def papr_Calc(datain):
power = datain.real**2 + datain.imag**2
##papr = 10 * math.log((np.max(power) / np.mean(power)),10)
power = np.sort(power)
papr = 10 * math.log(
(power[int(len(power) * 0.9999)] / np.mean(power)), 10) ##0.00001 PAPR
return papr
bbIQ0, sr0 = bb.baseband_Gen("64QAM", 20, 1)
bbIQ1, sr1 = bb.baseband_Gen("64QAM", 20, 1)
bbIQ_20M_0, sr0 = fb.firbranch_DL(bbIQ0, sr0)
bbIQ_20M_1, sr1 = fb.firbranch_DL(bbIQ1, sr1)
bbIQ_2x20M_20, sr3 = duc.duc([bbIQ_20M_0, bbIQ_20M_1], [-20000000, 20000000],
sr0)
plt.figure(0)
bb.PSD_Disp(bbIQ_2x20M_20, sr3)
papr_40 = papr_Calc(bbIQ_2x20M_20)
papr_20_0 = papr_Calc(bbIQ_20M_0)
papr_20_1 = papr_Calc(bbIQ_20M_1)
power = bbIQ_2x20M_20.real**2 + bbIQ_2x20M_20.imag**2
thrsh = np.mean(power) * math.pow(10, 0.75)
plt.figure(1)
plt.plot(power)
plt.axhline(thrsh, color='r')
# plt.show()
#
bbIQ0,sr0 = bb.baseband_Gen("64QAM",10,1)
bbIQ1,sr1 = bb.baseband_Gen("64QAM",20,1)
bbIQ_122_10M,sr0 = fb.firbranch_DL(bbIQ0,sr0)
bbIQ_122_20M,sr1 = fb.firbranch_DL(bbIQ1,sr1)
bbIQ_245_20M,sr2 = fb.upsampling_2x(bbIQ_122_20M,sr1)
bbIQ_122_2x10M_5,sr3 = duc.duc([bbIQ_122_10M,bbIQ_122_10M],[-5000000,5000000],sr0)
bbIQ_122_2x10M_25,sr4 = duc.duc([bbIQ_122_10M,bbIQ_122_10M],[-25000000,25000000],sr0)
bbIQ_122_2x20M_20,sr5 = duc.duc([bbIQ_122_20M,bbIQ_122_20M],[-20000000,20000000],sr0)
plt.figure(0)
bb.PSD_Disp(bbIQ_122_10M,sr0)
bb.PSD_Disp(bbIQ_122_20M,sr1)
bb.PSD_Disp(bbIQ_122_2x10M_5,sr3)
bb.PSD_Disp(bbIQ_122_2x10M_25,sr4)
bb.PSD_Disp(bbIQ_122_2x20M_20,sr5)
skewR_122_10M = calc_SkewR(bbIQ_122_10M)
skewR_122_20M = calc_SkewR(bbIQ_122_20M)
skewR_245_20M = calc_SkewR(bbIQ_245_20M)
skewR_122_2x10M_5 = calc_SkewR(bbIQ_122_2x10M_5)
skewR_122_2x10M_25 = calc_SkewR(bbIQ_122_2x10M_25)
skewR_122_2x20M_20 = calc_SkewR(bbIQ_122_2x20M_20)
disp_SkewRCDF([skewR_122_10M,skewR_122_20M,skewR_122_2x10M_5,skewR_122_2x10M_25,skewR_122_2x20M_20])
data_interp = np.zeros([len(datain) * 2], dtype=complex)
data_interp[0::2] = datain
dataout = signal.convolve(hbcoef, data_interp)
dataout = dataout[len(hbcoef) - 1:]
return dataout, sr * 2
#%%
'''
Downlink filter branch
Input: data IQ
Output: 122.88Msps data IQ
'''
def firbranch_DL(datain, sr):
bbIQ = channelfir(datain)
while int(122880000 / sr) != 1:
bbIQ, sr = upsampling_2x(bbIQ, sr)
return bbIQ, int(sr)
#%%
if __name__ == '__main__':
(bbIQ, sr) = baseband.baseband_Gen("16QAM", 10, 1)
# bbIQf = channelfir(bbIQ)
# bbIQ2x,sr = upsampling_2x(bbIQf,sr)
# bbIQ122,sr = upsampling_2x(bbIQ2x,sr)
bbIQ122, sr = firbranch_DL(bbIQ, sr)
baseband.PSD_Disp(bbIQ122, sr)
Output: (duc IQ out, sample rate)
Note: NCO unit is Hz
'''
def duc(bbIQ_list, NCO_list, fs):
dataout = np.zeros([len(bbIQ_list[0])], dtype=complex)
# idx = 0
for idx in range(len(bbIQ_list)):
# frq_shift = np.zeros([len(bbIQ)],dtype=complex)
frq_shift = np.exp(1j * 2 * cmath.pi * (NCO_list[idx] / fs) *
np.arange(len(bbIQ_list[idx])))
# for k in range(0,len(bbIQ)):
# frq_shift[k] = cmath.exp(1j*2*cmath.pi*(NCO_list[idx]/fs)*k)
dataout = dataout + bbIQ_list[idx] * frq_shift
# idx = idx + 1
return dataout, fs
#%%
if __name__ == '__main__':
bbIQ, sr = bb.baseband_Gen("64QAM", 20, 1)
bbIQf = fb.channelfir(bbIQ)
bbIQ2x, sr = fb.upsampling_2x(bbIQf, sr)
bbIQ4x, sr = fb.upsampling_2x(bbIQ2x, sr)
bbduc, sr = duc([bbIQ4x, bbIQ4x, bbIQ4x], [-20000000, 0, 20000000], sr)
bb.PSD_Disp(bbduc, sr)
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 31 16:49:41 2018
@author: exabefa
"""
import math
import duc
import baseband as bb
import filterbranch as fb
import numpy as np
import matplotlib.pyplot as plt
bbIQ0,sr0 = bb.baseband_Gen("64QAM",20,1)
plt.figure(0)
bb.PSD_Disp(bbIQ0,sr0)
power = bbIQ0.real **2 + bbIQ0.imag **2
power = np.sort(power)
b = len(power)
a = int(len(power)*0.9999)
r = power[a]
papr = 10 * math.log((r / np.mean(power)),10)
papr1 = 10 * math.log((power[int(len(power)*0.9999)] / np.mean(power)),10)