diff options
Diffstat (limited to 'dpd/src/Model.py')
| -rw-r--r-- | dpd/src/Model.py | 189 |
1 files changed, 118 insertions, 71 deletions
diff --git a/dpd/src/Model.py b/dpd/src/Model.py index 8df3925..b962140 100644 --- a/dpd/src/Model.py +++ b/dpd/src/Model.py @@ -16,42 +16,86 @@ class Model: """Calculates new coefficients using the measurement and the old coefficients""" - def __init__(self, coefs): - self.coefs = coefs - self.coefs_history = [coefs,] - self.mses = [0,] - self.errs = [0,] + def __init__(self, coefs_am, coefs_pm): + self.coefs_am = coefs_am + self.coefs_history = [coefs_am, ] + self.mses = [0, ] + self.errs = [0, ] + + self.coefs_pm = coefs_pm + self.coefs_pm_history = [coefs_pm, ] + self.errs_phase = [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") + + # Calculate new coefficients for AM/AM correction 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_abs ** 3, + rx_abs ** 5, + rx_abs ** 7, + rx_abs ** 9, + ]).T + rx_dpd = np.sum(rx_A * self.coefs_am, 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))) + 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]) + new_coefs = self.coefs_am - 0.1 * a_delta + new_coefs = new_coefs * (self.coefs_am[0] / new_coefs[0]) + logging.debug("a_delta {}".format(a_delta)) + logging.debug("new coefs_am {}".format(new_coefs)) + + # Calculate new coefficients for AM/PM correction + phase_diff_rad = (( + (np.angle(txframe_aligned) - + np.angle(rxframe_aligned) + + np.pi) % (2 * np.pi)) - + np.pi + ) + + tx_abs = np.abs(txframe_aligned) + tx_abs_A = np.vstack([tx_abs, + tx_abs ** 2, + tx_abs ** 3, + tx_abs ** 4, + tx_abs ** 5, + ]).T + phase_dpd = np.sum(tx_abs_A * self.coefs_pm, axis=1) + + err_phase = phase_dpd - phase_diff_rad + self.errs_phase.append(np.mean(np.abs(err_phase ** 2))) + a_delta = np.linalg.lstsq(tx_abs_A, err_phase)[0] + new_coefs_pm = self.coefs_pm - 0.1 * a_delta logging.debug("a_delta {}".format(a_delta)) - logging.debug("new coefs {}".format(new_coefs)) + logging.debug("new new_coefs_pm {}".format(new_coefs_pm)) + + def dpd_phase(tx): + tx_abs = np.abs(tx) + tx_A_complex = np.vstack([tx, + tx * tx_abs ** 1, + tx * tx_abs ** 2, + tx * tx_abs ** 3, + tx * tx_abs ** 4, + ]).T + tx_dpd = np.sum(tx_A_complex * self.coefs_pm, axis=1) + return tx_dpd + + tx_range = np.linspace(0, 2) + phase_range_dpd = dpd_phase(tx_range) tx_abs = np.abs(rxframe_aligned) tx_A = np.vstack([tx_abs, - tx_abs**3, - tx_abs**5, - tx_abs**7, - tx_abs**9, + tx_abs ** 3, + tx_abs ** 5, + tx_abs ** 7, + tx_abs ** 9, ]).T tx_dpd = np.sum(tx_A * new_coefs, axis=1) @@ -59,34 +103,34 @@ class Model: 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) + 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_am, 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)) + 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) + 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_am, 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)) - ) + + rx_range = np.linspace(0, 1, num=100) + rx_range_dpd = dpd(rx_range) + rx_range = rx_range[(rx_range_dpd > 0) & (rx_range_dpd < 2)] + rx_range_dpd = rx_range_dpd[(rx_range_dpd > 0) & (rx_range_dpd < 2)] if logging.getLogger().getEffectiveLevel() == logging.DEBUG: logging.debug("txframe: min %f, max %f, median %f" % @@ -104,15 +148,12 @@ class Model: dt = datetime.datetime.now().isoformat() fig_path = logging_path + "/" + dt + "_Model.pdf" - fig, axs = plt.subplots(7, figsize=(6,3*6)) + fig, axs = plt.subplots(8, figsize=(6, 4 * 6)) ax = axs[0] 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") @@ -125,9 +166,6 @@ class Model: 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") @@ -140,44 +178,40 @@ class Model: ax.scatter( np.abs(txframe_aligned[:1024]), np.abs(rxframe_aligned[:1024]), - s = 0.1) + s=0.1) + ax.plot(rx_range_dpd / self.coefs_am[0], rx_range, linewidth=0.25) ax.set_title("Amplifier Characteristic") ax.set_xlabel("TX Amplitude") ax.set_ylabel("RX Amplitude") ax = axs[3] - angle_diff_rad = (( - (np.angle(txframe_aligned[:1024]) - - np.angle(rxframe_aligned[:1024]) + - np.pi) % (2 * np.pi)) - - np.pi - ) ax.scatter( np.abs(txframe_aligned[:1024]), - angle_diff_rad * 180 / np.pi, - s = 0.1 + phase_diff_rad[:1024] * 180 / np.pi, + s=0.1 ) + ax.plot(tx_range, phase_range_dpd * 180 / np.pi, linewidth=0.25) ax.set_title("Amplifier Characteristic") 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) + label="TX Frame", + linestyle=":", + linewidth=0.5) ax.plot(np.abs(rxframe_aligned[:128]), - label="RX Frame", - linestyle="--", - linewidth=0.5) + label="RX Frame", + linestyle="--", + linewidth=0.5) ax.plot(np.abs(rx_dpd[:128]), - label="RX DPD Frame", - linestyle="-.", - linewidth=0.5) + 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) + label="TX DPD Frame Norm", + linestyle="-.", + linewidth=0.5) ax.legend(loc=4) ax.set_title("RX DPD") ax.set_xlabel("Samples") @@ -187,14 +221,25 @@ class Model: 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) + label="Coef {}".format(idx), + linewidth=0.5) ax.legend(loc=4) - ax.set_title("Coefficient History") + ax.set_title("AM/AM Coefficient History") ax.set_xlabel("Iterations") ax.set_ylabel("Coefficient Value") ax = axs[6] + coefs_history = np.array(self.coefs_pm_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("AM/PM Coefficient History") + ax.set_xlabel("Iterations") + ax.set_ylabel("Coefficient Value") + + ax = axs[7] coefs_history = np.array(self.coefs_history) ax.plot(self.mses, label="MSE") ax.plot(self.errs, label="ERR") @@ -207,9 +252,11 @@ class Model: fig.savefig(fig_path) fig.clf() - self.coefs = new_coefs - self.coefs_history.append(self.coefs) - return self.coefs + self.coefs_am = new_coefs + self.coefs_history.append(self.coefs_am) + self.coefs_pm = new_coefs_pm + self.coefs_pm_history.append(self.coefs_pm) + return self.coefs_am, self.coefs_pm # The MIT License (MIT) # |