Wi-Fi frame detection via spiking neural networks with memristive synapses

摘要: With increasing performance of deep learning, researchers have employed Deep Neural Networks (DNNs) for wireless communications. In particular, mechanisms for detecting Wi-Fi frames that use DNNs demonstrate their excellent performances in terms of detection accuracy. However, DNNs require significant amount of computation resources. Thus, if the DNN-based mechanisms are used in mobile devices or low-end devices, their battery would be quickly depleted. Spiking Neural Networks (SNNs), which are regarded as the next generation of neural network, have advantages over DNNs: low energy consumption and limited computational complexity. Motivated by these advantages, in this paper, we propose a mechanism to detect a Wi-Fi frame using SNNs and show the feasibility of SNNs for Wi-Fi detection. The mechanism is composed of a preprocessing module for converting collected signals and an …