论文标题
IRS辅助多源通信的快速梁训练
Fast Beam Training for IRS-Assisted Multiuser Communications
论文作者
论文摘要
在这封信中,我们考虑了一个智能反射表面(IRS)辅助的多源通信系统,其中部署了IRS以在访问点(AP)和多个用户之间提供虚拟的视线(LOS)链接。我们认为基于代码书的实用IRS被动横梁形成和IRS的研究有效设计反映了光束训练,这是由于反映元素数量的大量IR所致。与常规的单光束训练相反,我们通过将反映元素反映为多个子阵列的IRS并设计其同时的多光束转向的新型多光束训练方法。通过简单地比较接收到的信号功率,每个用户都可以以很高的概率检测其最佳IRS光束方向,即使无需在所有可能的光束方向上搜索单光束训练。仿真结果表明,我们提出的多光束训练大大减少了传统的单光束训练的训练时间,但可以实现可比的IRS被动边界成形性能以进行数据传输。
In this letter, we consider an intelligent reflecting surface (IRS)-assisted multiuser communication system, where an IRS is deployed to provide virtual line-of-sight (LoS) links between an access point (AP) and multiple users. We consider the practical codebook-based IRS passive beamforming and study efficient design for IRS reflect beam training, which is challenging due to the large number of IRS reflecting elements. In contrast to the conventional single-beam training, we propose a new multi-beam training method by dividing the IRS reflecting elements into multiple sub-arrays and designing their simultaneous multi-beam steering over time. By simply comparing the received signal power over time, each user can detect its optimal IRS beam direction with a high probability, even without searching over all possible beam directions as the single-beam training. Simulation results show that our proposed multi-beam training significantly reduces the training time of conventional single-beam training and yet achieves comparable IRS passive beamforming performance for data transmission.