CRB Minimization for RIS-Aided mmWave Integrated Sensing and Communications

CRB Minimization for RIS-Aided mmWave Integrated Sensing and Communications

IEEE Internet of Things Journal

10.1109/JIOT.2024.3361939

https://doi.org/10.1109/jiot.2024.3361939

Wanting Lyu, Songjie Yang, Yue Xiu, Ya Li, Hongjun He, Chau Yuen, Zhongpei Zhang

05 February 2024

Lyu, W., Yang, S., Xiu, Y., Li, Y., He, H., Yuen, C., & Zhang, Z. (2024). CRB Minimization for RIS-Aided mmWave Integrated Sensing and Communications. IEEE Internet of Things Journal, 11(10), 18381–18393. https://doi.org/10.1109/jiot.2024.3361939

In this article, reconfigurable intelligent surface (RIS) is employed in a millimeter-wave (mmWave) integrated sensing and communications (ISAC) system. To alleviate the multihop attenuation, the semi-self sensing RIS approach is adopted, wherein sensors are configured at the RIS to receive the radar echo signal. Focusing on the estimation accuracy, the Cram´er–Rao bound (CRB) for estimating the direction of the angles is derived as the metric for sensing performance. A joint optimization problem on hybrid beamforming and RIS phase shifts is proposed to minimize the CRB, while maintaining satisfactory communication performance evaluated by the achievable data rate. The CRB minimization problem is first transformed as a more tractable form based on Fisher information matrix (FIM). To solve the complex nonconvex problem, a double layer loop algorithm is proposed based on penalty concave– convex procedure (penalty-CCCP) and block coordinate descent (BCD) method with two subproblems. The successive convex approximation (SCA) algorithm and second-order cone (SOC) constraints are employed to tackle the nonconvexity in the hybrid beamforming optimization. To optimize the unit modulus constrained analog beamforming and phase shifts, manifold optimization (MO) is adopted. Finally, the numerical results verify the effectiveness of the proposed CRB minimization algorithm and show the performance improvement compared with other baselines. Additionally, the proposed hybrid beamforming algorithm can achieve approximately 96% of the sensing performance exhibited by the full digital approach within only a limited number of radio frequency (RF) chains.

Publisher Copyright

This research / project is supported by the China Scholarship Council - NA
Grant Reference no. : 202206070054

This research / project is supported by the Joint Project of China Mobile Research Institute & X-NET - NA
Grant Reference no. : NA

This research / project is supported by the Natural Science Foundation of Shenzhen City - NA
Grant Reference no. : JCYJ20210324140002008

This research / project is supported by the Natural Science Foundation of Sichuan Province - NA
Grant Reference no. : 2022NSFSC0489

This research / project is supported by the Ministry of Education, Singapore - Academic Research Fund Tier 2
Grant Reference no. : Award MOE-T2EP50220-0019

This research / project is supported by the Science and Engineering Research Council of Agency for Science, Technology and Research (A*STAR), Singapore - Manufacturing, Trade, and Connectivity Programmatic Fund
Grant Reference no. : M22L1b0110

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Institute of Microelectronics