Energy consumption optimization in 5G networks using multilevel beamforming and large scale antenna systems

被引:0
|
作者
Salem, Fatma Ezzahra [1 ,2 ]
Tall, Abdoulaye [2 ]
Altman, Zwi [2 ]
Gati, Azeddine [2 ]
机构
[1] Cent Supelec, 3 Rue Joliot Curie, F-91192 Gif Sur Yvette, France
[2] Orange Labs, 38-40 Rue Gen Leclerc, F-92794 Issy Les Moulineaux, France
来源
2016 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE | 2016年
关键词
Energy consumption; Green cellular networks; base station power model; multilevel codebook; Green policy management;
D O I
暂无
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Cellular networks are witnessing an exponential traffic growth leading to an increase in Energy Consumption (EC), and having both environmental and economic impact. Recently, different approaches have been studied to build Green cellular networks focusing mainly on the Base Stations (BSs) as the access network represents 80% of the total wireless network consumption [1] [2]. One of the promising solutions for increasing throughput and reducing EC is the deployment of large antenna arrays, known as Large Scale Antenna Systems (LSAS) [3] [4] [5] [6], that can transmit highly focused beams. In the present work, we focus on the use of an advanced BS power model developed within the GreenTouch project [7] [8]. This model allows to quantify the power consumption of a reference scenario comprising multiple sites with standard BS antennas, and then compare it to a LSAS solution implementing multilevel beamforming. We then exploit the LSAS merits to get greener deployment with less BSs, some of which can be turned off as a function of the traffic demand. The coverage areas of each cell can be modified, by updating the codebook of beams. We finally investigate different network configurations which represent distinct trade-offs between EC and capacity. We propose a methodology to represent and design green policies for managing the network which select the desired operating points. Detailed simulation results illustrate the proposed methodology.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] Effective spectrum sensing using cognitive radios in 5G and wireless body area networks
    Alqahtani, Abdulrahman Saad
    Changalasetty, Suresh Babu
    Parthasarathy, P.
    Thota, Lalitha Saroja
    Mubarakali, Azath
    COMPUTERS & ELECTRICAL ENGINEERING, 2023, 105
  • [42] Optimizing Energy Consumption for Big Data Collection in Large-Scale Wireless Sensor Networks With Mobile Collectors
    Ang, Kenneth Li-Minn
    Seng, Jasmine Kah Phooi
    Zungeru, Adamu Murtala
    IEEE SYSTEMS JOURNAL, 2018, 12 (01): : 616 - 626
  • [43] Energy-Efficient Computation Offloading with Privacy Preservation for Edge Computing-Enabled 5G Networks
    Liu, Xihua
    Xu, Xiaolong
    Yuan, Yuan
    Zhang, Xuyun
    Doug, Wanchun
    2019 INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA), 2019, : 176 - 181
  • [44] Energy-Efficient QoE-Driven Radio Resource Management Method for 5G and Beyond Networks
    Beshley, Mykola
    Kryvinska, Natalia
    Beshley, Halyna
    IEEE ACCESS, 2022, 10 : 131691 - 131710
  • [45] Towards Sustainable 5G Networks: A Proposed Coordination Solution for Macro and Pico Cells to Optimize Energy Efficiency
    Fall, Macoumba
    Balboul, Younes
    Fattah, Mohammed
    Mazer, Said
    El Bekkali, Moulhime
    Kora, Ahmed D.
    IEEE ACCESS, 2023, 11 : 50794 - 50804
  • [46] An ns3-based Energy Module of 5G NR User Equipments for Millimeter Wave Networks
    Sen, Argha
    Mondal, Abhijit
    Palit, Basabdatta
    Jayatheerthan, Jay
    Pau, Krishna
    Chakraborty, Sandip
    IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (IEEE INFOCOM WKSHPS 2021), 2021,
  • [47] Joint Visual Coverage and Energy Consumption Optimization for UAV-Aided 5G-and-Beyond Communications
    Huang, Zhengrui
    Wang, Shujie
    IEEE Transactions on Vehicular Technology, 2024, 73 (12) : 19417 - 19431
  • [48] Architecture and Methodology for Green MEC Services Using Programmable Data Planes in 5G and Beyond Networks
    Andres Brito, Jorge
    Ignacio Moreno, Jose
    Contreras, Luis M.
    Blanco Caamano, Marta
    2024 23RD IFIP NETWORKING CONFERENCE, IFIP NETWORKING 2024, 2024, : 738 - 743
  • [49] Minimizing Energy Consumption in Large Scale Wireless Sensor Network using Adaptive Duty Cycle Algorithm
    Dongre, Laxmi D.
    Gulhane, Veena
    2014 INTERNATIONAL CONFERENCE FOR CONVERGENCE OF TECHNOLOGY (I2CT), 2014,
  • [50] Optimising dimming systems for visual experience and energy consumption using genetic algorithms and neural networks
    Bian, Wenkai
    Hu, Wenye
    ENERGY AND BUILDINGS, 2025, 329