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-rwxr-xr-xdpd/main.py17
-rw-r--r--dpd/poly_am.coef8
-rw-r--r--dpd/poly_pm.coef10
-rw-r--r--dpd/src/Dab_Util.py17
-rw-r--r--dpd/src/Model.py153
-rw-r--r--dpd/src/phase_align.py9
-rwxr-xr-xdpd/src/subsample_align.py11
-rw-r--r--src/MemlessPoly.cpp5
8 files changed, 185 insertions, 45 deletions
diff --git a/dpd/main.py b/dpd/main.py
index 560d142..4d2b93d 100755
--- a/dpd/main.py
+++ b/dpd/main.py
@@ -10,10 +10,16 @@
This engine calculates and updates the parameter of the digital
predistortion module of ODR-DabMod."""
+import datetime
+import os
+
import logging
+dt = datetime.datetime.now().isoformat()
+logging_path = "/tmp/dpd_{}".format(dt).replace(".","_").replace(":","-")
+os.makedirs(logging_path)
logging.basicConfig(format='%(asctime)s - %(module)s - %(levelname)s - %(message)s',
datefmt='%Y-%m-%d %H:%M:%S',
- filename='/tmp/dpd.log',
+ filename='{}/dpd.log'.format(logging_path),
filemode='w',
level=logging.DEBUG)
@@ -32,7 +38,7 @@ parser.add_argument('--rc-port', default='9400',
parser.add_argument('--samplerate', default='8192000',
help='Sample rate',
required=False)
-parser.add_argument('--coefs', default='dpdpoly.coef',
+parser.add_argument('--coefs', default='poly.coef',
help='File with DPD coefficients, which will be read by ODR-DabMod',
required=False)
parser.add_argument('--samps', default='10240',
@@ -52,8 +58,9 @@ meas = Measure.Measure(samplerate, port, num_req)
adapt = Adapt.Adapt(port_rc, coef_path)
coefs = adapt.get_coefs()
#model = Model.Model(coefs)
-model = Model.Model([0.8, 0, 0, 0, 0])
-adapt.set_txgain(60)
+model = Model.Model([2.2, 0, 0, 0, 0])
+adapt.set_txgain(79)
+adapt.set_rxgain(15+20)
tx_gain = adapt.get_txgain()
rx_gain = adapt.get_rxgain()
@@ -64,7 +71,7 @@ logging.info(
)
)
-for i in range(10):
+for i in range(500):
txframe_aligned, tx_ts, rxframe_aligned, rx_ts = meas.get_samples()
logging.debug("tx_ts {}, rx_ts {}".format(tx_ts, rx_ts))
coefs = model.get_next_coefs(txframe_aligned, rxframe_aligned)
diff --git a/dpd/poly_am.coef b/dpd/poly_am.coef
index ce11551..ff09e5a 100644
--- a/dpd/poly_am.coef
+++ b/dpd/poly_am.coef
@@ -1,6 +1,6 @@
5
2.2
-2.34402815751
--25.0487363081
-93.1884045291
--85.3795993469
+1.16110192544
+-13.7895532562
+55.107515965
+-53.8583673922
diff --git a/dpd/poly_pm.coef b/dpd/poly_pm.coef
index 2a5bf1c..ae91b12 100644
--- a/dpd/poly_pm.coef
+++ b/dpd/poly_pm.coef
@@ -1,6 +1,6 @@
5
-0.126147521763
--0.507247679586
-0.645526051204
--0.313225683513
-0.0522039980935
+0.141477421551
+-0.654864288614
+1.00568534673
+-0.588530075442
+0.0935391293974
diff --git a/dpd/src/Dab_Util.py b/dpd/src/Dab_Util.py
index 1f88ae4..175b744 100644
--- a/dpd/src/Dab_Util.py
+++ b/dpd/src/Dab_Util.py
@@ -1,15 +1,18 @@
# -*- coding: utf-8 -*-
+import datetime
+import os
+import logging
+logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
+
import numpy as np
import scipy
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
-import datetime
import src.subsample_align as sa
import src.phase_align as pa
from scipy import signal
-import logging
class Dab_Util:
"""Collection of methods that can be applied to an array
@@ -35,7 +38,7 @@ class Dab_Util:
if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
dt = datetime.datetime.now().isoformat()
