Wireless Channel Scenario Recognition Based on Neural Networks

Wireless channel scenario recognition plays a key role in improving the performance of mobile communication systems. This paper combines wireless channel characteristics extracted using expert experience and neural networks, and proposes a wireless channel scenario recognition framework based on neural networks. Firstly, the wireless propagation environment is analyzed, and some wireless channel characteristics are extracted, such as the frequency domain fading factor, multipath power delay distribution, time domain energy peak response ratio and time correlation characteristics. Secondly, the combined algorithm model using the wireless channel characteristics and neural networks are proposed. Finally, after simulation verification, the new method has a greater improvement in the recognition accuracy than the traditional threshold algorithm.