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Reconfigurable intelligent surface (RIS) has emerged as a cost-effective and energy-efficient technique for 6G. By adjusting the phase shifts of passive reflecting elements, RIS is capable of suppressing the interference and combining the…
Reconfigurable intelligent surfaces (RIS), recognized as a critical enabler for 6G networks, exhibit unprecedented capabilities in electromagnetic wave manipulation and wireless channel reconfiguration. By leveraging existing network…
A reconfigurable intelligent surface (RIS) is a prospective wireless technology that enhances wireless channel quality. An RIS is often equipped with passive array of elements and provides cost and power-efficient solutions for coverage…
Reconfigurable intelligent surface (RIS) is an emerging technology for future wireless communication systems. In this work, we consider downlink spatial multiplexing enabled by the RIS for weighted sum-rate (WSR) maximization. In the…
Reconfigurable intelligent surfaces (RISs) are expected to make future 6G networks more connected and resilient against node failures, due to their ability to introduce controllable phase-shifts onto impinging electromagnetic waves and…
The adoption of a Reconfigurable Intelligent Surface (RIS) for downlink multi-user communication from a multi-antenna base station is investigated in this paper. We develop energy-efficient designs for both the transmit power allocation and…
Reconfigurable Intelligent Surface (RIS) has emerged as one of the key technologies for 6G in recent years, which comprise a large number of low-cost passive elements that can smartly interact with the impinging electromagnetic waves for…
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.…
Reconfigurable intelligent surface (RIS) has become a promising technology to improve wireless communication in recent years. It steers the incident signals to create a favorable propagation environment by controlling the reconfigurable…
Reconfigurable Intelligent Surfaces (RISs) are becoming one of the fundamental building blocks of next-generation wireless communication systems. To that end, RIS phase configuration optimization is an important issue, where finding the…
This paper presents a novel system architecture for hybrid satellite communications, integrating quantum key distribution (QKD) and classical radio frequency (RF) data transmission using a dual-band reconfigurable intelligent surface (RIS).…
We propose a graph neural network (GNN) architecture to optimize base station (BS) beamforming and reconfigurable intelligent surface (RIS) phase shifts in a multi-RIS assisted wireless network. We create a bipartite graph model to…
In the sixth-generation (6G) era, emerging large-scale computing based applications (for example processing enormous amounts of images in real-time in autonomous driving) tend to lead to excessive energy consumption for the end users, whose…
Graph Neural Networks (GNNs) are eminently suitable for wireless resource management, thanks to their scalability, but they still face computational challenges in large-scale, dense networks in classical computers. The integration of…
Reconfigurable intelligent surfaces (RIS) have been actively researched as a potential technique for future wireless communications, which intelligently ameliorate the signal propagation environment. In the conventional design, each RIS…
Reconfigurable intelligent surface (RIS) is a two-dimensional periodic structure integrated with a large number of reflective elements, which can manipulate electromagnetic waves in a digital way, offering great potentials for wireless…
The growing demand for high-speed, reliable wireless connectivity in 6G networks necessitates innovative approaches to overcome the limitations of traditional Radio Access Network (RAN). Reconfigurable Intelligent Surface (RIS) and…
We introduce Genetic Transformer Assisted Quantum Neural Networks (GTQNNs), a hybrid learning framework that combines a transformer encoder with a shallow variational quantum circuit and automatically fine tunes the circuit via the NSGA-II…
This paper presents a novel approach for the joint design of a reconfigurable intelligent surface (RIS) and a transmitter-receiver pair that are trained together as a set of deep neural networks (DNNs) to optimize the end-to-end…
The reconfigurable intelligent surface (RIS) is a promising technology for next-generation wireless communication. It comprises many passive antennas, which reflect signals from the transmitter to the receiver with adjusted phases without…