def pll_pn_power_est2(tf,
tf_params,
pn_dco,
pn_dco_df,
m,
n,
kdco,
fclk,
fmax,
points=1025):
freqs = np.linspace(0, fmax - fmax / points, points)
fbin = fmax / points
g = tf(freqs, **tf_params)
ndco = min_ro_pn(fclk * n, freqs, pn_dco, pn_dco_df) * np.abs(1 - g)**2
ndco[np.where(g == 1)] = 0
# ntdc = tdc_pn(fclk, n, g, 1/float(m*fclk))
ntdc = tdc_pn(fclk, n, m, g)
return np.sum(2 * (ndco + ntdc)) * fbin
FINE_IDEAL = np.round((FOSC - FL_DCO - MED_IDEAL * KDCO2) / KDCO1)
LF_IDEAL = MED_IDEAL * 2**(DCO_FINE_BITS) + FINE_IDEAL
MED_INIT = np.floor((FOSC - FL_DCO + INIT_F_ERR) / KDCO2)
FINE_INIT = np.round((FOSC - FL_DCO + INIT_F_ERR - MED_INIT * KDCO2) / KDCO1)
LF_INIT = MED_INIT * 2**(DCO_FINE_BITS) + FINE_INIT
print("* LF_MAX = %d" % (2**(DCO_FINE_BITS + DCO_MED_BITS) - 1))
print("* LF_IDEAL = %d" % LF_IDEAL)
print("* LF_INIT = %d" % LF_INIT)
#\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\
# Determine DCO phase noise
if USE_THEOR_DCO_PN:
DCO_PN = min_ro_pn(FOSC, DCO_PN_DF, DCO_POWER, TEMP)
DCO_FOM = 10 * np.log10(DCO_PN * FOSC**2 * DCO_POWER * 1e3 / DCO_PN_DF**2)
else:
DCO_PN = fom_to_pn(DCO_FOM, DCO_POWER, FOSC, DCO_PN_DF)
print("\nOscillator characteristics:")
print("\tFOM = %.1F dB" % DCO_FOM)
print("\tPower = %.1f uW" % (DCO_POWER * 1e6))
print("\tTEMP = %.1f K" % TEMP)
print("\tL(df=%.2E) = %.2f dBc/Hz" % (DCO_PN_DF, 10 * np.log10(DCO_PN)))
KB = 1.38064852e-23
KRW = rw_gain_fom(fom_db=DCO_FOM, fosc=FOSC, power=DCO_POWER, fs=FS)
print("\tkrw = %.2E" % KRW)
# initial design
import numpy as np
import matplotlib.pyplot as plt
from libpll.filter import *
from libpll.plot import plot_loop_filter, plot_dco_pn, plot_tdc_pn, plot_total_pn, plot_fd
from libpll.plot import plot_pn_ssb2, plot_pll_tf_step
from libpll.pncalc import min_ro_pn, make_pn_sig
from libpll.analysis import meas_inband_power, snr, est_tsettle_pll_tf
from libradio.modpsd import gmsk_psd
from libradio.transforms import mix
""" Plot phase noise for filter optimizer to match second order filter in closed loop PLL
Note: Settling time is very non-optimal!
"""
pn_dco_df = 1e6
pn_dco = min_ro_pn(f0=2.4e9, df=pn_dco_df, power=50e-6, temp=293)
fn = 1e5
damping = 0.707
k = 3e10
d = 0.707
tf = opt_pll_tf_so_type2(fn, d)
tf = lf_from_pll_tf(tf, 64, 150, 1e4, 16e6)
DF_INITIAL = 5e6
DF_SETTLED = 5e4
print("Tsettle estimate=%E" % est_tsettle_pll_tf(tf, DF_SETTLED / DF_INITIAL))
plt.subplot(1, 2, 1)
plot_loop_filter(pn_dco=pn_dco, pn_dco_df=pn_dco_df, **tf)
plt.subplot(1, 2, 2)
plot_pll_tf_step(tf, tmax=2e-4)
plt.show()
