This paper studies user fairness of an integrated sensing and communication (ISAC) system adopting both simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) and non-orthogonal multiple access (NO-MA). Note that optimizing user fairness of an ISAC system is critical, since the performance trade-off in terms of spectrum resource utilization between communication users and sensing users is hard to balance and improve, particularly at the low signal-to-noise ratio (SNR) regimes. However, such optimization problem is a coupled, non-convex, and is NP-hard in general. To solve this challenging problem, a low-complexity algorithm based on both the successive convex approximation and the semi-deterministic programming techniques is proposed. Notably, the proposed approach can maximize the signal-to-interference-plus-noise ratio (SINR) for the weakest communication user, while guaranteeing the superior sensing performance characterized by the cramér-rao lower bound (CRLB) for the sensing user. Simulation results demonstrate that our approach is capable of enabling superior sum-rate performance than the STAR-RIS with orthogonal multiple access (OMA), the conventional-RIS with NOMA, and the conventional-RIS with OMA schemes.


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    Title :

    Cramér-Rao Lower Bound and Fairness Optimization in STAR-RIS Assisted ISAC Systems


    Contributors:
    Wang, Ruidong (author) / Cao, Yuwen (author) / Ohtsuki, Tomoaki (author) / He, Jiguang (author)


    Publication date :

    2024-10-07


    Size :

    1128838 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English