Experimental Study on ISAC Performance With Different Sensing Sequences

Integrated sensing and communication (ISAC) has been recognized as one of the key techniques for 6G, aiming at realizing smart sensing applications using wireless signals. However, existing investigations are limited to the algorithm design for smart sensing applications, and the parameters affecting sensing performance have not been thoroughly explored. To fill this gap, we study the impact of sensing sequences and communication parameters on the performance with real-world evaluations in this letter. Specifically, we develop a sensing platform based on USRP X310 and propose a novel packet detection algorithm as well as a time synchronization algorithm. Two typical applications, i.e., human pose recognition and dynamic gesture recognition, have been conducted under different sequences and communication parameters. The extensive results indicate that the sensing performance is identical across various sequences, and the relationship between the sensing performance and communication parameters is fully investigated.