TY - GEN
T1 - Joint channel estimation algorithm based on structured compressed sensing for FDD multi-user massive MIMO
AU - Zhang, Ruoyu
AU - Zhao, Honglin
AU - Jia, Shaobo
AU - Shan, Chengzhao
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/2
Y1 - 2016/7/2
N2 - Accurate channel state information (CSI) at transmitter is of importance to sufficiently exploit the merits of massive multiple input multiple output (MIMO). Because of the large amount of antennas at base station (BS), the pilot overhead becomes unaffordable, especially in frequency-division duplexing (FDD) massive MIMO systems. To alleviate the overwhelming pilot overhead, a novel channel estimation algorithm for multi-user massive MIMO system employing structured compressed sensing (CS) theory is proposed. Firstly, the angular domain channel representation of massive MIMO is analyzed. Then, due to the practical scattering environment, the common sparsity and private sparsity structure of channel matrix exist in multi-user massive MIMO system. Finally, basing on the statistical information of multi-user channel matrix, a structured joint subspace matching pursuit (SJSMP) algorithm is proposed, which is to estimate channels with limited pilot jointly at the BS. Particularly, the common support and private support of multi-user channel matrix are separately estimated to reduce the pilot overhead with improved CSI estimation quality in terms of MSE.
AB - Accurate channel state information (CSI) at transmitter is of importance to sufficiently exploit the merits of massive multiple input multiple output (MIMO). Because of the large amount of antennas at base station (BS), the pilot overhead becomes unaffordable, especially in frequency-division duplexing (FDD) massive MIMO systems. To alleviate the overwhelming pilot overhead, a novel channel estimation algorithm for multi-user massive MIMO system employing structured compressed sensing (CS) theory is proposed. Firstly, the angular domain channel representation of massive MIMO is analyzed. Then, due to the practical scattering environment, the common sparsity and private sparsity structure of channel matrix exist in multi-user massive MIMO system. Finally, basing on the statistical information of multi-user channel matrix, a structured joint subspace matching pursuit (SJSMP) algorithm is proposed, which is to estimate channels with limited pilot jointly at the BS. Particularly, the common support and private support of multi-user channel matrix are separately estimated to reduce the pilot overhead with improved CSI estimation quality in terms of MSE.
KW - Compressed sensing
KW - frequency-division duplexing (FDD)
KW - multi-user massive MIMO
KW - pilot overhead reduction
KW - structured joint channel estimation
UR - https://www.scopus.com/pages/publications/85016283110
U2 - 10.1109/ICSP.2016.7878018
DO - 10.1109/ICSP.2016.7878018
M3 - 会议稿件
AN - SCOPUS:85016283110
T3 - International Conference on Signal Processing Proceedings, ICSP
SP - 1202
EP - 1207
BT - ICSP 2016 - 2016 IEEE 13th International Conference on Signal Processing, Proceedings
A2 - Baozong, Yuan
A2 - Qiuqi, Ruan
A2 - Yao, Zhao
A2 - Gaoyun, An
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th IEEE International Conference on Signal Processing, ICSP 2016
Y2 - 6 November 2016 through 10 November 2016
ER -