Energy-Efficient Use of Licensed and Unlicensed Bands in D2D-Assisted Cellular Network Systems

被引:1
|
作者
Chung, Yao-Liang [1 ]
机构
[1] Natl Taiwan Ocean Univ, Dept Commun Nav & Control Engn, Keelung 20224, Taiwan
关键词
energy-efficient; efficiency; licensed and unlicensed bands; device-to-device (D2D); 5th-generation (5G) cellular systems;
D O I
10.3390/en10111893
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
To date, the amount of research conducted regarding the subject of energy-efficient transmission in device-to-device (D2D)-assisted cellular network systems simultaneously utilizing both licensed and unlicensed bands is lacking. This topic is of substantial relevance to emerging 5th-generation (5G) cellular network systems, so the present study was conducted in order to address it in a practical manner. Specifically, this study proposes a simple yet effective algorithm aimed at ensuring efficient energy usage when such network systems make transmissions while utilizing both licensed and unlicensed bands. Based on novel system configurations with respect to bandwidth and link mode configurations, the proposed D2D-assisted transmission algorithm was designed with a system-level perspective in mind in order to yield greater efficiency in terms of transmission mode selection and link mode selection. As a result of these features, the proposed algorithm can not only maintain acceptable rates of transmission for all the connected users, but can also enhance system performance by a significant degree in terms of both energy efficiency and connection efficiency. Moreover, the results of simulations conducted to test the algorithm indicate that it is not only feasible, but, given its simple yet effective design, also easy to implement, such that it can serve as a valuable reference for the operators of 5G networks.
引用
收藏
页数:16
相关论文
共 50 条
  • [41] Energy-Efficient Resource Allocation for Heterogeneous Network with Grouping D2D
    Jing Cao
    Xin Song
    Siyang Xu
    Zhigang Xie
    Yanbo Xue
    中国通信, 2021, 18 (03) : 132 - 141
  • [42] Dual-Regularized Feedback and Precoding for D2D-Assisted MIMO Systems
    Chen, Junting
    Yin, Haifan
    Cottatellucci, Laura
    Gesbert, David
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2017, 16 (10) : 6854 - 6867
  • [43] Energy-Efficient Power Allocation for D2D Communication underlaying Cellular Networks
    Shi, Fengfeng
    Chen, Ruilu
    Shen, Hong
    Wang, Jiaheng
    Zhao, Chunming
    MOBILE NETWORKS & APPLICATIONS, 2022, 27 (02): : 483 - 491
  • [44] Resource Allocation for Energy-Efficient Transmission in D2D Underlaid Cellular Networks
    Xu, Hao
    Pan, Yijin
    Shi, Jianfeng
    Yang, Zhaohui
    Huang, Nuo
    Chen, Ming
    2016 IEEE GLOBECOM WORKSHOPS (GC WKSHPS), 2016,
  • [45] Energy-Efficient Power Allocation for D2D Communication underlaying Cellular Networks
    Fengfeng Shi
    Ruilu Chen
    Hong Shen
    Jiaheng Wang
    Chunming Zhao
    Mobile Networks and Applications, 2022, 27 : 483 - 491
  • [46] Energy-Efficient Matching for Resource Allocation in D2D Enabled Cellular Networks
    Zhou, Zhenyu
    Ota, Kaoru
    Dong, Mianxiong
    Xu, Chen
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2017, 66 (06) : 5256 - 5268
  • [47] Energy-Efficient Link Adaptation for Secure D2D Underlaid Cellular Networks
    Oh, Jintaek
    Kwon, Younggap
    Hwang, Taewon
    2016 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2016,
  • [48] Beef Up mmWave Dense Cellular Networks With D2D-Assisted Cooperative Edge Caching
    Wu, Wen
    Zhang, Ning
    Cheng, Nan
    Tang, Yujie
    Aldubaikhy, Khalid
    Shen, Xuemin
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (04) : 3890 - 3904
  • [49] Joint access and backhaul resource allocation for D2D-assisted dense mmWave cellular networks
    Dai, Xiangwen
    Gui, Jinsong
    COMPUTER NETWORKS, 2020, 183 (183)
  • [50] Soft Frequency Reuse-Based Resource Allocation for D2D Communications Using Both Licensed and Unlicensed Bands
    Li, Mingfu
    2019 ELEVENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS (ICUFN 2019), 2019, : 384 - 386