Low Complexity Joint Detection and Estimation for MIMO RIS-ISAC Systems

Integrated sensing and communication (ISAC) and reconfigurable intelligent surfaces (RIS) have been identified as key technologies in the realization of next-generation wireless networks. ISAC provides spectral and hardware efficiency by integrating the communication and sensing functionalities into one system, whilst RIS is used to improve signal transmission. In this letter, a low-cost RIS-ISAC receiver is proposed for the first time in a multiple-input multiple-output (MIMO) system. A search-tree is deployed to detect the MIMO RIS-ISAC transmitted communication signals. Next, the K-best algorithm is proposed to reduce the computational complexity of maximum likelihood (ML) detection while achieving near-ML bit-error rate performance. Additionally, the minimum mean-squared error estimation technique is adopted to estimate the reflection coefficients of a nearby target. Computational complexity analysis and Monte Carlo simulations are provided to support the findings.