自行完成：4-PSK、16-PSK仿真，并与8-PSK比较；或者，完成2FSK/2ASK仿真。

我可以为您提供一个基于Python的4-PSK和16-PSK仿真代码示例。请注意，由于缺乏具体的系统参数，此代码仅用于演示目的，您需要根据自己的系统参数进行修改。

import numpy as np
import matplotlib.pyplot as plt

# 调制信号
def modulate(bits, M):
    if M == 4:
        symbols = np.array([1+1j, 1-1j, -1+1j, -1-1j]) / np.sqrt(2)
    elif M == 16:
        symbols = np.array([
            1+1j, 1+3j, 3+1j, 3+3j,
            1-1j, 1-3j, 3-1j, 3-3j,
            -1+1j, -1+3j, -3+1j, -3+3j,
            -1-1j, -1-3j, -3-1j, -3-3j
        ]) / np.sqrt(10)
    else:
        raise ValueError("M must be 4 or 16")
    
    N = len(bits)
    k = int(np.log2(M))
    symbols_per_bit = int(N / k)
    bits = bits[:symbols_per_bit*k]
    bits = np.reshape(bits, (symbols_per_bit, k))
    bits = np.packbits(bits, axis=1)
    symbols = symbols[bits]
    return symbols.flatten()

# 高斯白噪声
def awgn(signal, SNR_dB):
    L = len(signal)
    SNR = 10**(SNR_dB/10.0)
    signal_power = np.sum(np.abs(signal)**2) / L
    noise_power = signal_power / SNR
    noise = np.sqrt(noise_power/2) * (np.random.randn(L) + 1j*np.random.randn(L))
    return signal + noise

# 误码率
def ber(bits_tx, bits_rx):
    return np.sum(bits_tx != bits_rx) / len(bits_tx)

# 模拟
M = 4
SNR_dB = 10
k = int(np.log2(M))
bits_tx = np.random.randint(0, 2, 10000*k)
symbols_tx = modulate(bits_tx, M)
symbols_rx = awgn(symbols_tx, SNR_dB)
bits_rx = np.unpackbits(np.array(np.round((symbols_rx.real + 2) / 2), dtype=np.uint8))
bits_rx = bits_rx[-len(bits_tx):]
print("M: %d, SNR: %d dB, BER: %.2e" % (M, SNR_dB, ber(bits_tx, bits_rx)))

M = 16
SNR_dB = 10
k = int(np.log2(M))
bits_tx = np.random.randint(0, 2, 10000*k)
symbols_tx = modulate(bits_tx, M)
symbols_rx = awgn(symbols_tx, SNR_dB)
bits_rx = np.unpackbits(np.array(np.round((symbols_rx.real + 2) / 2), dtype=np.uint8))
bits_rx = bits_rx[-len(bits_tx):]
print("M: %d, SNR: %d dB, BER: %.2e" % (M, SNR_dB, ber(bits_tx, bits_rx)))

M = 8
SNR_dB = 10
k = int(np.log2(M))
bits_tx = np.random.randint(0, 2, 10000*k)
symbols_tx = modulate(bits_tx, M)
symbols_rx = awgn(symbols_tx, SNR_dB)
bits_rx = np.unpackbits(np.array(np.round((symbols_rx.real + 2) / 2), dtype=np.uint8))
bits_rx = bits_rx[-len(bits_tx):]
print("M: %d, SNR: %d dB, BER: %.2e" % (M, SNR_dB, ber(bits_tx, bits_rx)))

您可以通过更改M和SNR_dB的值，以及添加其他的系统参数，来进行不同条件下的仿真。