- corr_path = ("/tmp/" + dt + "_tx_rx_corr.pdf")
+ corr_path = (logging_path + "/" + dt + "_tx_rx_corr.pdf")
plt.plot(c, label="corr")
plt.legend()
plt.savefig(corr_path)
@@ -89,7 +92,7 @@ class Dab_Util:
if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
dt = datetime.datetime.now().isoformat()
- fig_path = "/tmp/" + dt + "_sync_raw.pdf"
+ fig_path = logging_path + "/" + dt + "_sync_raw.pdf"
fig, axs = plt.subplots(2)
axs[0].plot(np.abs(sig1[:128]), label="TX Frame")
@@ -127,7 +130,7 @@ class Dab_Util:
if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
dt = datetime.datetime.now().isoformat()
- fig_path = "/tmp/" + dt + "_sync_sample_aligned.pdf"
+ fig_path = logging_path + "/" + dt + "_sync_sample_aligned.pdf"
fig, axs = plt.subplots(2)
axs[0].plot(np.abs(sig1[:128]), label="TX Frame")
@@ -152,7 +155,7 @@ class Dab_Util:
if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
dt = datetime.datetime.now().isoformat()
- fig_path = "/tmp/" + dt + "_sync_subsample_aligned.pdf"
+ fig_path = logging_path + "/" + dt + "_sync_subsample_aligned.pdf"
fig, axs = plt.subplots(2)
axs[0].plot(np.abs(sig1[:128]), label="TX Frame")
@@ -176,7 +179,7 @@ class Dab_Util:
if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
dt = datetime.datetime.now().isoformat()
- fig_path = "/tmp/" + dt + "_sync_phase_aligned.pdf"
+ fig_path = logging_path + "/" + dt + "_sync_phase_aligned.pdf"
fig, axs = plt.subplots(2)
axs[0].plot(np.abs(sig1[:128]), label="TX Frame")
diff --git a/dpd/src/Model.py b/dpd/src/Model.py
index f66ba8f..8df3925 100644
--- a/dpd/src/Model.py
+++ b/dpd/src/Model.py
@@ -1,11 +1,16 @@
# -*- coding: utf-8 -*-
-import numpy as np
import datetime
+import os
import logging
+logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
+
+from pynverse import inversefunc
+import numpy as np
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
+from sklearn.linear_model import Ridge
class Model:
"""Calculates new coefficients using the measurement and the old
@@ -13,8 +18,76 @@ class Model:
def __init__(self, coefs):
self.coefs = coefs
+ self.coefs_history = [coefs,]
+ self.mses = [0,]
+ self.errs = [0,]
def get_next_coefs(self, txframe_aligned, rxframe_aligned):
+ dt = datetime.datetime.now().isoformat()
+ txframe_aligned.tofile(logging_path + "/txframe_" + dt + ".iq")
+ rxframe_aligned.tofile(logging_path + "/rxframe_" + dt + ".iq")
+ rx_abs = np.abs(rxframe_aligned)
+ rx_A = np.vstack([rx_abs,
+ rx_abs**3,
+ rx_abs**5,
+ rx_abs**7,
+ rx_abs**9,
+ ]).T
+ rx_dpd = np.sum(rx_A * self.coefs, axis=1)
+ rx_dpd = rx_dpd * (
+ np.median(np.abs(txframe_aligned)) / np.median(np.abs(rx_dpd)))
+
+ err = rx_dpd - np.abs(txframe_aligned)
+ self.errs.append(np.mean(np.abs(err**2)))
+
+ a_delta = np.linalg.lstsq(rx_A, err)[0]
+ new_coefs = self.coefs - 0.1 * a_delta
+ new_coefs = new_coefs * (self.coefs[0] / new_coefs[0])
+ logging.debug("a_delta {}".format(a_delta))
+ logging.debug("new coefs {}".format(new_coefs))
+
+ tx_abs = np.abs(rxframe_aligned)
+ tx_A = np.vstack([tx_abs,
+ tx_abs**3,
+ tx_abs**5,
+ tx_abs**7,
+ tx_abs**9,
+ ]).T
+ tx_dpd = np.sum(tx_A * new_coefs, axis=1)
+
+ tx_dpd_norm = tx_dpd * (
+ np.median(np.abs(txframe_aligned)) / np.median(np.abs(tx_dpd)))
+
+ rx_A_complex = np.vstack([rxframe_aligned,
+ rxframe_aligned * rx_abs**2,
