Abstract
The pilot contamination problem in multi-cell multi-user massive MIMO systems is addressed in this paper. The overall performance of massive MIMO system is limited to the accuracy of the channel-state information (CSI) estimation at base station (BS). In time-division duplex systems, BS attains CSI using uplink-training sequence (TS) sent by users. The pilot contamination problem caused by using non-orthogonal TSs is the main challenge in this method. In this paper, a novel channel estimation method in the presence of pilot contamination is presented. The proposed method exploits sparse nature of the channel impulse response (CIR). Due to the pilot contamination and noise, the estimated CIR is not sparse anymore and consists of the desired and interference taps. To distinguish the desired taps from interferences, first, the initial estimation of the channel frequency response and equivalent CIR is achieved by taking EVD of received data covariance matrix. Finally, the initial estimated CIR will be modified using compressed-sensing methods. Simulation results indicate that the proposed approach achieves much better performance in terms of BER and sum-rate in comparison with the conventional methods.
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Notes
We have considered \( P \), \( 2P \) and \( 4P \) sparsity in simulations. The results show that the CS based algorithms have the best performance when \( 2P \) sparsity is assumed. The sparsity level was fixed at \( 2P \) in this paper.
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Kumeleh, M.H., Kenarsari, S.R. & Naeiny, M.F. Pilot Contamination Reduction Using Time-Domain Channel Sparsity in Massive MIMO-OFDM Systems. Iran J Sci Technol Trans Electr Eng 41, 255–266 (2017). https://doi.org/10.1007/s40998-017-0027-3
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DOI: https://doi.org/10.1007/s40998-017-0027-3