A Communication Protocol Identification Method Based on Time-Frequency Domain Combination for Internet of Things

At present, Internet of Things (IoT) testing instruments and meters are unable to identify the communication protocol of communication data when all characteristic parameters of communication data are unknown. Regarding this problem, this paper utilizes the K-Nearest Neighbors (KNN) model in machine learning, designs communication protocol identification methods and proposes a communication protocol identification method based on time-frequency domain combination (CPI- TFC). First, we generate time-domain waveforms and frequency-domain waveforms from sampling communication data sequences, and attempt only time-domain identification method and only frequency-domain identification method based on KNN model. Then, we compare the results, design a communication protocol identification method based on the combination of time-domain identification and frequency domain identification, and propose CPI-TFC. Experimental results show that CPI-TFC can achieve higher identification accuracy than only time-domain identification method and only frequency-domain identification method, so it can effectively identify the communication protocol for a IoT communication data. Moreover, CPI- TFC can provide prior information for subsequent configuring parameters in IoT testing instruments, improve the parameter configuration efficiency.

I. Introduction

The 6th Generation (6G) Internet of Things (IoT), as an important component of the new generation of information infrastructure, plays a crucial role in promoting the development of national economy, society, culture, and defense [1]. It empowers and enhances numerous industries, facilitating their transformation towards networked, informatized, and intelligent. This also promotes the development of advanced manufacturing and drives the structural adjustment and upgrading of manufacturing industry. However, in 6G IoT, multiple standards coexist, such as cellular communication and short-range communication, multiple application scenarios coexist, such as internet of vehicles, industrial IoT and WLAN, this situation presents significant challenges for IoT testing instruments and meters. In addition, the diverse ways of IoT device access also increase the difficulty of IoT device RF testing.