Fundamental Performance Limits of Non-Coherent ISAC: A Data-Aided Sensing Perspective
For researchers designing ISAC systems, this work provides fundamental performance limits and quantifies the advantage of using data symbols for sensing, which is an incremental but rigorous theoretical contribution.
This paper characterizes the communication rate-sensing distortion trade-off for a bistatic MIMO ISAC system with unknown CSI, showing that data-aided sensing (DAS) achieves a strict 3 dB effective SNR gain in the low-SNR regime and a faster scaling rate in the high-SNR limit compared to pilot sensing (PS).
In this paper, we investigate a bistatic multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system over block-fading channels, focusing on the scenario where the sensing and communication receivers (Rxs) are co-located. Under the assumption of unknown channel state information (CSI) at the Rx, two schemes are considered: pilot sensing (PS) and data-aided sensing (DAS). The communication rate-sensing distortion functions for both schemes are characterized. For the DAS scheme, a closed-form asymptotic expression for the sensing distortion is derived by using random matrix theory (RMT). The asymptotic performance analysis explicitly quantifies the significant gains of the DAS scheme, revealing a strict $3$ dB effective SNR improvement in the low-SNR regime and a strictly faster performance scaling rate in the high-SNR limit compared to the PS scheme.