Interference Management in Cellular-Connected Internet of Drones Networks With Drone-Pairing and Uplink Rate-Splitting Multiple Access

被引:22
作者
Hassan, Md Zoheb [1 ]
Kaddoum, Georges [1 ]
Akhrif, Ouassima [1 ]
机构
[1] Ecole Technol Super, Dept Elect Engn, Montreal, PQ H3C 1K3, Canada
关键词
Drones; Interference; Uplink; Resource management; Optimization; Cellular networks; Sensors; Interference management; Internet of Drones (IoD); rate-splitting multiple access; resource allocation; POWER-CONTROL; UAV; COMMUNICATION; OPTIMIZATION; ALLOCATION; SECURITY; DESIGN;
D O I
10.1109/JIOT.2022.3152382
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Interference management is a key challenge for cellular-connected Internet of Drones (IoD) networks that employ multiple cellular-connected hovering drones for data acquisition in surveillance and monitoring applications. This article proposes a novel resource optimization framework for managing interference in cellular-connected IoD networks. Specifically, the envisioned system divides the set of transmitting drones into distinct drone pairs, where the paired drones simultaneously transmit over the same radio resource blocks (RRBs). Each drone pair is assigned a set of orthogonal RRBs for data transmission, where these RRBs are shared with the terrestrial cellular network as well. An uplink rate-splitting multiple access scheme is employed to mitigate the interdrone interference at the drone pairs, and an RRB pricing method is exploited to control the interference between the aerial and cellular communication links. Our goal is to maximize the uplink capacity of the IoD network while reducing interference over the shared RRBs between the IoD and cellular networks. Toward this goal, a joint optimization of the drones' transmit power allocation, drone pairing, and RRB scheduling among the drone pairs is presented. In order to obtain an efficient suboptimal solution, an iterative optimization is devised. Particularly, the presented joint optimization problem is decomposed into three subproblems for transmit power allocation, drone pairing and RRB scheduling, and RRB price update. By solving theses subproblems iteratively, a convergent rate-splitting-empowered resource allocation and clustering for interference management (REACT) algorithm is proposed. Extensive simulations are conducted to verify the effectiveness of the proposed REACT algorithm over several benchmark schemes.
引用
收藏
页码:16060 / 16079
页数:20
相关论文
共 45 条
  • [31] Rate-Splitting Multiple Access and Dynamic User Clustering for Sum-Rate Maximization in Multiple RISs-Aided Uplink mmWave System
    Katwe, Mayur
    Singh, Keshav
    Clerckx, Bruno
    Li, Chih-Peng
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2022, 70 (11) : 7365 - 7383
  • [32] Rate-Splitting Multiple Access Networks Assisted by Aerial Intelligent Reflecting Surfaces
    Lima, Brena Kelly S.
    Dinis, Rui
    Da Costa, Daniel Benevides
    Beko, Marko
    Oliveira, Rodolfo
    Vigelis, Rui
    Debbah, Merouane
    2022 IEEE LATIN-AMERICAN CONFERENCE ON COMMUNICATIONS (LATINCOM), 2022,
  • [33] Rate-Splitting Multiple Access for UAV-Based RIS-Enabled Interference-Limited Vehicular Communication System
    Bansal, Ankur
    Agrawal, Neelima
    Singh, Keshav
    IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 8 (01): : 936 - 948
  • [34] Transformer-Empowered Predictive Beamforming for Rate-Splitting Multiple Access in Non-Terrestrial Networks
    Zhang, Shengyu
    Zhang, Shiyao
    Yuan, Weijie
    Quek, Tony Q. S.
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (12) : 19776 - 19788
  • [35] Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting
    Jaafar, Wael
    Naser, Shimaa
    Muhaidat, Sami
    Sofotasios, Paschalis C.
    Yanikomeroglu, Halim
    IEEE OPEN JOURNAL OF VEHICULAR TECHNOLOGY, 2020, 1 : 372 - 392
  • [36] Performance analysis of rate-splitting multiple access in intelligent reflecting surface-assisted uplink hybrid satellite-terrestrial networks
    Can, Mehmet
    Altunbas, Ibrahim
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2024, 37 (17)
  • [37] Efficient Rate-Splitting Multiple Access for the Internet of Vehicles: Federated Edge Learning and Latency Minimization
    Zhang, Shengyu
    Zhang, Shiyao
    Yuan, Weijie
    Li, Yonghui
    Hanzo, Lajos
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2023, 41 (05) : 1468 - 1483
  • [38] Decoupled Association With Rate Splitting Multiple Access in UAV-Assisted Cellular Networks Using Multi-Agent Deep Reinforcement Learning
    Ji, Jiequ
    Cai, Lin
    Zhu, Kun
    Niyato, Dusit
    IEEE TRANSACTIONS ON MOBILE COMPUTING, 2024, 23 (03) : 2186 - 2201
  • [39] Rate-Splitting Multiple Access in Multi-Cell Dense Networks: A Stochastic Geometry Approach
    Zhu, Qiao
    Qian, Zhihong
    Clerckx, Bruno
    Wang, Xue
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2023, 72 (12) : 15844 - 15857
  • [40] Rate-Splitting Multiple Access for Semantic-Aware Networks: An Age of Incorrect Information Perspective
    Dizdar, Onur
    Wang, Stephen
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2024, 13 (04) : 1168 - 1172