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Channel Estimation and Data Detection for Multicell Massive MIMO Systems in Correlated Channels

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Abstract

In this study, multicell multiuser multiple-input multiple-output systems are considered with very large number of antennas at base station. We consider a physical channel model comprised finite number of angle of arrivals, and propose a channel estimation scheme based on the eigenvalue decomposition of the covariance matrix of the received signal vector. To improve the channel estimation performance under strong intercell interference, a joint channel estimation and optimal multiuser detection scheme is proposed. Furthermore, an optimal linear receiver is developed for the uplink by taking the channel estimation error into account, and derive a closed-form expression for the sum achievable rate of the optimal receiver. Moreover, using the channel reciprocity of a time-division duplex system, we present how to form an optimal precoding vector for the downlink, and how to compute the sum achievable rate in the downlink. Numerical results are provided to verify the analysis and evaluate the performance of the channel estimation and data detection.

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Notes

  1. We assume that the channel is invariant during the sampling period.

  2. The SINR of each user for the downlink transmission can be derived by using the same procedure as the uplink case with the optimal linear precoder, MMSE, ZF, and MRT schemes, and the sum achievable rate can be defined similarly to (37).

  3. Since the noise variance is normalized to the unity, \({\mathrm {SNR}}\) is equal to \(P_{{\mathrm {u}}}\) or \(P_{{\mathrm {d}}}\).

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Acknowledgments

This work was supported by the Human Resources Development program (No. 20134010200570) of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Trade, Industry and Energy.

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Correspondence to Oh-Soon Shin.

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Nguyen, VD., Nguyen, H.V., Shin, Y. et al. Channel Estimation and Data Detection for Multicell Massive MIMO Systems in Correlated Channels. Wireless Pers Commun 86, 1857–1877 (2016). https://doi.org/10.1007/s11277-015-3151-2

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