2020/07/15 by Hamidreza Taghvaee, Akshay Jain, Taghvaee, Hamidreza +11 · 1 citation
Engineering · Materials Science · #Advanced Antenna and Metasurface Technologies #Emerging Technologies (cs.ET) #FOS: Computer and information sciences #FOS: Electrical engineering #Metamaterials and Metasurfaces Applications #Millimeter-Wave Propagation and Modeling #Networking and Internet Architecture (cs.NI) #Neural and Evolutionary Computing (cs.NE) #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2007.08035
openalex publication_date 2020/07/15 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
As the current standardization for the 5G networks nears completion, work\ntowards understanding the potential technologies for the 6G wireless networks\nis already underway. One of these potential technologies for the 6G networks\nare Reconfigurable Intelligent Surfaces (RISs). They offer unprecedented\ndegrees of freedom towards engineering the wireless channel, i.e., the ability\nto modify the characteristics of the channel whenever and however required.\nNevertheless, such properties demand that the response of the associated\nmetasurface (MSF) is well understood under all possible operational conditions.\nWhile an understanding of the radiation pattern characteristics can be obtained\nthrough either analytical models or full wave simulations, they suffer from\ninaccuracy under certain conditions and extremely high computational\ncomplexity, respectively. Hence, in this paper we propose a novel neural\nnetworks based approach that enables a fast and accurate characterization of\nthe MSF response. We analyze multiple scenarios and demonstrate the\ncapabilities and utility of the proposed methodology. Concretely, we show that\nthis method is able to learn and predict the parameters governing the reflected\nwave radiation pattern with an accuracy of a full wave simulation (98.8%-99.8%)\nand the time and computational complexity of an analytical model. The\naforementioned result and methodology will be of specific importance for the\ndesign, fault tolerance and maintenance of the thousands of RISs that will be\ndeployed in the 6G network environment.\n