混合可重构智能表面辅助的大规模MIMO集成感知与通信系统的性能分析与联合波束成形
Performance Analysis and Joint Beamforming for Hybrid RIS-Aided Massive MIMO ISAC
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中文总结 AI 辅助
该研究针对混合可重构智能表面辅助的大规模MIMO集成感知与通信系统，推导通信和速率与感知CRLB闭式表达式，提出联合优化算法，仿真验证其可同时大幅提升通信与感知性能。
中文摘要 AI 辅助
在集成感知与通信（ISAC）系统中，严格的感知性能约束会严重限制通信可用功率。兼具无源反射与有源信号放大能力的混合可重构智能表面（HRIS）可在功率受限场景下显著提升通信性能，这促使我们分析并优化HRIS辅助的多输入多输出（mMIMO）ISAC系统的性能。我们首先采用最小均方误差方法估计有效上行/下行链路信道，随后推导通信和速率与感知克拉美罗下界（CRLB）的闭式表达式，结果表明在等功率分配策略下，CRLB与HRIS系数无关。接着，我们构建功率分配与HRIS波束成形的联合优化问题，以最大化通信和速率同时满足指定的感知CRLB约束。为求解该非凸问题，我们提出基于分数规划与逐次凸近似的交替优化算法。大量仿真验证了我们的分析与所提算法，结果显示HRIS可同时显著提升通信与感知性能：例如，仅含4个有源单元的HRIS，在满足-30 dB的感知CRLB约束时，通信和速率提升97.30%。
英文摘要
In integrated sensing and communication (ISAC) systems, stringent sensing performance constraints can severely limit the power available for communication. Hybrid reconfigurable intelligent surfaces (HRISs) with capabilities of both passive reflection and active signal amplification can significantly improve communication performance in the power-limited regime. This motivates us to analyze and optimize the performance of an HRIS-aided multiple-input-multiple-output (mMIMO) ISAC system. We first estimate the effective uplink/downlink channels using the minimum mean square error method. We then derive closed-form expressions for the communication sum-rate and sensing Cramér-Rao lower bound (CRLB). It is shown that under the equal power allocation strategy, the CRLB remains independent of the HRIS coefficients. Then, we formulate a joint optimization problem of power allocation and HRIS beamforming to maximize the communication sum-rate while ensuring specified sensing CRLB constraints. To solve the formulated non-convex problem, we propose an alternating optimization algorithm based on fractional programming and successive convex approximation. Extensive simulations validate our analysis and proposed algorithm, showing significant improvements in both communication and sensing performances enabled by the HRIS. For example, an HRIS with only $4$ active elements offers $97.30\%$ improvement in the communication sum-rate, while ensuring a sensing CRLB constraint of $-30$ dB.
