相关论文: Towards Intelligent Reconfigurable Wireless Physic…
Machine Learning (ML) and Artificial Intelligence(AI) have become alternative approaches in wireless networksbeside conventional approaches such as model based solutionconcepts. Whereas traditional design concepts include the mod-elling of…
Security at the physical layer (PHY) is a salient research topic in wireless systems, and machine learning (ML) is emerging as a powerful tool for providing new data-driven security solutions. Therefore, the application of ML techniques to…
In this paper, we survey state-of-the-art research outcomes in the burgeoning field of reconfigurable intelligent surface (RIS) in view of its potential for significant performance enhancement for next generation wireless communication…
Following recent advances in flexible electronics and programmable metasurfaces, flexible intelligent metasurfaces (FIMs) have emerged as a promising enabling technology for next-generation wireless networks. A FIM is a morphable…
Signal processing and communication communities have witnessed the rise of many exciting communication technologies in recent years. Notable examples include alternative waveforms, massive multiple-input multiple-output (MIMO) signaling,…
Reconfigurable intelligent surfaces (RISs) are regarded as a promising emerging hardware technology to improve the spectrum and energy efficiency of wireless networks by artificially reconfiguring the propagation environment of…
Re-configurable Intelligent Surfaces (RIS) technology is increasingly becoming a potential component for next-generation wireless networks, offering enhanced performance in terms of throughput, spectral, and energy efficiency. However, the…
Traditional physical (PHY) layer protocols contain chains of signal processing blocks that have been mathematically optimized to transmit information bits efficiently over noisy channels. Unfortunately, this same optimality encourages…
Reconfigurable intelligent surfaces (RISs) are considered as potential technologies for the upcoming sixth-generation (6G) wireless communication system. Various benefits brought by deploying one or multiple RISs include increased spectrum…
Deep learning (DL) has proven its unprecedented success in diverse fields such as computer vision, natural language processing, and speech recognition by its strong representation ability and ease of computation. As we move forward to a…
Reconfigurable intelligent surfaces have emerged as a promising technology for future wireless networks. Given that a large number of reflecting elements is typically used, and that the surface has no signal processing capabilities, a major…
Reconfigurable Intelligent Surfaces (RISs) are a promising technique for enhancing the performance of Next Generation (NextG) wireless communication systems in terms of both spectral and energy efficiency, as well as resource utilization.…
Wireless communications are nowadays shifting to higher operation frequencies with the aim to meet the ever-increasing demand for bandwidth. While reconfigurable intelligent surfaces (RISs) are usually envisioned to restore the…
The advance of Artificial Intelligence (AI) is continuously reshaping the future 6G wireless communications. Particularly, the development of Large Language Models (LLMs) offers a promising approach to effectively improve the performance…
Research on reconfigurable intelligent surfaces (RISs) has predominantly focused on purely physical (PHY)-layer aspects, particularly, on how signals are dynamically shaped by a controllable wireless propagation environment. However,…
Reconfigurable Intelligent Surfaces are composed of physical elements that can dynamically alter electromagnetic wave properties to enhance beamforming and lead to improvements in areas with low coverage properties. When combined with…
The reconfigurable intelligent surface is a promising technology for the manipulation and control of wireless electromagnetic signals. In particular, it has the potential to provide significant performance improvements for wireless…
Reconfigurable intelligent surfaces (RISs), also known as intelligent reflecting surfaces (IRSs), or large intelligent surfaces (LISs), have received significant attention for their potential to enhance the capacity and coverage of wireless…
Deep learning (DL) has revolutionized wireless communication systems by introducing datadriven end-to-end (E2E) learning, where the physical layer (PHY) is transformed into DL architectures to achieve peak optimization. Leveraging DL for…
We introduce "Wireless 2.0": The future generation of wireless communication networks, where the radio environment becomes controllable, programmable, and intelligent by leveraging the emerging technologies of reconfigurable metasurfaces…