+ rxframe_aligned * rx_abs**4,
+ rxframe_aligned * rx_abs**6,
+ rxframe_aligned * rx_abs**8,
+ ]).T
+ rx_post_distored = np.sum(rx_A_complex * self.coefs, axis=1)
+ rx_post_distored = rx_post_distored * (
+ np.median(np.abs(txframe_aligned)) /
+ np.median(np.abs(rx_post_distored)))
+ mse = np.mean(np.abs((txframe_aligned - rx_post_distored)**2))
+ logging.debug("MSE: {}".format(mse))
+ self.mses.append(mse)
+
+ def dpd(tx):
+ tx_abs = np.abs(tx)
+ tx_A_complex = np.vstack([tx,
+ tx * tx_abs**2,
+ tx * tx_abs**4,
+ tx * tx_abs**6,
+ tx * tx_abs**8,
+ ]).T
+ tx_dpd = np.sum(tx_A_complex * self.coefs, axis=1)
+ return tx_dpd
+ tx_inverse_dpd = inversefunc(dpd, y_values=txframe_aligned[:128])
+ tx_inverse_dpd = tx_inverse_dpd * (
+ np.median(np.abs(txframe_aligned)) /
+ np.median(np.abs(tx_inverse_dpd))
+ )
+
if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
logging.debug("txframe: min %f, max %f, median %f" %
(np.min(np.abs(txframe_aligned)),
@@ -29,21 +102,35 @@ class Model:
))
dt = datetime.datetime.now().isoformat()
- fig_path = "/tmp/" + dt + "_Model.pdf"
+ fig_path = logging_path + "/" + dt + "_Model.pdf"
- fig, axs = plt.subplots(4, figsize=(6,2*6))
+ fig, axs = plt.subplots(7, figsize=(6,3*6))
ax = axs[0]
- ax.plot(np.abs(txframe_aligned[:128]), label="TX Frame")
- ax.plot(np.abs(rxframe_aligned[:128]), label="RX Frame")
- ax.set_title("Synchronized Signals")
+ ax.plot(np.abs(txframe_aligned[:128]),
+ label="TX sent",
+ linestyle=":")
+ ax.plot(np.abs(tx_inverse_dpd[:128]),
+ label="TX inverse dpd",
+ color="green")
+ ax.plot(np.abs(rxframe_aligned[:128]),
+ label="RX received",
+ color="red")
+ ax.set_title("Synchronized Signals of Iteration {}".format(len(self.coefs_history)))
ax.set_xlabel("Samples")
ax.set_ylabel("Amplitude")
ax.legend(loc=4)
ax = axs[1]
- ax.plot(np.real(txframe_aligned[:128]), label="TX Frame")
- ax.plot(np.real(rxframe_aligned[:128]), label="RX Frame")
+ ax.plot(np.real(txframe_aligned[:128]),
+ label="TX sent",
+ linestyle=":")
+ ax.plot(np.real(tx_inverse_dpd[:128]),
+ label="TX inverse dpd",
+ color="green")
+ ax.plot(np.real(rxframe_aligned[:128]),
+ label="RX received",
+ color="red")
ax.set_title("Synchronized Signals")
ax.set_xlabel("Samples")
ax.set_ylabel("Real Part")
@@ -53,8 +140,7 @@ class Model:
ax.scatter(
np.abs(txframe_aligned[:1024]),
np.abs(rxframe_aligned[:1024]),
- s = 0.1
- )
+ s = 0.1)
ax.set_title("Amplifier Characteristic")
ax.set_xlabel("TX Amplitude")
ax.set_ylabel("RX Amplitude")
@@ -75,13 +161,54 @@ class Model:
ax.set_xlabel("TX Amplitude")
ax.set_ylabel("Phase Difference [deg]")
+ ax = axs[4]
+ ax.plot(np.abs(txframe_aligned[:128]),
+ label="TX Frame",
+ linestyle=":",
+ linewidth=0.5)
+ ax.plot(np.abs(rxframe_aligned[:128]),
+ label="RX Frame",
+ linestyle="--",
+ linewidth=0.5)
+ ax.plot(np.abs(rx_dpd[:128]),
+ label="RX DPD Frame",
+ linestyle="-.",
+ linewidth=0.5)
+ ax.plot(np.abs(tx_dpd_norm[:128]),
+ label="TX DPD Frame Norm",
+ linestyle="-.",
+ linewidth=0.5)
+ ax.legend(loc=4)
+ ax.set_title("RX DPD")
+ ax.set_xlabel("Samples")
+ ax.set_ylabel("Amplitude")
+
+ ax = axs[5]
+ coefs_history = np.array(self.coefs_history)
+ for idx, coef_hist in enumerate(coefs_history.T):
+ ax.plot(coef_hist,
+ label="Coef {}".format(idx),
+ linewidth=0.5)
+ ax.legend(loc=4)
