Toward Integrated Sensing and Communication: Interference-Resistance Design for WiFi Sensing

Junmei Yao, Chaoyang Liu, Sheng Luo, Lu Wang, Tingting Zhang, Kaishun Wu

Abstract: WiFi has been widely used for local area networking of devices and Internet access in the past two decades. Many researchers exploit WiFi signals for target sensing through analyzing the Channel State Information (CSI) of signals affected by the target movement. With the development of 6G Integrated Sensing and Communication (ISAC), some researchers further consider using communication data packets for WiFi sensing. However, all the current works do not analyze the impact of ubiquitous interference on WiFi sensing performance. In this paper, we propose IRSensing, an interference-resistance design to improve the CSI quality under interference in the ISAC scenario, aiming to improve the WiFi sensing performance. IRSensing exploits the overall WiFi packet for CSI optimization. It first measures the interference level of each subcarrier based on variance analysis, then proposes a CSI optimization method based on maximal ratio combining to improve the CSI quality. It finally proposes a practical CSI enhancement process to adapt to complex interference situations in actual networks. We implement IRSensing on a hardware testbed and evaluate its performance under different settings. Experiment results show that it can significantly decrease the activity detection error rate by up to 80% and improve the classification accuracy by up to 15$\%$.