Enabling Indoor Multi-Person Tracking With 6G mmWave ISAC Systems

Integrated sensing and communication (ISAC) has emerged as a key technology for 6G wireless networks. In this paper, wireless sensing for the indoor multi-person tracking is explored with 6G mmWave ISAC systems. To limit the sensing overhead, a sparse deployment of sensing reference signals (RS) is applied in the orthogonal frequency-division multiplexing (OFDM) frame, where the channel state information (CSI) at the sensing RS is extracted for the multi-person tracking. To enable a robust tracking of multiple persons in a complex indoor environment, three key mechanisms are proposed: 1) a modified moving target indicator (MTI) scheme is proposed to remove the static environmental clutter under a sparse RS time spacing; 2) an effective target identification mechanism is developed to exclude false target points; 3) the Kalman filter with a penalty association algorithm is designed to associate the detected points with the right tracks, especially handling the crossover case of two tracks. With the above mechanisms, multiple persons can be effectively tracked with an extremely low sensing overhead. An mmWave bistatic ISAC prototype system at 26 GHz with 500 MHz bandwidth has been developed to validate our design, where the overhead of the sensing RS is less than 0.005\%. Experimental results demonstrate that our proposed design achieves a median position error of 12 cm for multi-person tracking with path-crossing in the indoor environment with a single receiver.

Experiment Study on Reference-Path-Aided System Calibration for mmWave Bistatic ISAC Systems

Integrated sensing and communications (ISAC) has been regarded as a key enabling technology for next-generation wireless networks. Compared to monostatic ISAC, bistatic ISAC can eliminate the critical challenge of self-interference cancellation and is well compatible with the existing network infrastructures. However, the synchronization between the transmitter and the sensing receiver becomes a crucial problem. The extracted channel state information (CSI) for sensing under communication synchronization contains different types of system errors, such as the sampling time offset (STO), carrier frequency offset (CFO), and random phase shift, which can severely degrade sensing performance or even render sensing infeasible. To address this problem, a reference-path-aided system calibration scheme is designed for mmWave bistatic ISAC systems, where the line-of-sight (LoS) path can be blocked. By exploiting the delay-angle sparsity feature in mmWave ISAC systems, the reference path, which can be either a LoS or a non-LoS (NLoS) path, is first identified. By leveraging the fact that all the paths suffer the same system errors, the channel parameter extracted from the reference path is utilized to compensate for the system errors in all other paths. A mmWave ISAC system is developed to validate our design. Experimental results demonstrate that the proposed scheme can support precise estimation of Doppler shift and delay, maintaining time-synchronization errors within 1 nanosecond.