TY - GEN
T1 - DNN Based Multi-Path Beamforming for FDD Millimeter-Wave Massive MIMO Systems
AU - Xu, Ke
AU - Zheng, Fu Chun
AU - Cao, Pan
AU - Xu, Hongguang
AU - Zhu, Xu
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/9/13
Y1 - 2021/9/13
N2 - In this paper, we propose a deep neural network (DNN) based beamforming scheme for frequency-division-duplex (FDD) millimeter-Wave (mmWave) massive multipleinput multiple-output (MIMO) systems. Different from the time-division-duplex (TDD) systems, for FDD systems the channel reciprocity between the down-link (DL) and up-link (UL) channels does not hold in general, requiring an extra channel state information (CSI) feedback stage. Based on the previous theoretical analysis and measurements, however, partial reciprocities, including the spatial directional angles and number of propagation paths, do exist for FDD mmWave systems. With this partial reciprocity, we propose a multi-path beamforming scheme with a predefined codebook. Different from most previous works that only focus on one dominant path of each mobile station (MS), this work considers a multi-path scenario where the proposed scheme identifies all the propagation paths of all MSs, and selects the optimal combination of codewords with the help of a DNN that not only overcomes angle ambiguity but also significantly reduces computational complexity.
AB - In this paper, we propose a deep neural network (DNN) based beamforming scheme for frequency-division-duplex (FDD) millimeter-Wave (mmWave) massive multipleinput multiple-output (MIMO) systems. Different from the time-division-duplex (TDD) systems, for FDD systems the channel reciprocity between the down-link (DL) and up-link (UL) channels does not hold in general, requiring an extra channel state information (CSI) feedback stage. Based on the previous theoretical analysis and measurements, however, partial reciprocities, including the spatial directional angles and number of propagation paths, do exist for FDD mmWave systems. With this partial reciprocity, we propose a multi-path beamforming scheme with a predefined codebook. Different from most previous works that only focus on one dominant path of each mobile station (MS), this work considers a multi-path scenario where the proposed scheme identifies all the propagation paths of all MSs, and selects the optimal combination of codewords with the help of a DNN that not only overcomes angle ambiguity but also significantly reduces computational complexity.
UR - https://www.scopus.com/pages/publications/85118470882
U2 - 10.1109/PIMRC50174.2021.9569454
DO - 10.1109/PIMRC50174.2021.9569454
M3 - 会议稿件
AN - SCOPUS:85118470882
T3 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
SP - 585
EP - 590
BT - Proceedings - 2001 IEEE International Conference on Data Mining, ICDM 2001
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 32nd IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2021
Y2 - 13 September 2021 through 16 September 2021
ER -