TY - GEN
T1 - Self-Calibration for Massive MIMO with Channel Reciprocity and Channel Estimation Errors
AU - Mi, De
AU - Zhang, Lei
AU - Dianati, Mehrdad
AU - Muhaidat, Sami
AU - Xiao, Pei
AU - Tafazolli, Rahim
N1 - Funding Information:
We would like to acknowledge the support of the University of Surrey 5GIC (www.surrey.ac.uk/5gic) members for this work. This work was also supported in part by the European Commission under the 5GPPP project 5G-Xcast (H2020-ICT-2016-2 call, grant number 761498). The views expressed in this contribution are those of the authors and do not necessarily represent the project.
Publisher Copyright:
© 2018 IEEE.
PY - 2018
Y1 - 2018
N2 - In time-division-duplexing (TDD) massive multiple-input multiple-output (MIMO) systems, channel reciprocity is exploited to overcome the overwhelming pilot training and the feedback overhead. However, in practical scenarios, the imperfections in channel reciprocity, mainly caused by radio-frequency mismatches among the antennas at the base station side, can significantly degrade the system performance and might become a performance limiting factor. In order to compensate for these imperfections, we present and investigate two new calibration schemes for TDD-based massive multi-user MIMO systems, namely, relative calibration and inverse calibration. In particular, the design of the proposed inverse calibration takes into account a compound effect of channel reciprocity error and channel estimation error. We further derive closed-form expressions for the ergodic sum rate, assuming maximum ratio transmissions with the compound effect of both errors. We demonstrate that the inverse calibration scheme outperforms the traditional relative calibration scheme. The proposed analytical results are also verified by simulated illustrations.
AB - In time-division-duplexing (TDD) massive multiple-input multiple-output (MIMO) systems, channel reciprocity is exploited to overcome the overwhelming pilot training and the feedback overhead. However, in practical scenarios, the imperfections in channel reciprocity, mainly caused by radio-frequency mismatches among the antennas at the base station side, can significantly degrade the system performance and might become a performance limiting factor. In order to compensate for these imperfections, we present and investigate two new calibration schemes for TDD-based massive multi-user MIMO systems, namely, relative calibration and inverse calibration. In particular, the design of the proposed inverse calibration takes into account a compound effect of channel reciprocity error and channel estimation error. We further derive closed-form expressions for the ergodic sum rate, assuming maximum ratio transmissions with the compound effect of both errors. We demonstrate that the inverse calibration scheme outperforms the traditional relative calibration scheme. The proposed analytical results are also verified by simulated illustrations.
UR - http://www.scopus.com/inward/record.url?scp=85063475254&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2018.8647759
DO - 10.1109/GLOCOM.2018.8647759
M3 - Conference contribution
AN - SCOPUS:85063475254
T3 - 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings
BT - 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Global Communications Conference, GLOBECOM 2018
Y2 - 9 December 2018 through 13 December 2018
ER -