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• W2783913181 abstract "Distributed massive multiple-input multiple-output (DM-MIMO) gives a higher spectral efficiency and enhanced coverage area, compared to collocated massive MIMO (CM-MIMO). In general, for massive MIMO, time division duplex is preferable as it enables downlink (DL) precoding based on uplink (UL) channel estimation. A time division duplex (TDD) reciprocity calibration is then essential to compensate the gap between the UL-DL channels, which can be done completely in the base station relying on sounding reference signals (SRS). For a collocated array, relying on mutual coupling between antenna elements, each SRS is received with sufficient power in the array, enabling a reliable estimate of the calibration coefficients. Nevertheless, for DM-MIMO, much less power is collected in distant inter-cluster antennas which degrades the accuracy of the estimated calibration. In this paper, we propose a novel inter-cluster combining method (ICCM) which improves the signal-to-quantization-noise ratio (SQNR) of the SRS, and hence achieves a more robust calibration accuracy for practical DM-MIMO systems. Our experimental results of two 32-antenna arrays distributed in an indoor environment show that ICCM outperforms the existing state-of-the-art algorithms in the sense of lower DL error vector magnitude (EVM) by exploiting diversity and array gain efficiently." @default.
• W2783913181 created "2018-01-26" @default.
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• W2783913181 date "2017-12-01" @default.
• W2783913181 modified "2023-09-26" @default.
• W2783913181 title "Distributed Massive MIMO: A Diversity Combining Method for TDD Reciprocity Calibration" @default.
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• W2783913181 doi "https://doi.org/10.1109/glocom.2017.8254817" @default.
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