Projection Based Feedback Compression for FDD Massive MIMO Systems

被引:0
|
作者
Han, Yonghee [1 ]
Shin, Wonjae [1 ,2 ]
Lee, Jungwoo [1 ]
机构
[1] Seoul Natl Univ, INMAC, Dept Elect & Comp Engn, Seoul, South Korea
[2] Samsung Elect Co Ltd, DMC R&D Ctr, Commun Res Team, Suwon, South Korea
关键词
WIRELESS;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In frequency division duplex (FDD) multiple-input multiple-output (MIMO) systems, channel state information (CSI) is conveyed to the transmitters through feedback link. Since the amount of feedback needs to grow linearly with the number of transmit antennas, feedback overhead becomes overwhelming in massive MIMO regime and it has been of great interest to reduce the feedback overhead. In this paper, a feedback protocol using adaptive compression for FDD massive MIMO systems is proposed. Under the assumption of spatially and temporally correlated massive MIMO channel, the proposed scheme compresses CSI by projecting a vector in M (the number of transmit antennas) dimensional space into a lower dimensional subspace. To find an appropriate subspace, long-term statistics of the channel (spatial and temporal correlation), which can be obtained relatively easily, are exploited. Simulation results show that the proposed scheme can reduce the amount of feedback significantly yielding a marginal performance loss.
引用
收藏
页码:364 / 369
页数:6
相关论文
共 50 条
  • [1] Projection-Based Differential Feedback for FDD Massive MIMO Systems
    Han, Yonghee
    Shin, Wonjae
    Lee, Jungwoo
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2017, 66 (01) : 202 - 212
  • [2] Antenna Grouping Based Feedback Compression for FDD-Based Massive MIMO Systems
    Lee, Byungju
    Choi, Junil
    Seol, Ji-Yun
    Love, David J.
    Shim, Byonghyo
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2015, 63 (09) : 3261 - 3274
  • [3] Exploiting Dominant Eigendirections for Feedback Compression for FDD-based Massive MIMO Systems
    Lee, Byungju
    Ji, Hyoungju
    Love, David J.
    Shim, Byonghyo
    2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2016,
  • [4] A Novel Compression CSI Feedback based on Deep Learning for FDD Massive MIMO Systems
    Wang, Yuting
    Zhang, Yibin
    Sun, Jinlong
    Gui, Guan
    Ohtsuki, Tomoaki
    Adachi, Fumiyuki
    2021 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2021,
  • [5] Efficient Lossless Feedback Compression for FDD Massive MIMO
    Ndiaye, Papis
    Diallo, Moussa
    Mbaye, Moustapha
    Diop, Idy
    Seye, Madoune Robert
    2019 15TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE (IWCMC), 2019, : 579 - 585
  • [6] Path Selection Based Feedback Reduction for FDD Massive MIMO Systems
    Kim, Seungnyun
    Choi, Jun Won
    Shim, Byonghyo
    2019 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2019,
  • [7] Downlink Channel Feedback for FDD Massive MIMO Systems via Tensor Compression and Sampling
    Ibrahim, Mohamed Salah
    Kanatsoulis, Charilaos, I
    Sidiropoulos, Nicholas D.
    2020 54TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, 2020, : 27 - 31
  • [8] Sparsity Learning-Based CSI Feedback for FDD Massive MIMO Systems
    Zeng, Wenbo
    He, Yigang
    Li, Bing
    Wang, Shudong
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2021, 10 (03) : 585 - 588
  • [9] A Covariance-Based Hybrid Channel Feedback in FDD Massive MIMO Systems
    Qiu, Shuang
    Gesbert, David
    Chen, Da
    Jiang, Tao
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2019, 67 (12) : 8365 - 8377
  • [10] CSI Feedback Method Based on Deep Learning for FDD Massive MIMO Systems
    Liao Y.
    Yao H.-M.
    Hua Y.-X.
    Zhao Y.
    Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2020, 48 (06): : 1182 - 1189