diff options
Diffstat (limited to 'dpd')
| -rwxr-xr-x | dpd/main.py | 21 | ||||
| -rw-r--r-- | dpd/src/Agc.py | 6 | ||||
| -rw-r--r-- | dpd/src/TX_Agc.py | 17 | ||||
| -rw-r--r-- | dpd/src/const.py | 10 |
4 files changed, 28 insertions, 26 deletions
diff --git a/dpd/main.py b/dpd/main.py index 923a7f8..8de0f86 100755 --- a/dpd/main.py +++ b/dpd/main.py @@ -145,10 +145,10 @@ elif dpddata[0] == "lut": else: logging.error("Unknown dpd data format {}".format(dpddata[0])) -tx_agc = TX_Agc.TX_Agc(adapt) +tx_agc = TX_Agc.TX_Agc(adapt, c) # Automatic Gain Control -agc = Agc.Agc(meas, adapt) +agc = Agc.Agc(meas, adapt, c) agc.run() state = "measure" @@ -165,7 +165,7 @@ while i < num_iter: tx, rx, phase_diff, n_per_bin = extStat.extract(txframe_aligned, rxframe_aligned) - if extStat.n_meas >= 15: + if extStat.n_meas >= 200: state = "model" else: state = "measure" @@ -181,11 +181,11 @@ while i < num_iter: elif state == "adapt": adapt.set_predistorter(dpddata) state = "report" - i += 1 # Report elif state == "report": try: + i += 1 path = adapt.dump() off = SA.calc_offset(txframe_aligned) @@ -196,12 +196,12 @@ while i < num_iter: rx_gain = adapt.get_rxgain() digital_gain = adapt.get_digital_gain() tx_median = np.median(np.abs(txframe_aligned)) - rx_shoulders = MS.average_shoulders(rxframe_aligned) - tx_shoulders = MS.average_shoulders(txframe_aligned) + rx_shoulder_tuple = MS.average_shoulders(rxframe_aligned) + tx_shoulder_tuple = MS.average_shoulders(txframe_aligned) logging.info(list((name, eval(name)) for name in - ['i', 'tx_mer', 'tx_shoulders', 'rx_mer', - 'rx_shoulders', 'mse', 'tx_gain', + ['i', 'tx_mer', 'tx_shoulder_tuple', 'rx_mer', + 'rx_shoulder_tuple', 'mse', 'tx_gain', 'digital_gain', 'rx_gain', 'rx_median', 'tx_median'])) if dpddata[0] == "poly": @@ -216,11 +216,6 @@ while i < num_iter: lut = dpddata[2] logging.info("It {}: LUT scalefactor {}, LUT {}". format(i, scalefactor, lut)) - - model.reset_coefs() - dpd_data = model.get_dpd_data() - adapt.set_predistorter(dpd_data) - tx_gain = tx_gain - 1 if tx_gain < 89: adapt.set_txgain(tx_gain) else: diff --git a/dpd/src/Agc.py b/dpd/src/Agc.py index b83c91e..670fbbb 100644 --- a/dpd/src/Agc.py +++ b/dpd/src/Agc.py @@ -35,14 +35,14 @@ class Agc: received signal fulfills our desired property, of having all amplitudes properly quantized.""" - def __init__(self, measure, adapt, min_rxgain=25, peak_to_median=20): + def __init__(self, measure, adapt, c): assert isinstance(measure, Measure.Measure) assert isinstance(adapt, Adapt.Adapt) self.measure = measure self.adapt = adapt - self.min_rxgain = min_rxgain + self.min_rxgain = c.RAGC_min_rxgain self.rxgain = self.min_rxgain - self.peak_to_median = peak_to_median + self.peak_to_median = 1./c.RAGC_rx_median_target def run(self): self.adapt.set_rxgain(self.rxgain) diff --git a/dpd/src/TX_Agc.py b/dpd/src/TX_Agc.py index affc42f..b9226b2 100644 --- a/dpd/src/TX_Agc.py +++ b/dpd/src/TX_Agc.py @@ -24,10 +24,7 @@ import src.Adapt as Adapt class TX_Agc: def __init__(self, adapt, - max_txgain=89, - tx_median_target=0.16, - tx_median_threshold_max=0.18, - tx_median_threshold_min=0.14): + c): """ In order to avoid digital clipping, this class increases the TX gain and reduces the digital gain. Digital clipping happens @@ -47,16 +44,16 @@ class TX_Agc: :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 = max_txgain + self.max_txgain = c.TAGC_max_txgain self.txgain = self.max_txgain - assert tx_median_threshold_max > tx_median_target,\ - "The tolerated tx_median has to be larger then the goal tx_median" - self.tx_median_threshold_tolerate_max = tx_median_threshold_max - self.tx_median_threshold_tolerate_min = tx_median_threshold_min - self.tx_median_target = tx_median_target + 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 adapt_if_necessary(self, tx): tx_median = np.median(np.abs(tx)) diff --git a/dpd/src/const.py b/dpd/src/const.py index c7f4b7c..63a095b 100644 --- a/dpd/src/const.py +++ b/dpd/src/const.py @@ -43,6 +43,16 @@ class const: self.ES_n_bins = 64 self.ES_n_per_bin = 128 + # Constants for TX_Agc + self.TAGC_max_txgain = 89 + self.TAGC_tx_median_target = 0.1 + self.TAGC_tx_median_max = self.TAGC_tx_median_target*1.4 + self.TAGC_tx_median_min = self.TAGC_tx_median_target/1.4 + + # Constants for Agc + self.RAGC_min_rxgain = 25 + self.RAGC_rx_median_target = self.TAGC_tx_median_target + # Constants for Model_PM self.MPM_tx_min = 0.1 |