397, 401, 405, 409, 411, 413, 417, 421, 425, 427, 429, 433, 437, 441, 443, 445, 449, 453, 457, 459, 461, 465, 469, 473, 475, 477, 481, 485, 489, 491, 493, 495, 497, 499, 501, 503, 505, 507, -1 ], name = 'tch_afs_12_2', description = [ "TCH/AFS 12.2 kbits 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 definition ConvolutionalCode( 210, [ ( G1, G3 ), ( G2, G3 ), ( 1, 1 ), ], puncture = [ 1, 4, 7, 10, 16, 19, 22, 28, 31, 34, 40, 43, 46, 52, 55, 58, 64, 67, 70, 76, 79, 82, 88, 91, 94, 100, 103, 106, 112, 115, 118, 124, 127, 130, 136, 139, 142, 148, 151, 154, 160, 163, 166, 172, 175, 178, 184, 187, 190, 196, 199, 202, 208, 211, 214, 220, 223, 226, 232, 235, 238, 244, 247, 250, 256, 259, 262, 268, 271, 274, 280, 283, 286, 292, 295, 298, 304, 307, 310, 316, 319, 322, 325, 328, 331, 334, 337, 340, 343, 346, 349, 352, 355, 358, 361, 364, 367, 370, 373, 376, 379, 382, 385, 388, 391, 394, 397, 400, 403, 406, 409, 412, 415, 418, 421, 424, 427, 430, 433, 436, 439, 442, 445, 448, 451, 454, 457, 460, 463, 466, 469, 472, 475, 478, 481, 484, 487, 490, 493, 496, 499, 502, 505, 508, 511, 514, 517, 520, 523, 526, 529, 532, 535, 538, 541, 544, 547, 550, 553, 556, 559, 562, 565, 568, 571, 574, 577, 580, 583, 586, 589, 592, 595, 598, 601, 604, 607, 609, 610, 613, 616, 619, 621, 622, 625, 627, 628, 631, 633, 634, 636, 637, 639, 640, -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 definition ConvolutionalCode( 165, [ ( 1, 1 ), ( G5, G4 ), ( G6, G4 ), ], puncture = [ 1, 2, 4, 5, 8, 22, 70, 118, 166, 214, 262, 310, 317, 319, 325, 332, 334, 341, 343, 349, 356, 358, 365, 367, 373, 380, 382, 385, 389, 391, 397, 404, 406, 409, 413, 415, 421, 428, 430, 433, 437, 439, 445, 452, 454, 457, 461, 463, 469, 476, 478, 481, 485, 487, 490, 493, 500, 502, 503, 505, 506, 508, 509, 511, 512, -1 ], 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 definition ConvolutionalCode( 154, [ ( G1, G3 ), ( G2, G3 ), ( 1, 1 ), ], puncture = [ 0, 355, 361, 367, 373, 379, 385, 391, 397, 403, 409, 415, 421, 427, 433, 439, 445, 451, 457, 460, 463, 466, 468, 469, 471, 472, -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 definition ConvolutionalCode( 140, [ ( G1, G3 ), ( G2, G3 ), ( 1, 1 ), ( 1, 1 ), ], puncture = [ 1, 3, 7, 11, 15, 27, 39, 55, 67, 79, 95, 107, 119, 135, 147, 159, 175, 187, 199, 215, 227, 239, 255, 267, 279, 287, 291, 295, 299, 303, 307, 311, 315, 319, 323, 327, 331, 335, 339, 343, 347, 351, 355, 359, 363, 367, 369, 371, 375, 377, 379, 383, 385, 387, 391, 393, 395, 399, 401, 403, 407, 409, 411, 415, 417, 419, 423, 425, 427, 431, 433, 435, 439, 441, 443, 447, 449, 451, 455, 457, 459, 463, 465, 467, 471, 473, 475, 479, 481, 483, 487, 489, 491, 495, 497, 499, 503, 505, 507, 511, 513, 515, 519, 521, 523, 527, 529, 531, 535, 537, 539, 543, 545, 547, 549, 551, 553, 555, 557, 559, 561, 563, 565, 567, 569, 571, 573, 575, -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 definition ConvolutionalCode( 