Towards Mutual Benefit Between Sensing and Communication: Transceiver Design and Performance Analysis
Integrated sensing and communication (ISAC) is envisioned as a key technology for 6 G networks. Most prior works achieve one-sided performance gain on either sensing or communication functionality by compromising the performance of the other. In this paper, the transceiver design and performance analysis are investigated to achieve mutual benefit between sensing and communication (S&C) functions in ISAC systems. We consider two types of user equipment (UE): the active UE (A-UE) actively communicates with the base station and the inactive UE (I-UE) stays silent. Both the A-UE and I-UE need to be sensed by the ISAC base station. To achieve the mutual performance gain, an ISAC transceiver is designed by exploiting the correlated S&C channel information within the received signals from multiple sources. Specifically, the sensing information extracted from communication channel state information and received echo signals is fused to enhance A-UE angle estimation and I-UE detection. In addition, the enhanced angle estimation is further utilized to improve communication beamforming accuracy. To quantify the mutual benefit gain, we first obtain the closed-form expression for the optimal I-UE detection probability and the A-UE estimation rate. Based on the angle estimation accuracy, the ergodic communication rate is derived and the asymptotic characteristic is further studied in the regime of a large transmit antenna number. Our results demonstrate that the proposed scheme not only achieves simultaneous enhancement in both S&C performance, but also significantly outperforms existing approaches in terms of ISAC performance metrics, such as sensing accuracy, detection probability, and communication rate.
Authors
- Lei Chao-yang
- Manlin Wang (ORCID: https://orcid.org/0000-0002-7526-4567)
- Yinghong Guo (ORCID: https://orcid.org/0000-0002-5772-8612)
- Bin Xia (ORCID: https://orcid.org/0000-0003-4713-5765)
- Yixiao Gu (ORCID: https://orcid.org/0000-0002-5868-8130)
Institutions
- Shanghai University (CN)
- Shanghai Jiao Tong University (CN)
- China Telecom (China) (CN)
Publication Details
- Journal
- IEEE Transactions on Vehicular Technology
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tvt.2025.3618664
- Primary Topic
- Distributed Sensor Networks and Detection Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00