Joint Beamforming and Power Allocation Strategy for NOMA Empowered ISAC Systems
The emerging integrated sensing and communication paradigm has gained considerable recent attention due to its potential for supporting sensing and communication services simultaneously. To provide low-latency communication services for multiple communication users while sensing an unmanned aerial vehicle simultaneously, a non-orthogonal multiple access (NOMA) empowered integrated sensing and communication (ISAC) system is developed in this paper. To support the NOMA-empowered ISAC system efficiently, a beamforming-based cross-layer scheduling scheme is designed, which exploits the traffic dynamics information at the network layer and channel state information at the physical layer. Under the cross-layer scheduling scheme, an efficient joint beamforming, power allocation, and rate adaptation strategy is obtained via a developed Newton's method-based algorithm and the linear programming formulation. With the aid of the proposed strategy, the average delay in the communication task can be minimized while assuring sensing capability. Besides, an optimal tradeoff between the average delay and the average transmission power in the NOMA-empowered ISAC system is uncovered, which is further demonstrated by extensive numerical results.
Authors
- Shenghui Song (ORCID: https://orcid.org/0000-0001-6316-8415)
- Yi Gu
- Zhanyuan Xie (ORCID: https://orcid.org/0000-0001-8391-2803)
- Peng Chen (ORCID: https://orcid.org/0000-0001-8634-4717)
- Zheng Jiang (ORCID: https://orcid.org/0000-0002-5743-223X)
- Randall Li (ORCID: https://orcid.org/0009-0009-8966-2177)
- Jianchi Zhu
Institutions
- Hong Kong University of Science and Technology (HK)
- China Telecom (China) (CN)
- China Telecom (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- IEEE Transactions on Vehicular Technology
- Published
- 2024-09-27
- DOI
- https://doi.org/10.1109/tvt.2024.3469397
- Citations
- 10
- Primary Topic
- Advanced Wireless Communication Technologies
- Type
- article
- Field-Weighted Citation Impact
- 2.09