124, [ ( G4, G6 ), ( G5, G6 ), ( 1, 1), ( 1, 1), ], puncture = [ 0, 1, 3, 5, 7, 11, 15, 31, 47, 63, 79, 95, 111, 127, 143, 159, 175, 191, 207, 223, 239, 255, 271, 287, 303, 319, 327, 331, 335, 343, 347, 351, 359, 363, 367, 375, 379, 383, 391, 395, 399, 407, 411, 415, 423, 427, 431, 439, 443, 447, 455, 459, 463, 467, 471, 475, 479, 483, 487, 491, 495, 499, 503, 507, 509, 511, 512, 513, 515, 516, 517, 519, -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 definition ConvolutionalCode( 109, [ ( G1, G3 ), ( G1, G3 ), ( G2, G3 ), ( 1, 1 ), ( 1, 1 ), ], puncture = [ 0, 4, 5, 9, 10, 14, 15, 20, 25, 30, 35, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, 300, 310, 315, 320, 325, 330, 334, 335, 340, 344, 345, 350, 354, 355, 360, 364, 365, 370, 374, 375, 380, 384, 385, 390, 394, 395, 400, 404, 405, 410, 414, 415, 420, 424, 425, 430, 434, 435, 440, 444, 445, 450, 454, 455, 460, 464, 465, 470, 474, 475, 480, 484, 485, 490, 494, 495, 500, 504, 505, 510, 514, 515, 520, 524, 525, 529, 530, 534, 535, 539, 540, 544, 545, 549, 550, 554, 555, 559, 560, 564, -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 definition ConvolutionalCode( 101, [ ( G4, G6 ), ( G4, G6 ), ( G5, G6 ), ( 1, 1 ), ( 1, 1 ), ], puncture = [ 0, 1, 2, 4, 5, 7, 9, 15, 25, 35, 45, 55, 65, 75, 85, 95, 105, 115, 125, 135, 145, 155, 165, 175, 185, 195, 205, 215, 225, 235, 245, 255, 265, 275, 285, 295, 305, 315, 325, 335, 345, 355, 365, 375, 385, 395, 400, 405, 410, 415, 420, 425, 430, 435, 440, 445, 450, 455, 459, 460, 465, 470, 475, 479, 480, 485, 490, 495, 499, 500, 505, 509, 510, 515, 517, 519, 520, 522, 524, 525, 526, 527, 529, 530, 531, 532, 534, -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", ] ), # TCH_FR definition ConvolutionalCode( 185, CCH_poly, name = "tch_fr", description = ["TCH/F convolutional code"] ), # TCH_HR definition ConvolutionalCode( 98, [ ( G4, 1 ), ( G5, 1 ), ( G6, 1 ), ], puncture = [ 1, 4, 7, 10, 13, 16, 19, 22, 25, 28, 31, 34, 37, 40, 43, 46, 49, 52, 55, 58, 61, 64, 67, 70, 73, 76, 79, 82, 85, 88, 91, 94, 97, 100, 103, 106, 109, 112, 115, 118, 121, 124, 127, 130, 133, 136, 139, 142, 145, 148, 151, 154, 157, 160, 163, 166, 169, 172, 175, 178, 181, 184, 187, 190, 193, 196, 199, 202, 205, 208, 211, 214, 217, 220, 223, 226, 229, 232, 235, 238, 241, 244, 247, 250, 253, 256, 259, 262, 265, 268, 271, 274, 277, 280, 283, 295, 298, 301, 304, 307, 310, -1, ], name = "tch_hr", description = ["TCH/H convolutional code"] ), # TCH_AHS_7_95 definition ConvolutionalCode( 129, [ ( 1, 1 ), ( G1, G0 ), ], puncture = [ 1, 3, 5, 7, 11, 15, 19, 23, 27, 31, 35, 43, 47, 51, 55, 59, 63, 67, 71, 79, 83, 87, 91, 95, 99, 103, 107, 115, 119, 123, 127, 131, 135, 139, 143, 151, 155, 159, 163, 167, 171, 175, 177, 179, 183, 185, 187, 191, 193, 195, 197, 199, 203, 205, 207, 211, 213, 215, 219, 221, 223, 227, 229, 231, 233, 235, 239, 241, 243, 247, 249, 251, 255, 257, 259, 261, 263, 265, -1, ], name = "tch_ahs_7_95", description = ["TCH/AHS 7.95 kbits convolutional code"] ), # TCH_AHS_7_4 definition ConvolutionalCode( 126, [ ( 1, 1 ), ( G1, G0 ), ], puncture = [ 1, 3, 7, 11, 19, 23, 27, 35, 39, 43, 51, 55, 59, 67, 71, 75, 83, 87, 91, 99, 103, 107, 115, 119, 123, 131, 135, 139, 143, 147, 151, 155, 159, 163, 167, 171, 175, 179, 183, 187, 191, 195, 199, 203, 207, 211, 215, 219, 221, 223, 227, 229, 231, 235, 237, 239, 243, 245, 247, 251, 253, 255, 257, 259, -1, ], name = "tch_ahs_7_4", description = ["TCH/AHS 7.4 kbits convolutional code"] ), # TCH_AHS_6_7 definition ConvolutionalCode( 116, [ ( 1, 1 ), ( G1, G0 ), ], puncture = [ 1, 3, 9, 19, 29, 39, 49, 59, 69, 79, 89, 99, 109, 119, 129, 139, 149, 159, 167, 169, 177, 179, 187, 189, 197, 199, 203, 207, 209, 213, 217, 219, 223, 227, 229, 231, 233, 235, 237, 239, -1, ], name = "tch_ahs_6_7", description = ["TCH/AHS 6.7 kbits convolutional code"] ), # TCH_AHS_5_9 definition ConvolutionalCode( 108, [ ( 1, 1 ), ( G1, G0 ), ], puncture = [ 1, 15, 71, 127, 139, 151, 163, 175, 187, 195, 203, 211, 215, 219, 221, 223, -1, ], name = "tch_ahs_5_9", description = ["TCH/AHS 5.9 kbits convolutional code"] ), # TCH_AHS_5_15 definition ConvolutionalCode( 97, [ ( G1, G3 ), ( G2, G3 ), ( 1, 1 ), ], puncture = [ 0, 1, 3, 4, 6, 9, 12, 15, 18, 21, 27, 33, 39, 45, 51, 54, 57, 63, 69, 75, 81, 87, 90, 93, 99, 105, 111, 117, 123, 126, 129, 135, 141, 147, 153, 159, 162, 165, 168, 171, 174, 177, 180, 183, 186, 189, 192, 195, 198, 201, 204, 207, 210, 213, 216, 219, 222, 225, 228, 231, 234, 237, 240, 243, 244, 246, 249, 252, 255, 256, 258, 261, 264, 267, 268, 270, 273, 276, 279, 280, 282, 285, 288, 289, 291, 294, 295, 297, 298, 300, 301, -1, ], name = "tch_ahs_5_15", description = ["TCH/AHS 5.15 kbits convolutional code"] ), # TCH_AHS_4_75 definition ConvolutionalCode( 89, [ ( 1, 1 ), ( G5, G4 ), ( G6, G4 ), ], puncture = [ 1, 2, 4, 5, 7, 8, 10, 13, 16, 22, 28, 34, 40, 46, 52, 58, 64, 70, 76, 82, 88, 94, 100, 106, 112, 118, 124, 130, 136, 142, 148, 151, 154, 160, 163, 166, 172, 175, 178, 184, 187, 190, 196, 199, 202, 208, 211, 214, 220, 223, 226, 232, 235, 238, 241, 244, 247, 250, 253, 256, 259, 262, 265, 268, 271, 274, 275, 277, 278, 280, 281, 283, 284, -1, ], name = "tch_ahs_4_75", description = ["TCH/AHS 4.75 kbits convolutional code"] ), # EDGE MCS1_DL_HDR definition ConvolutionalCode( 36, MCS_poly, name = "mcs1_dl_hdr", term_type = "CONV_TERM_TAIL_BITING", description = [ "EDGE MCS-1 DL header convolutional code:", "42 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS1_UL_HDR definition ConvolutionalCode( 39, MCS_poly, name = "mcs1_ul_hdr", term_type = "CONV_TERM_TAIL_BITING", description = [ "EDGE MCS-1 UL header convolutional code:", "45 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS1 definition ConvolutionalCode( 190, MCS_poly, name = "mcs1", description = [ "EDGE MCS-1 data convolutional code:", "196 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS2 