Enhancing the Energy Efficiency of mmWave Massive MIMO by Modifying the RF Circuit Configuration

被引:13
作者
Uthansakul, Peerapong [1 ]
Khan, Arfat Ahmad [1 ]
机构
[1] Suranaree Univ Technol, Sch Telecommun Engn, Nakhon Ratchasima 30000, Thailand
关键词
hybrid analog; digital precoding and decoding; mmWave communications; RF signal mapping; Massive MIMO; optimization; power Consumption; Energy Efficiency; MILLIMETER-WAVE COMMUNICATIONS; HYBRID ANALOG; ANTENNA-ARRAY; NETWORKS; CAPACITY; SYSTEMS;
D O I
10.3390/en12224356
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
Hybrid architectures are used in the Millimeter wave (mmWave) Massive MIMO systems, which use a smaller number of RF chains and reduces the power and energy consumption of the mmWave Massive MIMO systems. However, the majority of the hybrid architectures employs the conventional circuit configuration by connecting each of the RF chains with all the transmitting antennas at the base station. As a result, the conventional circuit configuration requires a large number of phase shifters, combiners, and low-end amplifiers. In this paper, we modify the RF circuit configuration by connecting each of the RF chains with some of the transmitting antennas of mmWave Massive MIMO. Furthermore, the hybrid analogue/digital precoders and decoders along with the overall circuit power consumptions are modelled for the modified RF circuit configuration. In addition, we propose the alternating optimization algorithm to enhance the optimal energy efficiency and compute the optimal system parameters of the mmWave Massive MIMO system. The proposed framework provides deeper insights of the optimal system parameters in terms of throughput, consumed power and the corresponding energy efficiency. Finally, the simulation results validate the proposed framework, where it can be seen that the proposed algorithm significantly reduces the power and energy consumptions, with a little compromise on the system spectral gain.
引用
收藏
页数:23
相关论文
共 50 条
  • [31] Energy and Spectral Efficiency Tradeoff With User Association and Power Coordination in Massive MIMO Enabled HetNets
    Hao, Yuanyuan
    Ni, Qiang
    Li, Hai
    Hou, Shujuan
    IEEE COMMUNICATIONS LETTERS, 2016, 20 (10) : 2091 - 2094
  • [32] Energy-Efficient Power Allocation in Uplink mmWave Massive MIMO With NOMA
    Zeng, Ming
    Hao, Wanming
    Dobre, Octavia A.
    Poor, H. Vincent
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (03) : 3000 - 3004
  • [33] Massive MIMO in LTE Systems: Energy and Spectral Efficiency
    Gizlenmistir, Yazarlar
    2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2018,
  • [34] Energy Efficiency of Massive-MIMO Heterogeneous Network
    Bao, Hui
    PengboFang
    PROCEEDINGS OF THE 2015 5TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCES AND AUTOMATION ENGINEERING, 2016, 42 : 571 - 574
  • [35] Spectral and Energy Efficiency Analysis with Massive MIMO Systems
    Fang, Xin
    Zhang, Yufei
    Cao, Haiyan
    Ying, Na
    2015 IEEE 16TH INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGY (ICCT), 2015, : 837 - 843
  • [36] Energy Efficiency in Hybrid Beamforming Large-scale mmWave Multiuser MIMO with Spatial Modulation
    Yuezgeccioglu, Merve
    Zappone, Alessi
    Jorswieck, Eduard
    2018 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2018,
  • [37] Energy Efficiency Optimization for Massive MIMO Non-Orthogonal Unicast and Multicast Transmission with Statistical CSI
    Wang, Wenjin
    Huang, Yufei
    You, Li
    Xiong, Jiayuan
    Li, Jiamin
    Gao, Xiqi
    ELECTRONICS, 2019, 8 (08)
  • [38] Trade-Off Energy and Spectral Efficiency in a Downlink Massive MIMO System
    Salh, A.
    Audah, L.
    Shah, N. S. M.
    Hamzah, S. A.
    WIRELESS PERSONAL COMMUNICATIONS, 2019, 106 (02) : 897 - 910
  • [39] Energy-Efficient Hybrid Precoding With Low Complexity for mmWave Massive MIMO Systems
    Liu, Yang
    Feng, Qingxia
    Wu, Qiong
    Zhang, Yinghui
    Jin, Minglu
    Qiu, Tianshuang
    IEEE ACCESS, 2019, 7 : 95021 - 95032
  • [40] Energy Efficiency Optimization Based on Power Allocation in Massive MIMO Downlink Systems
    Liu, Hongmei
    Deng, Honggui
    Yi, Yougen
    Zhu, Zaoxing
    Liu, Gang
    Zhang, Jie
    SYMMETRY-BASEL, 2022, 14 (06):