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Reconfigurable intelligent surface (RIS) has entered the public consciousness as a promising technology for enhancing the performance of future wireless communication systems by dynamically constructing the wireless channels. In this…
A multiuser multiple-input multiple-output wireless communication system is analytically studied, which operates with the aid of a reconfigurable intelligent surface (RIS). The intermediate RIS is equipped with multiple elements and…
Nonorthogonal multiple access (NOMA) with multi-antenna base station (BS) is a promising technology for next-generation wireless communication, which has high potential in performance and user fairness. Since the performance of NOMA depends…
Intelligent reflecting surfaces (IRSs) are regarded as key enablers of next-generation wireless communications, due to their capability of customizing the wireless propagation environment. In this paper, we investigate power-efficient…
The integration of Reconfigurable Intelligent Surfaces (RIS) in 6G wireless networks offers unprecedented control over communication environments. However, identifying optimal configurations within practical constraints remains a…
Deep learning (DL) has made notable progress in addressing complex radio access network control challenges that conventional analytic methods have struggled to solve. However, DL has shown limitations in solving constrained NP-hard problems…
Reconfigurable intelligent surface (RIS) is an attractive technology to improve the transmission rate of millimetre-wave (mmWave) communication systems. The previous {research} on RIS technology mainly focused on improving the transmission…
The transition toward localized intelligence through Small Language Models (SLMs) has intensified the need for rigorous performance characterization on resource-constrained edge hardware. However, objectively measuring the theoretical…
Reconfigurable intelligent surfaces (RISs) have huge potential to improve spectral and energy efficiency in future wireless systems at a minimal cost. However, early prototype results indicate that deploying hundreds or thousands of…
The steering dynamics of re-configurable intelligent surfaces (RIS) have hoisted them to the front row of technologies that can be exploited to solve skip-zones in wireless communication systems. They can enable a programmable wireless…
Reconfigurable intelligent surface (RIS) has been anticipated to be a novel cost-effective technology to improve the performance of future wireless systems. In this paper, we investigate a practical RIS-aided multiple-input-multiple-output…
Reconfigurable intelligent surface (RIS) technology holds immense potential for increasing the performance of wireless networks. Therefore, RIS is also regarded as one of the solutions to address communication challenges in high-mobility…
Indoor millimeter-wave (mmWave) environment channels are typically sparsely-scattered and dominated by a strong line-of-sight (LOS) path. Therefore, communication over such channels is in general extremely difficult when the LOS path is not…
Reconfigurable intelligent surfaces (RISs) have a revolutionary capability to customize the radio propagation environment for wireless networks. To fully exploit the advantages of RISs in wireless systems, the phases of the reflecting…
Reconfigurable Intelligent Surfaces (RIS) show great promise in the realm of 6th generation (6G) wireless systems, particularly in the areas of localization and communication. Their cost-effectiveness and energy efficiency enable the…
Due to the serious path loss of millimeter-wave (mmWave), the signal sent by the base station is seriously attenuated when it reaches the indoors. Recent studies have proposed a glass-based metasurface that can enhance mmWave indoor…
This article addresses the challenge of optimizing handover (HO) in next-generation wireless networks by integrating Reconfigurable Intelligent Surfaces (RIS), predicting received signal power, and utilizing learning-based decision-making.…
Large language model (LLM) has recently been considered a promising technique for many fields. This work explores LLM-based wireless network optimization via in-context learning. To showcase the potential of LLM technologies, we consider…
Unmanned aerial vehicles (UAVs) have brought a lot of flexibility in the network deployment. However, UAVs suffer from the high mobility and instability. To improve the capacity and reliability of the UAV networks, millimeter-wave (mmWave)…
Utilizing Deep Reinforcement Learning (DRL) for Reconfigurable Intelligent Surface (RIS) assisted wireless communication has been extensively researched. However, existing DRL methods either act as a simple optimizer or only solve problems…