Performance Analysis of Integrated Sensing and Backscatter Communication for Multi-User NOMA
Integrating sensing and communication (ISAC) capabilities into wireless networks is a transformative strategy for advancing future technologies. Backscatter communication, leveraging its ultra-low power and passive transmission characteristics, is particularly suited for future wireless systems addressing the challenges of energy constraints in Internet of Things and 6G environments. This paper proposes a novel non-orthogonal multiple access (NOMA)-based backscatter ISAC system. The system features a full-duplex base station (BS) that employs NOMA to serve K NOMA users while leveraging a backscatter tag to enhance communication and sensing functionalities. The backscatter tag reflects the BS’s transmitted signals, enabling it to transmit its data back to the BS while simultaneously improving the performance of the NOMA users. The BS, in turn, extracts environmental information from the same reflected signals. Outage probability expressions are derived for both communication and sensing tasks, considering different backscatter setups, namely parasitic and commensal. Moreover, to gain deeper insights, asymptotic outage and system throughput are also obtained to evaluate the system performance. Furthermore, the impact of different system parameters on the outage is investigated, and valuable insights are drawn.
Authors
- Shubham Bisen (ORCID: https://orcid.org/0000-0002-2651-6641)
- Ondřej Krejcar (ORCID: https://orcid.org/0000-0002-5992-2574)
- Vimal Bhatia (ORCID: https://orcid.org/0000-0001-5148-6643)
- Brejesh Lall (ORCID: https://orcid.org/0000-0003-2677-3071)
Institutions
- Soochow University (CN)
- Indian Institute of Technology Delhi (IN)
- University of Hradec Králové (CZ)
Publication Details
- Journal
- IEEE Wireless Communications Letters
- Published
- 2025-08-28
- DOI
- https://doi.org/10.1109/lwc.2025.3603912
- Citations
- 1
- Primary Topic
- Advanced Wireless Communication Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.73