3 research outputs found
Self-Calibration for Massive MIMO with Channel Reciprocity and Channel Estimation Errors
In time-division-duplexing (TDD) massive multipleinput
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 radiofrequency
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 closedform
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
Self-Calibration for Massive MIMO with Channel Reciprocity and Channel Estimation Errors
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
Self-Calibration for Massive MIMO with Channel Reciprocity and Channel Estimation Errors
In time-division-duplexing (TDD) massive multipleinput 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 radiofrequency 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 closedform 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