This is a code package for the paper: R. Liu, M. Li, H. Luo, Q. Liu, and A. L. Swindlehurst, “Integrated sensing and communication with reconfigurable intelligent surfaces: Opportunities, applications, and future directions,” IEEE Wireless Commun., vol. 30, no. 1, pp. 50-57, Feb. 2023.
@ARTICLE{10077119, author={Liu, Rang and Li, Ming and Luo, Honghao and Liu, Qian and Swindlehurst, A. Lee}, journal={IEEE Wireless Communications}, title={Integrated Sensing and Communication with Reconfigurable Intelligent Surfaces: Opportunities, Applications, and Future Directions}, year={2023}, volume={30}, number={1}, pages={50-57}, keywords={Wireless communication;Economics;6G mobile communication;Wireless sensor networks;Hardware;Sensors;Wireless sensor networks}, doi={10.1109/MWC.002.2200206}}
- If you use this simulation code package in any way, please cite the original paper above.
- All codes are contributed by Rang Liu (email: rangl2@uci.edu; website: https://rangliu0706.github.io/). Please feel free to contact with her if you have any suggestions.
- The link of this paper is: https://ieeexplore.ieee.org/document/10077119
- More information can be found at: https://www.minglabdut.com/resource.html
- Copyright Notice: This code is licensed for personal, non-commercial use only, specifically for academic purposes. Copyright reserved by the MingLab (led by Prof. Ming Li), School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China.
- Please note that the MATLAB2022b is used for this simulation code package, and there may be some imcompatibility problems among different sofrware versions.
- To run those codes, please download and install CVX & Manopt
- The files "main_iterations", "main_SINR_N" is used to generate Figs. 2 and 3.
Abstract of the paper: Integrated sensing and communication (ISAC) is emerging as a key enabler to address the growing spectrum congestion problem and satisfy increasing demands for ubiquitous sensing and communication. By sharing various resources and information, ISAC achieves much higher spectral, energy, hardware, and economic efficiencies. Concurrently, reconfigurable intelligent surface (RIS) technology has been deemed as a promising approach due to its capability of intelligently manipulating the wireless propagation environment in an energy and hardware efficient manner. Given the extensive research on RIS-assisted communications, in this article we mainly focus on the potential of deploying RIS to improve sensing performance and enhance the trade-off between communication and sensing performance. We first describe the fundamentals of RIS and its applications in traditional communication and sensing systems, then introduce the principles of ISAC and overview existing explorations on RIS-assisted ISAC, followed by one case study to verify the advantages of deploying RIS in ISAC systems. Finally, open challenges and research directions are discussed to stimulate this line of research and pave the way for practical applications.