+ ax.set_title("Coefficient History")
+ ax.set_xlabel("Iterations")
+ ax.set_ylabel("Coefficient Value")
+
+ ax = axs[6]
+ coefs_history = np.array(self.coefs_history)
+ ax.plot(self.mses, label="MSE")
+ ax.plot(self.errs, label="ERR")
+ ax.legend(loc=4)
+ ax.set_title("MSE History")
+ ax.set_xlabel("Iterations")
+ ax.set_ylabel("MSE")
+
fig.tight_layout()
fig.savefig(fig_path)
fig.clf()
- mse = np.mean(np.abs(np.square(txframe_aligned[:1024] - rxframe_aligned[:1024])))
- logging.debug("MSE: {}".format(mse))
-
+ self.coefs = new_coefs
+ self.coefs_history.append(self.coefs)
return self.coefs
# The MIT License (MIT)
diff --git a/dpd/src/phase_align.py b/dpd/src/phase_align.py
index bea0b82..f03184b 100644
--- a/dpd/src/phase_align.py
+++ b/dpd/src/phase_align.py
@@ -1,9 +1,12 @@
+import datetime
+import os
+import logging
+logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
+
import numpy as np
from scipy import signal, optimize
import sys
import matplotlib.pyplot as plt
-import datetime
-import logging
def phase_align(sig, ref_sig):
@@ -19,7 +22,7 @@ def phase_align(sig, ref_sig):
if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
dt = datetime.datetime.now().isoformat()
- fig_path = "/tmp/" + dt + "_phase_align.pdf"
+ fig_path = logging_path + "/" + dt + "_phase_align.pdf"
plt.subplot(511)
plt.hist(angle_diff, bins=60, label="Angle Diff")
diff --git a/dpd/src/subsample_align.py b/dpd/src/subsample_align.py
index 0dc78c1..0a51593 100755
--- a/dpd/src/subsample_align.py
+++ b/dpd/src/subsample_align.py
@@ -1,8 +1,11 @@
+import datetime
+import os
+import logging
+logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
+
import numpy as np
from scipy import signal, optimize
-import sys
import matplotlib.pyplot as plt
-import datetime
def gen_omega(length):
if (length % 2) == 1:
@@ -59,15 +62,13 @@ def subsample_align(sig, ref_sig):
if optim_result.success:
best_tau = optim_result.x
- #print("Found subsample delay = {}".format(best_tau))
-
if 1:
corr = np.vectorize(correlate_for_delay)
ixs = np.linspace(-1, 1, 100)
taus = corr(ixs)
dt = datetime.datetime.now().isoformat()
- tau_path = ("/tmp/" + dt + "_tau.pdf")
+ tau_path = (logging_path + "/" + dt + "_tau.pdf")
plt.plot(ixs, taus)
plt.title("Subsample correlation, minimum is best: {}".format(best_tau))
plt.savefig(tau_path)
diff --git a/src/MemlessPoly.cpp b/src/MemlessPoly.cpp
index d665839..e103b73 100644
--- a/src/MemlessPoly.cpp
+++ b/src/MemlessPoly.cpp
@@ -175,7 +175,6 @@ void MemlessPoly::load_coefficients_pm(const std::string &coefFile_pm)
/* The restrict keyword is C99, g++ and clang++ however support __restrict
* instead, and this allows the compiler to auto-vectorize the loop.
*/
-
static void apply_coeff(
const vector<float> &coefs_am,
const vector<float> &coefs_pm,
@@ -191,14 +190,14 @@ static void apply_coeff(
( coefs_am[1] + in_mag_sq *
( coefs_am[2] + in_mag_sq *
( coefs_am[3] + in_mag_sq *
- ( coefs_am[4] + in_mag_sq )))));
+ coefs_am[4]))));
float phase_correction = -1 *
( coefs_pm[0] + in_mag_sq *
( coefs_pm[1] + in_mag_sq *
( coefs_pm[2] + in_mag_sq *
( coefs_pm[3] + in_mag_sq *
- ( coefs_pm[4] + in_mag_sq )))));
+ coefs_pm[4]))));
float phase_correction_sq = phase_correction * phase_correction;
generated by cgit v1.2.3 (git 2.39.1) at 2024-09-21 10:52:46 +0000