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Robust Bayesian Precoding for Mitigation of TDD Hardware Calibration Errors
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AI
DOI：10.1109/LSP.2016.2569199.png)
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Abstract
En 中文
The predominantly used channel reciprocity condition in time-division-duplex mode only holds in practical systems if the transmit and receive hardware chains at the base station (BS) and at the user equipments are perfectly calibrated. Otherwise, there is a mismatch between the uplink (UL) and downlink channel state information (CSI) that leads to performance degradations. In this paper, we consider a multi-userMIMO system with hardware calibration errors (CaEs) at the BS and derive robust Bayesian precoders that minimize inter-user interference using the UL CSI and CaEs statistics as side information. The proposed robust precoding outperforms conventional non-robust precoding, and its gains compared to non-robust precoding increase with increasing numbers of users and CaEs. Furthermore, robust precoding can be used to relax calibration requirements, which is a result of practical interest. Our approach is applicable to any number of BS antennas but is especially important for massive MIMO systems where larger CaEs might be expected.
Keywords:
Bayesian estimation
calibration errors (CaEs)
robust precoding
time-division-duplex (TDD) mode
Journal
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9.6
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