On the Resource Allocation of Hierarchical NOMA for Fog-RAN with Energy Harvesting

被引:0
|
作者
Papanikolaou, Vasilis K. [1 ]
Mitsiou, Nikos A. [1 ]
Diamantoulakis, Panagiotis D. [1 ]
Goudos, Sotirios K. [2 ]
Karagiannidis, George K. [1 ]
机构
[1] Aristotle Univ Thessaloniki, Dept Elect & Comp Engn, GR-54124 Thessaloniki, Greece
[2] Aristotle Univ Thessaloniki, Dept Phys, GR-54124 Thessaloniki, Greece
来源
2021 10TH INTERNATIONAL CONFERENCE ON MODERN CIRCUITS AND SYSTEMS TECHNOLOGIES (MOCAST) | 2021年
关键词
non-orthogonal multiple access (noma); hierarchical noma; convex optimization; resource allocation; energy harvesting; NETWORKS; ACCESS;
D O I
10.1109/MOCAST52088.2021.9493358
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, we introduce a multiple access protocol, termed hierarchical non-orthogonal multiple access (HiNOMA), optimized for fog-radio access networks (F-RANs). Resource allocation optimization is deemed critical in order to guarantee the users' fairness in the network, while energy efficiency can be increased through energy harvesting (EH) at the user equipment (UE) nodes. Therefore, the HiNOMA protocol with energy harvesting capabilities is examined for F-RANs, leading to the optimization of the proportional fairness metric. Finally, numerical results reveal the effectiveness of the joint design and the interesting trade-off between harvested power and achievable rate in the case of F-RAN.
引用
收藏
页数:4
相关论文
共 50 条
  • [21] AirFogComp: Over-the-Air-Fog Computation for Federated Learning Over Fog-RAN
    Park, Eunhyuk
    Park, Seok-Hwan
    2024 FIFTEENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS, ICUFN 2024, 2024, : 395 - 397
  • [22] Robust Wireless Fronthauling Methods for Decentralized Deep Learning in Fog-RAN
    Lee, Hoon
    Kim, Junbeom
    Park, Seok-Hwan
    12TH INTERNATIONAL CONFERENCE ON ICT CONVERGENCE (ICTC 2021): BEYOND THE PANDEMIC ERA WITH ICT CONVERGENCE INNOVATION, 2021, : 315 - 317
  • [23] RESOURCE ALLOCATION IN NOMA-BASED FOG RADIO ACCESS NETWORKS
    Zhang, Haijun
    Qiu, Yu
    Long, Keping
    Karagiannidis, George K.
    Wang, Xianbin
    Nallanathan, Arumugam
    IEEE WIRELESS COMMUNICATIONS, 2018, 25 (03) : 110 - 115
  • [24] Hierarchical Reinforcement Learning Based Resource Allocation for RAN Slicing
    Anil Akyildiz, Hasan
    Faruk Gemici, Omer
    Hokelek, Ibrahim
    Ali Cirpan, Hakan
    IEEE ACCESS, 2024, 12 : 75818 - 75831
  • [25] Joint resource allocation for cognitive OFDM-NOMA systems with energy harvesting in green IoT
    Na, Zhenyu
    Wang, Xin
    Shi, Jingcheng
    Liu, Chungang
    Liu, Yue
    Gao, Zihe
    AD HOC NETWORKS, 2020, 107
  • [26] Energy Harvesting and Resource Allocation for Cache-Enabled UAV Based IoT NOMA Networks
    Li, Huifang
    Li, Jing
    Liu, Meng
    Ding, Zhiguo
    Gong, Fengkui
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 70 (09) : 9625 - 9630
  • [27] Optimal and Fair Energy Efficient Resource Allocation for Energy Harvesting-Enabled-PD-NOMA-Based HetNets
    Moltafet, Mohammad
    Azmi, Paeiz
    Mokari, Nader
    Javan, Mohammad Reza
    Mokdad, Ali
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2018, 17 (03) : 2054 - 2067
  • [28] Energy-Efficient Hierarchical Resource Allocation in Uplink-Downlink Decoupled NOMA HetNets
    Dong, Shaofeng
    Zhan, Jinsong
    Hu, Wei
    Mohajer, Amin
    Bavaghar, Maryam
    Mirzaei, Abbas
    IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2023, 20 (03): : 3380 - 3395
  • [29] Resource Allocation in Fog RAN for Heterogeneous IoT Environments based on Reinforcement Learning
    Nassar, Almuthanna
    Yilmaz, Yasin
    ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2019,
  • [30] Resource allocation for NOMA-based multicast cognitive radio networks with energy-harvesting relays
    Baidas, Mohammed W.
    Amini, Mohammad Reza
    PHYSICAL COMMUNICATION, 2020, 42