Federated Learning Meets Intelligence Reflection Surface in Drones for Enabling 6G Networks: Challenges and Opportunities

被引:6
|
作者
Shvetsov, Alexey V. [1 ]
Alsamhi, Saeed Hamood [2 ]
Hawbani, Ammar [3 ]
Kumar, Santosh [4 ]
Srivastava, Sumit [5 ]
Agarwal, Sweta [6 ,7 ]
Rajput, Navin Singh [8 ]
Alammari, Amr A. [2 ]
Nashwan, Farhan M. A. [2 ]
机构
[1] Moscow Polytech Univ, Dept Smart Technol, Moscow 107023, Russia
[2] Ibb Univ, Fac Engn, Elect Engn Dept, Ibb, Yemen
[3] Shenyang Aerosp Univ, Sch Comp Sci, Shenyang 110136, Peoples R China
[4] IIIT Naya Raipur, Dept CSE, Chhattisgarh 493661, India
[5] MJP Rohilkhand Univ, Dept Elect & Commun Engn, FET, Bareilly 243006, Uttar Pradesh, India
[6] Invertis Univ, Dept EC, Bareilly 243123, Uttar Pradesh, India
[7] Invertis Univ, Dept EE, Bareilly 243123, Uttar Pradesh, India
[8] Banaras Hindu Univ Varanasi, Indian Inst Technol, Dept Elect Engn, Varanasi 221005, Uttar Pradesh, India
来源
IEEE ACCESS | 2023年 / 11卷
关键词
6G; drones; drone swarm; federated learning; IoT; IRS; smart environment; PASSIVE BEAMFORMING DESIGN; SUM-RATE MAXIMIZATION; RESOURCE-ALLOCATION; UAV COMMUNICATIONS; WIRELESS COMMUNICATIONS; ENERGY EFFICIENCY; TRAJECTORY OPTIMIZATION; JOINT OPTIMIZATION; MULTIPLE-ACCESS; COMMUNICATION;
D O I
10.1109/ACCESS.2023.3323399
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The combination of drones and Intelligent Reflecting Surfaces (IRS) have emerged as potential technologies for improving the performance of six Generation (6G) communication networks by proactively modifying wireless communication through smart signal reflection and manoeuvre control. By deploying the IRS on drones, it becomes possible to improve the coverage and reliability of the communication network while reducing energy consumption and costs. Furthermore, integrating IRS with Federated Learning (FL) can further boost the performance of the drone network by enabling collaborative learning among multiple drones, leading to better and more efficient decision-making and holding great promise for enabling 6G communication networks. Therefore, we present a novel framework for FL meets IRS in drones for enabling 6G. In this framework, multiple IRS-equipped drone swarm are deployed to form a distributed wireless network, where FL techniques are used to collaborate with the learning process and optimize the reflection coefficients of each drone-IRS. This allows drone swarm to adapt to changing communication environments and improve the coverage and quality of wireless communication services. Integrating FL and IRS into drones offers several advantages over traditional wireless communication networks, including rapid deployment in emergencies or disasters, improved coverage and quality of communication services, and increased accessibility to remote areas. Finally, we highlight the challenges and opportunities of integrating FL and IRS into drones for researchers interested in drone networks. We also help drive innovation in developing 6G communication networks.
引用
收藏
页码:130860 / 130887
页数:28
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