Optimization-enabled user pairing algorithm for energy-efficient resource allocation for noma heterogeneous networks

被引:0
|
作者
Raghu K. [1 ]
Chandra Sekhar Reddy P. [1 ]
机构
[1] Department of Ece, Jawaharlal Nehru Technological University Hyderabad, Telangana
关键词
feedback artificial tree; nonorthogonal multiple access (NOMA); resource allocation; sea lion optimization algorithm; user pairing algorithm;
D O I
10.1515/joc-2022-0095
中图分类号
学科分类号
摘要
In recent times, nonorthogonal multiple access (NOMA) has appeared as an encouraging system for satisfying the requirements of 5G communications in alleviating the spectrum insufficiency problems. The purpose of NOMA in heterogeneous networks (HetNets) is to increase the spectrum exploitation with the cost of proficient allotment of resources. Therefore, to achieve effective resource assignments for NOMA HetNets, this study develops the best user pairing and efficient power allocation approach. Here, the newly devised optimization method, Feedback Sea Lion Optimization (FSLnO), is employed for achieving a less-difficult optimal solution when user pairing. In addition, the designed FSLnO is also accomplished for performing the energy-efficient power allocation process by enhancing the lesser energy effectiveness of the femtocell users. The Feedback Artificial Tree (FAT) and Sea Lion Optimization (SLnO) are combined to create the developed FSLnO algorithm. Additionally, according to evaluation metrics like achievable rate, energy efficiency, sum rate, and throughput, the developed approach performed better, with maximum values of 2.384 Mbits/s, 0.028 Mbits/Joules, 13.27 5 Mbits/s, and 0.154 Mbps, respectively. © 2022 Walter de Gruyter GmbH, Berlin/Boston 2022.
引用
收藏
页码:813 / 828
相关论文
共 50 条
  • [31] Energy-Efficient Resource Allocation for UAV-Enabled Information and Power Transfer with NOMA
    Najmeddin, Saif
    Aissa, Sonia
    Tahar, Sofiene
    2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2020,
  • [32] Energy-efficient UAV communication: A NOMA scheme with resource allocation and trajectory optimization
    Jin, Huilong
    Zhou, Yucong
    Jin, Xiaozi
    Zhang, Shuang
    PLOS ONE, 2024, 19 (04):
  • [33] Energy-Efficient Resource Allocation for NOMA-MEC Networks With Imperfect CSI
    Fang, Fang
    Wang, Kaidi
    Ding, Zhiguo
    Leung, Victor C. M.
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2021, 69 (05) : 3436 - 3449
  • [34] Joint User Pairing and Resource Allocation in a SWIPT-Enabled Cooperative NOMA System
    Wu, Mengru
    Song, Qingyang
    Guo, Lei
    Jamalipour, Abbas
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 70 (07) : 6826 - 6840
  • [35] Energy-Efficient Resource Allocation for Fractional Frequency Reuse in Heterogeneous Networks
    Davaslioglu, Kemal
    Coskun, Cemil Can
    Ayanoglu, Ender
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2015, 14 (10) : 5484 - 5497
  • [36] Energy-efficient resource allocation in heterogeneous networks with cell range expansion
    Jiang, Jiamo
    Peng, Mugen
    Li, Lei
    Wang, Wenbo
    IET NETWORKS, 2015, 4 (04) : 209 - 219
  • [37] Energy-efficient resource allocation in macrocell-smallcell heterogeneous networks
    Feng L.
    Chen Y.
    Wang X.
    1600, Engineering and Technology Publishing (11) : 609 - 614
  • [38] Energy-Efficient Resource Allocation in CoMP-SWIPT Heterogeneous Networks
    Tang, Jie
    So, Daniel K. C.
    Shojaeifard, Arman
    Wong, Kai-Kit
    2017 IEEE/CIC INTERNATIONAL CONFERENCE ON COMMUNICATIONS IN CHINA (ICCC), 2017, : 132 - 137
  • [39] Energy-Efficient Resource Allocation for Federated Learning in NOMA-Enabled and Relay-Assisted Internet of Things Networks
    Al-Abiad, Mohammed S.
    Hassan, Md. Zoheb
    Hossain, Md. Jahangir
    IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (24) : 24736 - 24753
  • [40] Energy-Efficient Resource Allocation for Different QoS Requirements in Heterogeneous Networks
    Wang, Yuanshuang
    Zhao, Ning
    Wang, Xia
    Miao, Guowang
    2016 IEEE 83RD VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING), 2016,