Souto Victoria Dala Pegorara, Souza Richard Demo, Uchôa-Filho Bartolomeu F, Li Yonghui
Center of Social and Technological Sciences, Catholic University of Pelotas, Pelotas 96015-560, RS, Brazil.
Department of Electrical and Electronic Engineering, Federal University of Santa Catarina, Florianópolis 88040-900, SC, Brazil.
Sensors (Basel). 2022 Mar 20;22(6):2390. doi: 10.3390/s22062390.
Intelligent Reflecting Surfaces (IRSs) are emerging as an effective technology capable of improving the spectral and energy efficiency of future wireless networks. The proposed scenario consists of a multi-antenna base station and a single-antenna user that is assisted by an IRS. The large number of reflecting elements at the IRS and its passive operation represent an important challenge in the acquisition of the instantaneous channel state information (I-CSI) of all links as it adds a very high overhead to the system and requires equipping the IRS with radio-frequency chains. To overcome this problem, a new approach is proposed in order to optimize beamforming at the BS and the phase shifts at the IRS without considering any knowledge of I-CSI but while only exploring the statistical channel state information (S-CSI). We aim at maximizing the user-achievable rate subject to a maximum transmit power constraint. To achieve this goal, we propose a new two-phase framework. In the first phase, both the beamforming at the BS and IRS are designed based only on S-CSI and, in the second phase, the previously designed beamforming pair is used as an initial solution, and beamforming at the BS and IRS is designed only by considering the feedback of the SNR at UE. Moreover, for each phase, we propose new methods based on Genetic Algorithms. Results show that the developed algorithms can approach beamforming with I-CSI but with significantly reduced channel estimation overhead.
智能反射面（IRS）正成为一种能够提高未来无线网络频谱和能量效率的有效技术。所提出的场景由一个多天线基站和一个由IRS辅助的单天线用户组成。IRS处大量的反射元件及其无源操作，在获取所有链路的瞬时信道状态信息（I-CSI）方面构成了一项重大挑战，因为这给系统增加了非常高的开销，并且需要为IRS配备射频链路。为克服这一问题，提出了一种新方法，以便在不考虑任何I-CSI知识的情况下，仅通过探索统计信道状态信息（S-CSI）来优化基站处的波束成形和IRS处的相移。我们的目标是在最大发射功率约束下最大化用户可实现速率。为实现这一目标，我们提出了一种新的两阶段框架。在第一阶段，基站和IRS处的波束成形仅基于S-CSI进行设计，在第二阶段，将先前设计的波束成形对用作初始解，并且仅通过考虑UE处SNR的反馈来设计基站和IRS处的波束成形。此外，对于每个阶段，我们基于遗传算法提出了新的方法。结果表明，所开发的算法能够接近具有I-CSI的波束成形，但显著降低了信道估计开销。
