用100行Python进行OQAM_OFDM通感一体化波形设计

OQAM (Offset QAM) 和 OFDM (Orthogonal Frequency Division Multiplexing) 是用于现代无线通信系统中的关键技术，它们结合在一起通常用于高效的频谱利用率和抗多径衰落的能力。要在100行Python代码中实现这种融合的一体化波形设计，你需要涉及numpy库来进行矩阵运算、scipy库进行信号处理以及matplotlib绘制波形。以下是一个简化的示例，它不会包括所有细节，因为真正的实现可能会超过100行：

import numpy as np
from scipy.signal import chirp
import matplotlib.pyplot as plt

# 参数设置
NFFT = 1024
carrier_freq = 2e6
num_subcarriers = NFFT // 2 + 1
num_symbols = 1000
offset_factor = 0.5
qam_order = 4

# 创建OFDM信号
t = np.linspace(0, num_symbols * 1e-6, num_symbols)
data = np.random.randint(qam_order, size=num_symbols)

# OQAM变换
iq_data = data.astype(complex) * np.exp(1j * 2 * np.pi * carrier_freq * t)
oqam_data = np.zeros((num_subcarriers, num_symbols), dtype=complex)
for i in range(num_subcarriers):
    oqam_data[i::2, :] = iq_data[i::2] + offset_factor * iq_data[i+1::2]
    oqam_data[i+1::2, :] = -iq_data[i::2] + offset_factor * iq_data[i+1::2]

# IFFT生成OFDM信号
ofdm_signal = np.fft.ifft(oqam_data, axis=0)[:num_subcarriers].real

# 帧同步和窗口加窗
window = np.hanning(NFFT)
ofdm_windowed = ofdm_signal * window

# 可视化波形
plt.figure()
plt.plot(t, ofdm_windowed)
plt.xlabel('Time (s)')
plt.ylabel('Amplitude')
plt.title('OQAM-OFDM Waveform')
plt.show()