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arXiv 2405.03300cs.ITeess.SPmath.IT
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非理想CSI与相位噪声下有源RIS辅助的大规模MIMO

Active RIS-Aided Massive MIMO With Imperfect CSI and Phase Noise

Zhangjie Peng, Jianchen Zhu, Cunhua Pan, Zaichen Zhang, Daniel Benevides da Costa, Maged Elkashlan, George K. Karagiannidis

AI总结:

本文研究有源RIS辅助上行大规模MIMO在非理想CSI和相位噪声下的性能,采用双时间尺度方案与LMMSE信道估计,推导速率下界并分析功率缩放律,提出遗传算法优化相移,验证有源RIS的显著增益。

摘要:

有源可重构智能表面(RIS)作为最近提出的一种RIS架构,已引起广泛关注。由于其能够放大入射信号,有源RIS可以缓解无源RIS辅助系统中固有的乘性衰落效应。本文考虑一个有源RIS辅助的上行多用户大规模多输入多输出(MIMO)系统,并在有源RIS处存在相位噪声。具体而言,我们采用双时间尺度方案,其中基站(BS)处的波束成形根据瞬时聚合信道状态信息(CSI)进行调整,而统计CSI作为设计有源RIS相移的基础,从而可以显著降低反馈开销和计算复杂度。由级联信道和直射信道组成的聚合信道利用线性最小均方误差(LMMSE)技术进行估计。基于估计信道,我们推导出可实现速率下界的解析闭式表达式。基于理论表达式,研究了有源RIS辅助系统中的功率缩放律。当每个用户的发射功率按基站天线数M或反射单元数N缩减时,我们发现热噪声将导致可实现速率的下界趋近于零,因为M或N的数量增加到无穷大。此外,引入了一种基于遗传算法(GA)的优化方法来处理相移优化问题。数值结果表明,有源RIS能够在各种设置下显著提升所考虑系统的性能。

英文摘要:

Active reconfigurable intelligent surface (RIS) has attracted significant attention as a recently proposed RIS architecture. Owing to its capability to amplify the incident signals, active RIS can mitigate the multiplicative fading effect inherent in the passive RIS-aided system. In this paper, we consider an active RIS-aided uplink multi-user massive multiple-input multiple-output (MIMO) system in the presence of phase noise at the active RIS. Specifically, we employ a two-timescale scheme, where the beamforming at the base station (BS) is adjusted based on the instantaneous aggregated channel state information (CSI) and the statistical CSI serves as the basis for designing the phase shifts at the active RIS, so that the feedback overhead and computational complexity can be significantly reduced. The aggregated channel composed of the cascaded and direct channels is estimated by utilizing the linear minimum mean square error (LMMSE) technique. Based on the estimated channel, we derive the analytical closed-form expression of a lower bound of the achievable rate. The power scaling laws in the active RIS-aided system are investigated based on the theoretical expressions. When the transmit power of each user is scaled down by the number of BS antennas M or reflecting elements N, we find that the thermal noise will cause the lower bound of the achievable rate to approach zero, as the number of M or N increases to infinity. Moreover, an optimization approach based on genetic algorithms (GA) is introduced to tackle the phase shift optimization problem. Numerical results reveal that the active RIS can greatly enhance the performance of the considered system under various settings.

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