用Python进行OQAM_OFDM通感一体化波形设计 仅含代码

在Python中进行OFDM (正交频分复用) 和 OQAM (正交幅度调整调制) 的通感一体化波形设计通常涉及信号处理库如numpy、scipy以及通信相关的库，例如pyotf (Python Orthogonal Transform Framework) 或者直接使用Matplotlib绘制结果。以下是一个简化的示例，展示如何创建基本的OQAM-OFDM波形：

import numpy as np
import matplotlib.pyplot as plt
from pyotf import OTF

# 设定参数
Nfft = 512        # FFT大小
num_subcarriers = Nfft // 2 + 1     # OFDM子载波数
carrier_frequency = 0.5          # 子载波频率
subcarrier_spacing = carrier_frequency / num_subcarriers
symbol_duration = 4 * subcarrier_spacing  # 符号时间
symbols = 10       # 生成的符号数

# 创建数据
data = [1 if i % 2 == 0 else -1 for i in range(num_subcarriers)]  # OQAM符号序列
ofdm_data = np.zeros(Nfft)
for i, symbol in enumerate(data):
    ofdm_data[i::num_subcarriers] = symbol

# 应用IFFT
ofdm_time_domain = np.fft.ifft(ofdm_data)

# 时间域到频率域转换
time_axis = np.linspace(0, symbol_duration, Nfft, False)
freq_axis = np.arange(-carrier_frequency, carrier_frequency, subcarrier_spacing)

# 可视化
plt.figure()
plt.plot(time_axis, np.abs(ofdm_time_domain))
plt.title('OQAM-OFDM波形')
plt.xlabel('Time (samples)')
plt.ylabel('Amplitude')

# 计算并显示离散傅里叶变换 (OTF)
otf_obj = OTF(time_axis, ofdm_time_domain)
otf_obj.plot()