definition ConvolutionalCode( 238, MCS_poly, name = "mcs2", description = [ "EDGE MCS-2 data convolutional code:", "244 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS3 definition ConvolutionalCode( 310, MCS_poly, name = "mcs3", description = [ "EDGE MCS-3 data convolutional code:", "316 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS4 definition ConvolutionalCode( 366, MCS_poly, name = "mcs4", description = [ "EDGE MCS-4 data convolutional code:", "372 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS5_DL_HDR definition ConvolutionalCode( 33, MCS_poly, name = "mcs5_dl_hdr", term_type = "CONV_TERM_TAIL_BITING", description = [ "EDGE MCS-5 DL header convolutional code:", "39 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS5_UL_HDR definition ConvolutionalCode( 45, MCS_poly, name = "mcs5_ul_hdr", term_type = "CONV_TERM_TAIL_BITING", description = [ "EDGE MCS-5 UL header convolutional code:", "51 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS5 definition ConvolutionalCode( 462, MCS_poly, name = "mcs5", description = [ "EDGE MCS-5 data convolutional code:", "468 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS6 definition ConvolutionalCode( 606, MCS_poly, name = "mcs6", description = [ "EDGE MCS-6 data convolutional code:", "612 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS7_DL_HDR definition ConvolutionalCode( 45, MCS_poly, name = "mcs7_dl_hdr", term_type = "CONV_TERM_TAIL_BITING", description = [ "EDGE MCS-7 DL header convolutional code:", "51 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS7_UL_HDR definition ConvolutionalCode( 54, MCS_poly, name = "mcs7_ul_hdr", term_type = "CONV_TERM_TAIL_BITING", description = [ "EDGE MCS-7 UL header convolutional code:", "60 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS7 definition ConvolutionalCode( 462, MCS_poly, name = "mcs7", description = [ "EDGE MCS-7 data convolutional code:", "468 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS8 definition ConvolutionalCode( 558, MCS_poly, name = "mcs8", description = [ "EDGE MCS-8 data convolutional code:", "564 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), # EDGE MCS9 definition ConvolutionalCode( 606, MCS_poly, name = "mcs9", description = [ "EDGE MCS-9 data convolutional code:", "612 bits blocks, rate 1/3, k = 7", "G4 = 1 + D2 + D3 + D5 + D6", "G7 = 1 + D + D2 + D3 + D6", "G5 = 1 + D + D4 + D6" ] ), ] if __name__ == '__main__': path = sys.argv[1] if len(sys.argv) > 1 else os.getcwd() prefix = "gsm0503" sys.stderr.write("Generating convolutional codes...\n") # Open a new file for writing f = open(os.path.join(path, "gsm0503_conv.c"), 'w') f.write(mod_license + "\n") f.write("#include \n") f.write("#include \n\n") # Generate the tables one by one for code in conv_codes: sys.stderr.write("Generate '%s' definition\n" % code.name) code.gen_tables(prefix, f) sys.stderr.write("Generation complete.\n")