Three-dimensional communication small base station

Three-Dimensional Deployment Optimization of UAVs Using

We propose a novel systematic approach for the deployment optimization of unmanned aerial vehicles (UAVs). In this context, this study focuses on enhancing the

3-D UAV Small Cell Base Station Positioning and Resource

The suggested mathematical formulation determines the minimum number of required UAVs, their 3-D positions, and the best user association strategy. The proposed model also includes

linhhoang-ex/uav-bs-placement-drl

This repository is the implementation of the deep reinforcement learning (DRL) framework for multi-UAV 3D placement optimization proposed in

Efficient three‐dimensional deployment of multiple unmanned

UAVs can be used as flying base stations without an infrastructure to improve coverage, capacity, line-of-sight (LoS) connection, and rate performance in wireless

Adaptive Multi-Scale Bidirectional TD3 Algorithm for Layout

Section 3 elaborates on the three-dimensional base station communication model, including the principles of terrain generation, signal coverage description, base station

Three-Dimensional Model of the Radio Links Formation between

A three-dimensional model of the radio links formation between a base station (BS) of a mobile communication system and a ground user terminal with signal relaying through an unmanned

3-D Positioning and Resource Allocation for Multi-UAV Base

In this section, we provide simulation results to evaluate the performance of the proposed joint 3-D positioning and resource allocation scheme for multi-UAV communication networks aided by

Three-Dimensional Deployment Optimization of

We propose a novel systematic approach for the deployment optimization of unmanned aerial vehicles (UAVs). In this context, this

Three-Dimensional Model of the Radio Links Formation between the Base

A three-dimensional model of the radio links formation between a base station (BS) of a mobile communication system and a ground user terminal with signal relaying through an unmanned

Efficient three‐dimensional deployment of multiple

UAVs can be used as flying base stations without an infrastructure to improve coverage, capacity, line-of-sight (LoS)

linhhoang-ex/uav-bs-placement-drl

This repository is the implementation of the deep reinforcement learning (DRL) framework for multi-UAV 3D placement optimization proposed in the paper Adaptive 3D Placement of

3D deployment of UAV-mounted base stations for

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

Dynamic 3-Dimensional Deployment of Unmanned Aerial Vehicle Base

In this paper, the dynamic deployment of multiple UAV-BSs in complex urban scenario is studied with the objective of enhancing the overall average transmission rate.

3D Deployment of Multiple UAV-Mounted Base Stations for UAV Communications

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 the coverage rate by...

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4 FAQs about Three-dimensional communication small base station

Can a 3D aerial base station be placed in a cellular network?

A 3D placement of unmanned aerial vehicle base station based on multi-population genetic algorithm for maximizing users with different QoS requirements. Paper presented at: 2018 IEEE 18th International Conference on Communication Technology (ICCT). IEEE Efficient 3-D placement of an aerial base station in next generation cellular networks.

Can a 3D base station be used in next generation cellular networks?

IEEE Efficient 3-D placement of an aerial base station in next generation cellular networks. Paper presented at: 2016 IEEE International Conference on Communications (ICC).

Can a fixed base station deliver a high-reliable and low-latency communication capacity?

However, achieving the ultra-reliable and low-latency communication capacity promised by 6G is not possible with fixed base stations alone. In particular, environments such as densely populated areas, disaster areas, rural areas, and hard-to-reach areas are among the scenarios where fixed infrastructures are inadequate.

Will drone base station technology play a significant role in mobile communication networks?

All these studies indicate that drone base station technology will play a significant role in the future of mobile communication networks. Therefore, research activities in this area continue to increase. 2. Technical Background of UAV Deployment Optimization and Base Station Communication 2.1. General Structure of UAVs