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Diffstat (limited to 'dpd/src/TX_Agc.py')
| -rw-r--r-- | dpd/src/TX_Agc.py | 131 |
1 files changed, 0 insertions, 131 deletions
diff --git a/dpd/src/TX_Agc.py b/dpd/src/TX_Agc.py deleted file mode 100644 index 309193d..0000000 --- a/dpd/src/TX_Agc.py +++ /dev/null @@ -1,131 +0,0 @@ -# -*- coding: utf-8 -*- -# -# DPD Computation Engine, Automatic Gain Control. -# -# http://www.opendigitalradio.org -# Licence: The MIT License, see notice at the end of this file - -import datetime -import os -import logging -import time -import numpy as np -import matplotlib - -matplotlib.use('agg') -import matplotlib.pyplot as plt - -import src.Adapt as Adapt - - -# TODO fix for float tx_gain -class TX_Agc: - def __init__(self, - adapt, - c): - """ - In order to avoid digital clipping, this class increases the - TX gain and reduces the digital gain. Digital clipping happens - when the digital analog converter receives values greater than - it's maximal output. This class solves that problem by adapting - the TX gain in a way that the peaks of the TX signal are in a - specified range. The TX gain is adapted accordingly. The TX peaks - are approximated by estimating it based on the signal median. - - :param adapt: Instance of Adapt Class to update - txgain and coefficients - :param max_txgain: limit for TX gain - :param tx_median_threshold_max: if the median of TX is larger - than this value, then the digital gain is reduced - :param tx_median_threshold_min: if the median of TX is smaller - than this value, then the digital gain is increased - :param tx_median_target: The digital gain is reduced in a way that - the median TX value is expected to be lower than this value. - """ - - assert isinstance(adapt, Adapt.Adapt) - self.adapt = adapt - self.max_txgain = c.TAGC_max_txgain - self.txgain = self.max_txgain - - self.tx_median_threshold_tolerate_max = c.TAGC_tx_median_max - self.tx_median_threshold_tolerate_min = c.TAGC_tx_median_min - self.tx_median_target = c.TAGC_tx_median_target - - def _calc_new_tx_gain(self, tx_median): - delta_db = 20 * np.log10(self.tx_median_target / tx_median) - new_txgain = self.adapt.get_txgain() - delta_db - assert new_txgain < self.max_txgain, \ - "TX_Agc failed. New TX gain of {} is too large.".format( - new_txgain - ) - return new_txgain, delta_db - - def _calc_digital_gain(self, delta_db): - digital_gain_factor = 10 ** (delta_db / 20.) - digital_gain = self.adapt.get_digital_gain() * digital_gain_factor - return digital_gain, digital_gain_factor - - def _set_tx_gain(self, new_txgain): - self.adapt.set_txgain(new_txgain) - txgain = self.adapt.get_txgain() - return txgain - - def _have_to_adapt(self, tx_median): - too_large = tx_median > self.tx_median_threshold_tolerate_max - too_small = tx_median < self.tx_median_threshold_tolerate_min - return too_large or too_small - - def adapt_if_necessary(self, tx): - tx_median = np.median(np.abs(tx)) - - if self._have_to_adapt(tx_median): - # Calculate new values - new_txgain, delta_db = self._calc_new_tx_gain(tx_median) - digital_gain, digital_gain_factor = \ - self._calc_digital_gain(delta_db) - - # Set new values. - # Avoid temorary increase of output power with correct order - if digital_gain_factor < 1: - self.adapt.set_digital_gain(digital_gain) - time.sleep(0.5) - txgain = self._set_tx_gain(new_txgain) - time.sleep(1) - else: - txgain = self._set_tx_gain(new_txgain) - time.sleep(1) - self.adapt.set_digital_gain(digital_gain) - time.sleep(0.5) - - logging.info( - "digital_gain = {}, txgain_new = {}, " \ - "delta_db = {}, tx_median {}, " \ - "digital_gain_factor = {}". - format(digital_gain, txgain, delta_db, - tx_median, digital_gain_factor)) - - return True - return False - -# 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. |