Filtering Reconfigurable Intelligent Computational Surface for RF Spectrum Purification
arxiv(2024)
摘要
The increasing demand for communication is degrading the electromagnetic (EM)
transmission environment due to severe EM interference, significantly reducing
the efficiency of the radio frequency (RF) spectrum. Metasurfaces, a promising
technology for controlling desired EM waves, have recently received significant
attention from both academia and industry. However, the potential impact of
out-of-band signals has been largely overlooked, leading to RF spectrum
pollution and degradation of wireless transmissions. To address this issue, we
propose a novel surface structure called the Filtering Reconfigurable
Intelligent Computational Surface (FRICS). We introduce two types of FRICS
structures: one that dynamically reflects resonance band signals through a
tunable spatial filter while absorbing out-of-band signals using metamaterials
and the other one that dynamically amplifies in-band signals using
computational metamaterials while reflecting out-of-band signals. To evaluate
the performance of FRICS, we implement it in device-to-device (D2D)
communication and vehicular-to-everything (V2X) scenarios. The experiments
demonstrate the superiority of FRICS in signal-to-interference-noise ratio
(SINR) and energy efficiency (EE). Finally, we discuss the critical challenges
faced and promising techniques for implementing FRICS in future wireless
systems.
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