📄 noiser.py
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########################################################################## ######## noiser.py ######## ######## This file is part of the turbo decoder IP core project ######## http://www.opencores.org/projects/turbocodes/ ######## ######## Author(s): ######## - David Brochart(dbrochart@opencores.org) ######## ######## All additional information is available in the README.txt ######## file. ######## ############################################################################## ######## Copyright (C) 2005 Authors ######## ######## This source file may be used and distributed without ######## restriction provided that this copyright statement is not ######## removed from the file and that any derivative work contains ######## the original copyright notice and the associated disclaimer. ######## ######## This source file is free software; you can redistribute it ######## and/or modify it under the terms of the GNU Lesser General ######## Public License as published by the Free Software Foundation; ######## either version 2.1 of the License, or (at your option) any ######## later version. ######## ######## This source 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 Lesser General Public License for more ######## details. ######## ######## You should have received a copy of the GNU Lesser General ######## Public License along with this source; if not, download it ######## from http://www.opencores.org/lgpl.shtml ######## ##########################################################################from random import gaussfrom myhdl import Signal, posedge, negedgedef noiser(clk, rst, a, b, y1, y2, y1Int, y2Int, aNoisy, bNoisy, y1Noisy, y2Noisy, y1IntNoisy, y2IntNoisy, n = 4 , mu = 2**(4 - 1), sigma = 2**(4 - 2) + 2**(4 - 3)): """ Signal noiser (Gauss distribution). n -- number of bits for the coding of the noisy signals (= for the sampling of the received data) mu -- mean value for the distribution sigma -- standard deviation for the distribution (0 means no noise) clk, rst -- in : clock and negative reset a, b, y1, y2, y1Int, y2Int -- in : original coder signals, coded with 1 bit aNoisy, bNoisy, y1Noisy, y2Noisy, y1IntNoisy, y2IntNoisy -- out : noisy signals, coded with n bits and delayed by 1 clock cycle """ #mu = 2**(n - 1) #8 #sigma = 2**(n - 2) + 2**(n - 3) #6# cnt = Signal(int(0)) while 1: if rst.val == 0: aNoisy.next = 0 bNoisy.next = 0 y1Noisy.next = 0 y2Noisy.next = 0# cnt.next = 0 else:# if cnt.val < 10:# cnt.next = cnt.next + 1# aNoisy.next = ((a.val * 2) - 1) * 7# bNoisy.next = ((b.val * 2) - 1) * 7# y1Noisy.next = ((y1.val * 2) - 1) * 7# y2Noisy.next = ((y2.val * 2) - 1) * 7# y1IntNoisy.next = ((y1Int.val * 2) - 1) * 7# y2IntNoisy.next = ((y2Int.val * 2) - 1) * 7# else:# cnt.next = 0# aNoisy.next = 7# bNoisy.next = 7# y1Noisy.next = 7# y2Noisy.next = 7# y1IntNoisy.next = 7# y2IntNoisy.next = 7 if a.val == 0: aNoisy.next = int(round(gauss(-mu + 1, sigma))) else: aNoisy.next = int(round(gauss(mu - 1, sigma))) if b.val == 0: bNoisy.next = int(round(gauss(-mu + 1, sigma))) else: bNoisy.next = int(round(gauss(mu - 1, sigma))) if y1.val == 0: y1Noisy.next = int(round(gauss(-mu + 1, sigma))) else: y1Noisy.next = int(round(gauss(mu - 1, sigma))) if y2.val == 0: y2Noisy.next = int(round(gauss(-mu + 1, sigma))) else: y2Noisy.next = int(round(gauss(mu - 1, sigma))) if y1Int.val == 0: y1IntNoisy.next = int(round(gauss(-mu + 1, sigma))) else: y1IntNoisy.next = int(round(gauss(mu - 1, sigma))) if y2Int.val == 0: y2IntNoisy.next = int(round(gauss(-mu + 1, sigma))) else: y2IntNoisy.next = int(round(gauss(mu - 1, sigma))) yield posedge(clk), negedge(rst)⌨️ 快捷键说明
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