Direct-to-satellite (DtS) communication has gained importance recently to support globally connected Internet of things (IoT) networks. However, relatively long distances of densely deployed satellite networks around the Earth cause a high path loss. In addition, since high complexity operations such as beamforming, tracking and equalization have to be performed in IoT devices partially, both the hardware complexity and the need for high-capacity batteries of IoT devices increase. The reconfigurable intelligent surfaces (RISs) have the potential to increase the energy-efficiency and to perform complex signal processing over the transmission environment instead of IoT devices. But, RISs need the information of the cascaded channel in order to change the phase of the incident signal. This study evaluates the pilot signal as a graph and incorporates this information into the graph attention networks (GATs) to track the phase relation through pilot signaling. Proposed GAT based channel estimation method examines the performance of the DtS IoT networks for different RIS configurations to solve the challenging channel estimation problem. It is shown that the proposed GAT both demonstrates a higher performance with increased robustness under changing conditions and has lower computational complexity compared to conventional deep learning methods. Moreover, bit error rate performance is investigated for RIS designs with discrete and non-uniform phase shifts under channel estimation based on the proposed method. One of the findings in this study is that the channel models of the operating environment and the performance of the channel estimation method must be considered during RIS design to exploit performance improvement as far as possible.
翻译:直接到卫星(DtS)通信最近越来越重要,以支持全球连通的物联网网络(IoT),然而,地球周围密集部署的卫星网络距离相对较长,造成高路径损失;此外,由于在IoT装置中必须部分地进行诸如光成像、跟踪和均衡等高度复杂的操作,因此,在IoT装置中,硬件的复杂性和对高容量电池装置的需求都有所增加。可重新配置的智能表面(RIS)有可能提高能源效率,在传输环境而不是IoT装置上进行复杂的信号处理。但是,RIS需要升级的频道信息,以改变事件信号的阶段。此外,这项研究将试验信号作为图表,并将这一信息纳入图示关注网络,以便通过试点信号跟踪阶段的关系。基于GAT的频道估算方法将审查DtS IoT网络的性能,以便解决具有挑战性的频道估算问题。 研究显示,拟议的GATT网络既能显示更高的性能,也需要升级的频道信号渠道信息,以便改变事件信号信号的阶段。 本阶段的运行方法在进行深度设计方法下,在进行更精确的研拟方法下,必须进行更精确的周期的研算。