Literature DB >> 36015781

Mobility Management of Unmanned Aerial Vehicles in Ultra-Dense Heterogeneous Networks.

W T Alshaibani1, Ibraheem Shayea2,3, Ramazan Caglar1, Jafri Din3, Yousef Ibrahim Daradkeh4.   

Abstract

The rapid growth of mobile data traffic will lead to the deployment of Ultra-Dense Networks (UDN) in the near future. Various networks must overlap to meet the massive demands of mobile data traffic, causing an increase in the number of handover scenarios. This will subsequently affect the connectivity, stability, and reliability of communication between mobile and serving networks. The inclusion of Unmanned Aerial Vehicles (UAVs)-based networks will create more complex challenges due to different mobility characterizations. For example, UAVs move in three-dimensions (3D), with dominant of line-of-sight communication links and faster mobility speed scenarios. Assuring steady, stable, and reliable communication during UAVs mobility will be a major problem in future mobile networks. Therefore, this study provides an overview on mobility (handover) management for connected UAVs in future mobile networks, including 5G, 6G, and satellite networks. It provides a brief overview on the most recent solutions that have focused on addressing mobility management problems for UAVs. At the same time, this paper extracts, highlights, and discusses the mobility management difficulties and future research directions for UAVs and UAV mobility. This study serves as a part of the foundation for upcoming research related to mobility management for UAVs since it reviews the relevant knowledge, defines existing problems, and presents the latest research outcomes. It further clarifies handover management of UAVs and highlights the concerns that must be solved in future networks.

Entities:  

Keywords:  5G networks; UAV; connected drones; deep learning; drones; handover; heterogeneous 6G networks; machine learning; mobility management

Year:  2022        PMID: 36015781      PMCID: PMC9416608          DOI: 10.3390/s22166013

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.847


  13 in total

1.  Orbit Angular Momentum MIMO with Mode Selection for UAV-Assisted A2G Networks.

Authors:  Tao Hu; Yang Wang; Bo Ma; Jie Zhang
Journal:  Sensors (Basel)       Date:  2020-04-17       Impact factor: 3.576

2.  DDQN with Prioritized Experience Replay-Based Optimized Geographical Routing Protocol of Considering Link Stability and Energy Prediction for UANET.

Authors:  Yanan Zhang; Hongbing Qiu
Journal:  Sensors (Basel)       Date:  2022-07-03       Impact factor: 3.847

3.  Secrecy Capacity Maximization of UAV-Enabled Relaying Systems with 3D Trajectory Design and Resource Allocation.

Authors:  Qi An; Yu Pan; Huizhu Han; Hang Hu
Journal:  Sensors (Basel)       Date:  2022-06-15       Impact factor: 3.847

4.  Super-Wide Impedance Bandwidth Planar Antenna for Microwave and Millimeter-Wave Applications.

Authors:  Mohammad Alibakhshikenari; Bal Singh Virdee; Chan H See; Raed A Abd-Alhameed; Francisco Falcone; Ernesto Limiti
Journal:  Sensors (Basel)       Date:  2019-05-19       Impact factor: 3.576

5.  Aerial Coverage Analysis of Cellular Systems at LTE and mmWave Frequencies Using 3D City Models.

Authors:  Achiel Colpaert; Evgenii Vinogradov; Sofie Pollin
Journal:  Sensors (Basel)       Date:  2018-12-06       Impact factor: 3.576

6.  Deep Reinforcement Learning for UAV Trajectory Design Considering Mobile Ground Users.

Authors:  Wonseok Lee; Young Jeon; Taejoon Kim; Young-Il Kim
Journal:  Sensors (Basel)       Date:  2021-12-09       Impact factor: 3.576

Review 7.  Closing Connectivity Gap: An Overview of Mobile Coverage Solutions for Not-Spots in Rural Zones.

Authors:  Diego Fernando Cabrera-Castellanos; Alejandro Aragón-Zavala; Gerardo Castañón-Ávila
Journal:  Sensors (Basel)       Date:  2021-12-01       Impact factor: 3.576

8.  Flying Ad Hoc Networks: A New Domain for Network Communications.

Authors:  Antonio Guillen-Perez; Maria-Dolores Cano
Journal:  Sensors (Basel)       Date:  2018-10-21       Impact factor: 3.576

9.  Energy-Efficient UAV Movement Control for Fair Communication Coverage: A Deep Reinforcement Learning Approach.

Authors:  Ibrahim A Nemer; Tarek R Sheltami; Slim Belhaiza; Ashraf S Mahmoud
Journal:  Sensors (Basel)       Date:  2022-03-01       Impact factor: 3.576

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.