Recently, unmanned aerial vehicles (UAVs) have been reported a lot as aerial base stations (BSs) to assist wireless communication in Internet of Things (IoT). However, most results for UAV deployment require uniform access requirements and obstacle-free environment.
However, most researchers focusing on intelligent algorithm-based base station deployment consider only two-dimensional map environments, neglecting the impact of real three-dimensional geographic environments on signal propagation and the actual random distribution of users based on real-world streets and other settings.
In particular, integrating passive IS into the base station (BS) is a novel solution to enhance the wireless network throughput and coverage, both cost-effectively and energy-efficiently. In this article, we provide an overview of IS-integrated BSs for wireless networks.
Previous research has extensively explored strategies for base station deployment using intelligent optimization algorithms. These studies employed advanced algorithms such as the sparrow algorithm, artificial immune system algorithm, and genetic algorithm, aiming to find optimal base station layouts in complex network environments.
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Adaptive 3D Placement of Aerial Base Stations via Deep Reinforcement Learning This repository is the implementation of the deep reinforcement learning (DRL) framework for multi-UAV 3D placement …
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Deploying uncrewed aerial vehicles (UAVs) as aerial base stations (BSs) to assist terrestrial connectivity has drawn significant attention in recent years. Alongside other UAV …
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This article investigates a communication system assisted by multiple UAV-mounted base stations (BSs), aiming to minimize the number of required UAVs and to improve …
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Adaptive 3D Placement of Aerial Base Stations via Deep Reinforcement Learning This repository is the implementation of the deep reinforcement learning (DRL) framework for …
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Recently, unmanned aerial vehicles (UAVs) have been reported a lot as aerial base stations (BSs) to assist wireless communication in Internet of Things (IoT). However, most …
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Channel theory is a fundamental theory of wireless communications. The sixth generation (6G) and beyond 6G (B6G) wireless communication networks are expected to …
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Learn how to set the base station position automatically or manually, and how to enable RTK corrections output in both RTCM and CMR formats.
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To solve the problems of unreasonable deployment and high construction costs caused by the rapid increase of the fifth generation (5 G) base stations, this article proposes a …
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Learn how to set the base station position automatically or manually, and how to enable RTK corrections output in both RTCM and CMR formats.
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Intelligent surface (IS) technology is promising for sixth-generation (6G) wireless networks, which can effectively reconfigure the wireless propagation environment using …
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UAV-based aerial base stations (BSs) can assist the ground network in improving both commu-nication and localization services. There have been many studies on deploying …
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Abstract—The emerging concept of 3D networks, integrating terrestrial, aerial, and space layers, introduces a novel and complex structure characterized by stations relaying …
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