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Three-dimensional communication bidding for small base stations

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

Efficient three‐dimensional deployment of multiple unmanned

Our work investigates a model to find the efficient placements of multiple UAVs and optimize bandwidth between UAVs and GBS to enhance network performance by maximizing

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

3D Deployment of UAV-BSs for Effective Communication Coverage

In this paper, we propose a novel heuristic algorithm based three-dimensional (3-D) UAV deployment scheme while guaranteeing the connectivity of the UAV network in both

Efficient three‐dimensional deployment of multiple

Our work investigates a model to find the efficient placements of multiple UAVs and optimize bandwidth between UAVs and GBS to

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

Modified Least Squares Algorithm for Three-Dimensional

For the first time, this paper focuses on the problem of modifying the axis-Z location coordinates in three-dimensional (3D) target location. A novel algorithm is proposed by establishing the

Wireless Communication Base Station Location Selection

1. Introduction, the enhancement of wireless network performance is concerned with meeting the increasing communication demands. For wireless communication systems,

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

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

Compared with the existing works, the constraints of the required quality of service (QoS) and the service ability of each UAV are considered, which makes the problem more challenging. A...

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

Compared with the existing works, the constraints of the required quality of service (QoS) and the service ability of each UAV are considered, which makes the problem more challenging. A...

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

Abstract In this paper, we propose to deploy multiple unmanned aerial vehicle (UAV) mounted base stations to serve ground users in outdoor environments with obstacles. In particular, the

Three-Dimensional Deployment Optimization of

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

Adaptive 3D Placement of Multiple UAV-Mounted Base Stations

Since the users'' location and traffic demand vary over time, we dynamically group users into clusters using a K-means-based algorithm and adjust the 3D location of UAV-BSs using an

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4 FAQs about Three-dimensional communication bidding for small base stations

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 unmanned aerial vehicles be a base station for IoT?

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.

How are base stations based on ray-tracing based channel modeling?

Additionally, at their new locations, these behaviors are adjusted to facilitate accurate coverage estimation from the base stations they serve. In the deployment optimization of UAVs, the placement of base stations is determined using received signal strength data obtained through the ray-tracing-based channel modeling technique.

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