# -*- coding: utf-8 -*- # # Modulation Error Rate # # http://www.opendigitalradio.org # Licence: The MIT License, see notice at the end of this file import datetime import os import logging try: logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename) except: logging_path = "/tmp/" import src.const import numpy as np import matplotlib matplotlib.use('agg') import matplotlib.pyplot as plt class MER: def __init__(self, c): self.c = c def _calc_spectrum(self, tx): fft = np.fft.fftshift(np.fft.fft(tx)) return np.delete(fft[self.c.FFT_start:self.c.FFT_end], self.c.FFT_delete) def _split_in_carrier(self, x, y): if 0.5 < np.mean((np.abs(np.abs(x) - np.abs(y)) / np.abs(np.abs(x) + np.abs(y)))): # Constellation points are axis aligned on the Im/Re plane x1 = x[(y < x) & (y > -x)] y1 = y[(y < x) & (y > -x)] x2 = x[(y > x) & (y > -x)] y2 = y[(y > x) & (y > -x)] x3 = x[(y > x) & (y < -x)] y3 = y[(y > x) & (y < -x)] x4 = x[(y < x) & (y < -x)] y4 = y[(y < x) & (y < -x)] else: # Constellation points are on the diagonal or Im/Re plane x1 = x[(+x > 0) & (+y > 0)] y1 = y[(+x > 0) & (+y > 0)] x2 = x[(-x > 0) & (+y > 0)] y2 = y[(-x > 0) & (+y > 0)] x3 = x[(-x > 0) & (-y > 0)] y3 = y[(-x > 0) & (-y > 0)] x4 = x[(+x > 0) & (-y > 0)] y4 = y[(+x > 0) & (-y > 0)] return (x1, y1), (x2, y2), (x3, y3), (x4, y4) def _calc_mer_for_isolated_constellation_point(self, x, y): """Calculate MER for one constellation point""" x_mean = np.mean(x) y_mean = np.mean(y) U_RMS = np.sqrt(x_mean ** 2 + y_mean ** 2) U_ERR = np.mean(np.sqrt((x - x_mean) ** 2 + (y - y_mean) ** 2)) MER = 20 * np.log10(U_ERR / U_RMS) return x_mean, y_mean, U_RMS, U_ERR, MER def calc_mer(self, tx, debug=False): assert tx.shape[0] == self.c.T_U,\ "Wrong input length" spectrum = self._calc_spectrum(tx) if debug: dt = datetime.datetime.now().isoformat() fig_path = logging_path + "/" + dt + "_MER.svg" MERs = [] for i, (x, y) in enumerate(self._split_in_carrier( np.real(spectrum), np.imag(spectrum))): x_mean, y_mean, U_RMS, U_ERR, MER =\ self._calc_mer_for_isolated_constellation_point(x, y) MERs.append(MER) tau = np.linspace(0, 2 * np.pi, num=100) x_err = U_ERR * np.sin(tau) + x_mean y_err = U_ERR * np.cos(tau) + y_mean if debug: ax = plt.subplot(221 + i) ax.scatter(x, y, s=0.2, color='black') ax.plot(x_mean, y_mean, 'p', color='red') ax.plot(x_err, y_err, linewidth=2, color='blue') ax.text(0.1, 0.1, "MER {:.1f}dB".format(MER), transform=ax.transAxes) ax.set_xlabel("Real") ax.set_ylabel("Imag") ylim = ax.get_ylim() ax.set_ylim(ylim[0] - (ylim[1] - ylim[0]) * 0.1, ylim[1]) if debug: plt.tight_layout() plt.savefig(fig_path) plt.show() plt.close() MER_res = 20 * np.log10(np.mean([10 ** (MER / 20) for MER in MERs])) return MER_res # The MIT License (MIT) # # Copyright (c) 2017 Andreas Steger # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE.