TY - JOUR
T1 - Expectation-maximization-based channel estimation for multiuser MIMO systems
AU - Park, Sunho
AU - Choi, Jun Won
AU - Seol, Ji Yun
AU - Shim, Byonghyo
N1 - Funding Information:
This work was sponsored by Communications Research Team DMC Research and Development Center, Samsung Electronics Co. Ltd, and the National Research Foundation of Korea grant funded by the Korean government(MSIP) (2016R1A2B3015576 & 2014R1A5A1011478).
Publisher Copyright:
© 2017 IEEE.
PY - 2017/6
Y1 - 2017/6
N2 - Multiuser multiple-input multiple-output (MUMIMO) transmission techniques have been popularly used to improve the spectral efficiency and user experience. However, due to the coarse knowledge of channel state information at the transmitter, the quality of transmit precoding to control multiuser interference is degraded, and hence, co-scheduled user equipment may suffer from large residual multiuser interference. In this paper, we propose a new channel estimation technique employing reliable soft symbols to improve the channel estimation and subsequent detection quality of MU-MIMO systems. To this end, we pick reliable data tones from both desired and interfering users and then use them as pilots to re-estimate the channel. In order to jointly estimate the channel and data symbols, we employ the expectation maximization algorithm, where the channel estimation and data decoding are performed iteratively. From numerical experiments in realistic MU-MIMO scenarios, we show that the proposed method achieves substantial performance gain in channel estimation and detection quality over conventional channel estimation approaches.
AB - Multiuser multiple-input multiple-output (MUMIMO) transmission techniques have been popularly used to improve the spectral efficiency and user experience. However, due to the coarse knowledge of channel state information at the transmitter, the quality of transmit precoding to control multiuser interference is degraded, and hence, co-scheduled user equipment may suffer from large residual multiuser interference. In this paper, we propose a new channel estimation technique employing reliable soft symbols to improve the channel estimation and subsequent detection quality of MU-MIMO systems. To this end, we pick reliable data tones from both desired and interfering users and then use them as pilots to re-estimate the channel. In order to jointly estimate the channel and data symbols, we employ the expectation maximization algorithm, where the channel estimation and data decoding are performed iteratively. From numerical experiments in realistic MU-MIMO scenarios, we show that the proposed method achieves substantial performance gain in channel estimation and detection quality over conventional channel estimation approaches.
KW - Channel estimation
KW - Expectation-maximization (EM)
KW - Joint channel estimation and detection
KW - Multipleinput multiple-output (MIMO)
KW - Orthogonal frequency division multiplexing (OFDM)
UR - http://www.scopus.com/inward/record.url?scp=85025644122&partnerID=8YFLogxK
U2 - 10.1109/TCOMM.2017.2688447
DO - 10.1109/TCOMM.2017.2688447
M3 - Article
AN - SCOPUS:85025644122
SN - 0090-6778
VL - 65
SP - 2397
EP - 2410
JO - IEEE Transactions on Communications
JF - IEEE Transactions on Communications
IS - 6
M1 - 7888476
ER -