stbc-ofdm代码
时间: 2023-07-09 16:42:24 浏览: 57
好的,下面给你提供一个简单的STBC-OFDM代码做参考:
```python
import numpy as np
import matplotlib.pyplot as plt
# OFDM参数设置
N = 64 # 子载波数
cp_len = 16 # 循环前缀长度
pilot_freq = 8 # 导频间隔
pilot_symbol = np.array([1, -1, 1, 1]) # 导频序列
data_len = 48 # 数据长度
data_symbol = np.random.randint(0, 2, data_len) * 2 - 1 # 随机生成BPSK调制数据
mod_order = 2 # 调制阶数,2表示BPSK
EbN0_dB = 30 # 信噪比,单位dB
# STBC编码参数
Nt = 2 # 天线数
code_rate = 1 # 编码速率,1表示ALAMOUTI编码,0.5表示Space-Time Block Coding
if code_rate == 1:
T = np.array([[1, 1j], [1j, -1]]) / np.sqrt(2)
else:
T = np.array([[1, 0], [0, 1j]])
# 生成OFDM符号
if mod_order == 2:
data_mod = data_symbol
else:
raise NotImplementedError("此处只实现了BPSK调制")
data_mod_reshape = data_mod.reshape((-1, N))
data_mod_stbc = np.zeros((data_mod_reshape.shape[0], Nt, N), dtype=np.complex)
data_mod_stbc[:, 0, :] = data_mod_reshape.dot(T[0, :])
data_mod_stbc[:, 1, :] = data_mod_reshape.dot(T[1, :])
data_ofdm = np.zeros((data_mod_reshape.shape[0], Nt, N), dtype=np.complex)
for i in range(data_mod_reshape.shape[0]):
for j in range(Nt):
data_ofdm[i, j, :] = np.fft.ifft(data_mod_stbc[i, j, :], N)
data_ofdm[i, :, 0:cp_len] = data_ofdm[i, :, -cp_len:]
data_ofdm[i, 1, 0:cp_len] = 0
data_ofdm = data_ofdm.reshape(-1, Nt * N)
pilot = np.zeros((data_ofdm.shape[0],), dtype=np.complex)
pilot[::pilot_freq] = pilot_symbol
tx_signal = np.concatenate([pilot[:, np.newaxis], data_ofdm], axis=1)
# 加噪声
Es = np.sum(np.abs(tx_signal) ** 2, axis=1) / (tx_signal.shape[1])
Eb = Es / np.log2(mod_order)
N0 = Eb / 10 ** (EbN0_dB / 10)
noise = np.random.randn(*tx_signal.shape) * np.sqrt(N0 / 2) + 1j * np.random.randn(*tx_signal.shape) * np.sqrt(N0 / 2)
rx_signal = tx_signal + noise
# 接收端处理
rx_signal = rx_signal.reshape(-1, Nt, N)
rx_symbol = np.zeros((rx_signal.shape[0], N), dtype=np.complex)
for i in range(rx_signal.shape[0]):
for j in range(N):
h_ij = np.array([[np.random.randn(), np.random.randn()], [np.random.randn(), np.random.randn()]]) / np.sqrt(2)
rx_symbol[i, j] = rx_signal[i, :, j].dot(h_ij).dot(np.linalg.inv(T))
rx_symbol[i, 0:pilot_freq:pilot_freq+1] = 0 # 去掉导频
rx_symbol = rx_symbol.reshape(-1)
rx_data = np.zeros((rx_symbol.shape[0],), dtype=np.int8)
rx_data[rx_symbol > 0] = 1
# 计算误码率
err_num = np.sum(rx_data != data_mod)
print("误码率:", err_num / data_mod.shape[0])
# 绘制调制后的信号和接收信号的频谱
fig, ax = plt.subplots(2, 1, figsize=(6, 6))
ax[0].plot(tx_signal[0, :].real)
ax[0].plot(tx_signal[0, :].imag)
ax[0].set_title("Transmitted Signal")
ax[1].plot(np.fft.fftshift(np.abs(np.fft.fft(tx_signal[0, :]))))
ax[1].set_title("Transmitted Spectrum")
fig.tight_layout()
fig, ax = plt.subplots(2, 1, figsize=(6, 6))
ax[0].plot(rx_signal[0, :, :].real.T)
ax[0].plot(rx_signal[0, :, :].imag.T)
ax[0].set_title("Received Signal")
ax[1].plot(np.fft.fftshift(np.abs(np.fft.fft(rx_signal[0, :, :].reshape(-1)))))
ax[1].set_title("Received Spectrum")
fig.tight_layout()
plt.show()
```
这段代码实现了一个基于ALAMOUTI编码的STBC-OFDM系统,包含随机生成BPSK数据、STBC编码、OFDM调制、加噪声、接收端处理、误码率计算和绘制调制后的信号和接收信号的频谱等步骤。你可以根据自己的需要进行修改和扩展。
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