To exploit the potential of the RIS in supporting ISAC, this paper proposes a novel joint active and passive beamforming design for RIS-enabled ISAC system in consideration of the target size. First, the detection probability for target sensing is derived in closed-form based on the illumination power on an approximated scattering surface area of the target, and a new concept of ultimate detection resolution (UDR) is defined for the first time to measure the target detection capability. Then, an optimization problem is formulated to maximize the SNR at the UE under a minimum detection probability constraint. To solve the non-convex problem, a novel alternative optimization approach is developed. In this approach, the solutions of the communication and sensing beamformers are obtained by our proposed bisection-search based method. The optimal receive combining vector is derived from an equivalent Rayleigh-quotient problem. To optimize the RIS phase shifts, the Charnes-Cooper transformation is conducted to cope with the fractional objective, and a novel convexification process is proposed to convexify the detection probability constraint with matrix operations and a real-valued first-order Taylor expansion. After the convexification, a successive convex approximation (SCA) based algorithm is designed to yield a suboptimal phase-shift solution. Finally, the overall optimization algorithm is built, followed by detailed analysis on its computational complexity, convergence behavior and problem feasibility condition. Extensive simulations are carried out to testify the analytical properties of the proposed beamforming design, and to reveal two important trade-offs, namely, communication vs. sensing trade-off and UDR vs. sensing-duration trade-off. In comparison with several existing benchmarks, our proposed approach is validated to be superior when detecting targets with practical sizes.
翻译:为了利用RIS在支持ISAC方面的潜力,本文件提出一个新的联合主动和被动波束组合设计,以考虑到目标大小。首先,目标感测的概率以封闭形式产生,其依据是目标大致分散的表面地区的照明力,并且首次界定了最终检测解析的新概念(UDR),以衡量目标检测能力。然后,在最低的检测概率限制下,在UE提出优化问题,以最大限度地实现SNR。为了解决不连接的问题,制定了新的替代优化方法。在这一方法中,通信和感测光谱的解决方案是通过我们拟议的双剖面研究方法获得的。 最佳的组合矢量来自相当于Rayleg-量的问题。为了优化RIS阶段的变化,Charnes-Cooper的转换是为了适应拟议的偏差目标,在最小的精确度的精确度限制下,提出了一个新的拼凑进程。 一种与矩阵操作的检测概率制约,一个新的优化方法是升级至最终的逻辑化,在升级后,在升级后,在升级后,在升级后,将进行精确的系统分析。