A Novel Massive MIMO Beam Domain Channel Model

被引:4
|
作者
Lai, Fan [1 ,2 ]
Wang, Cheng-Xiang [1 ,2 ]
Huang, Jie [1 ,2 ]
Gao, Xiqi [1 ,2 ]
Zheng, Fu-Chun [1 ,2 ]
机构
[1] Southeast Univ, Sch Informat Sci & Engn, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
[2] Purple Mt Labs, Nanjing 211111, Peoples R China
来源
2020 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC) | 2020年
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
BDCM; massive MIMO; near-field effect; computational complexity; statistical properties;
D O I
10.1109/wcnc45663.2020.9120569
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A novel beam domain channel model (BDCM) for massive multiple-input multiple-output (MIMO) communication systems has been proposed in this paper. The near-field effect and spherical wavefront are firstly assumed in the proposed model, which is different from the conventional BDCM for MIMO based on the far-field effect and plane wavefront assumption. The proposed novel BDCM is the transformation of an existing geometry-based stochastic model (GBSM) from the antenna domain into beam domain. The space-time non-stationarity is also modeled in the novel BDCM. Moreover, the comparison of computational complexity for both models is studied. Based on the numerical analysis, comparison of cluster-level statistical properties between the proposed BDCM and existing GBSM has shown that there exists little difference in the space, time, and frequency correlation properties for two models. Also, based on the simulation, coherence bandwidths of the two models in different scenarios are almost the same. The computational complexity of the novel BDCM is much lower than the existing GBSM. It can be observed that the proposed novel BDCM has similar statistical properties to the existing GBSM at the clusterlevel. The proposed BDCM has less complexity and is therefore more convenient for information theory and signal processing research than the conventional GBSMs.
引用
收藏
页数:6
相关论文
共 50 条
  • [21] Pilot Beam Pattern Design for Channel Estimation in Massive MIMO Systems
    Noh, Song
    Zoltowski, Michael D.
    Sung, Youngchul
    Love, David J.
    IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2014, 8 (05) : 787 - 801
  • [22] Closed-Loop Beam Alignment for Massive MIMO Channel Estimation
    Duly, Andrew J.
    Kim, Taejoon
    Love, David J.
    Krogmeier, James V.
    IEEE COMMUNICATIONS LETTERS, 2014, 18 (08) : 1439 - 1442
  • [23] Angle-Domain Aided UL/DL Channel Estimation for Wideband mmWave Massive MIMO Systems With Beam Squint
    Jian, Mengnan
    Gao, Feifei
    Tian, Zhi
    Jin, Shi
    Ma, Shaodan
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2019, 18 (07) : 3515 - 3527
  • [24] Sparse Bayesian Learning Using Complex t-Prior for Beam-Domain Massive MIMO Channel Estimation
    Furuta, Kengo
    Takahashi, Takumi
    Ochiai, Hideki
    IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, 2024, 5 : 5905 - 5920
  • [25] Low-complexity beam-domain channel estimation and power allocation in hybrid architecture massive MIMO systems
    Xiao Chen
    Zaichen Zhang
    Liang Wu
    Jian Dang
    EURASIP Journal on Wireless Communications and Networking, 2019
  • [26] Low-complexity beam-domain channel estimation and power allocation in hybrid architecture massive MIMO systems
    Chen, Xiao
    Zhang, Zaichen
    Wu, Liang
    Dang, Jian
    EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2019, 2019 (01)
  • [27] A Novel 2D Non-Stationary Wideband Massive MIMO Channel Model
    Lopez, Carlos L.
    Wang, Cheng-Xiang
    Feng, Rui
    2016 IEEE 21ST INTERNATIONAL WORKSHOP ON COMPUTER AIDED MODELLING AND DESIGN OF COMMUNICATION LINKS AND NETWORKS (CAMAD), 2016, : 207 - 212
  • [28] A correlation-based stochastic model for massive MIMO channel
    Liu, Yang
    Li, Gang
    Wang, Chengxiang
    CHINA COMMUNICATIONS, 2024, 21 (01) : 175 - 187
  • [29] A Correlation-Based Stochastic Model for Massive MIMO Channel
    Yang Liu
    Gang Li
    Chengxiang Wang
    China Communications, 2024, 21 (01) : 175 - 187
  • [30] Channel Hardening in Massive MIMO: Model Parameters and Experimental Assessment
    Gunnarsson, Sara
    Flordelis, Jose
    Van der Perre, Liesbet
    Tufvesson, Fredrik
    IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, 2020, 1 : 501 - 512