# -*- coding:utf-8 -*-   import numpy as np   from math import pi   import matplotlib.pyplot as plt   import matplotlib   import scipy.signal as signal   import math       #碼元數   size = 10   sampling_t = 0.01   t = np.arange(0, size, sampling_t)       # 隨機生成訊號序列   a = np.random.randint(0, 2, size)   m = np.zeros(len(t), dtype=np.float32)   for i in range(len(t)):       m[i] = a[math.floor(t[i])]   fig = plt.figure()   ax1 = fig.add_subplot(3, 1, 1)       # 解決set_title中文亂碼   zhfont1 = matplotlib.font_manager.FontProperties(fname = 'C:\Windows\Fonts\simsun.ttc')   ax1.set_title('產生隨機n位二進位制訊號', fontproperties = zhfont1, fontsize = 20)   plt.axis([0, size, -0.5, 1.5])   plt.plot(t, m, 'b')       fc = 4000   fs = 20 * fc # 取樣頻率   ts = np.arange(0, (100 * size) / fs, 1 / fs)   coherent_carrier = np.cos(np.dot(2 * pi * fc, ts))       bpsk = np.cos(np.dot(2 * pi * fc, ts) + pi * (m - 1) + pi / 4)       # BPSK調製訊號波形   ax2 = fig.add_subplot(3, 1, 2)   ax2.set_title('BPSK調製訊號', fontproperties=zhfont1, fontsize=20)   plt.axis([0,size,-1.5, 1.5])   plt.plot(t, bpsk, 'r')           # 定義加性高斯白噪聲   def awgn(y, snr):       snr = 10 ** (snr / 10.0)       xpower = np.sum(y ** 2) / len(y)       npower = xpower / snr       return np.random.randn(len(y)) * np.sqrt(npower) + y       # 加AWGN噪聲   noise_bpsk = awgn(bpsk, 5)       # BPSK調製訊號疊加噪聲波形   ax3 = fig.add_subplot(3, 1, 3)   ax3.set_title('BPSK調製訊號疊加噪聲波形', fontproperties = zhfont1, fontsize = 20)   plt.axis([0, size, -1.5, 1.5])   plt.plot(t, noise_bpsk, 'r')           # 帶通橢圓濾波器設計，通帶為[2000，6000]   [b11,a11] = signal.ellip(5, 0.5, 60, [2000 * 2 / 80000, 6000 * 2 / 80000], btype = 'bandpass', analog = False, output = 'ba')       # 低通濾波器設計，通帶截止頻率為2000Hz   [b12,a12] = signal.ellip(5, 0.5, 60, (2000 * 2 / 80000), btype = 'lowpass', analog = False, output = 'ba')       # 通過帶通濾波器濾除帶外噪聲   bandpass_out = signal.filtfilt(b11, a11, noise_bpsk)       # 相干解調,乘以同頻同相的相干載波   coherent_demod = bandpass_out * (coherent_carrier * 2)       # 通過低通濾波器   lowpass_out = signal.filtfilt(b12, a12, coherent_demod)   fig2 = plt.figure()   bx1 = fig2.add_subplot(3, 1, 1)   bx1.set_title('本地載波下變頻，經低通濾波器後', fontproperties = zhfont1, fontsize=20)   plt.axis([0, size, -1.5, 1.5])   plt.plot(t, lowpass_out, 'r')       #抽樣判決   detection_bpsk = np.zeros(len(t), dtype=np.float32)   flag = np.zeros(size, dtype=np.float32)       for i in range(10):       tempF = 0       for j in range(100):           tempF = tempF + lowpass_out[i * 100 + j]       if tempF > 0:           flag[i] = 1       else:           flag[i] = 0   for i in range(size):       if flag[i] == 0:           for j in range(100):               detection_bpsk[i * 100 + j] = 0       else:           for j in range(100):               detection_bpsk[i * 100 + j] = 1       bx2 = fig2.add_subplot(3, 1, 2)   bx2.set_title('BPSK訊號抽樣判決後的訊號', fontproperties = zhfont1, fontsize=20)   plt.axis([0, size, -0.5, 1.5])   plt.plot(t, detection_bpsk, 'r')   plt.show()