Abstract
The process of estimating channel parameters is key to massive multiple-input multiple-output (MIMO) in mitigating pilot contamination and hence bolster spectral and energy efficiency. This paper presents an improved minimum mean square error (MMSE) channel estimator combined with a sub-space tracking algorithm (fasts data projection method (FDPM)) to realize a semi-blind channel estimator for massive MIMO time division duplex (TDD) system with pilot contamination. The proposed estimate addresses performance under poor to good signal to noise ratio (SNR). The achievable normalized mean square error (NMSE) for the semi-blind channel estimation and the conventional channel estimation was simulated and analyzed. The improved MMSE estimator performs equally well as the MMSE estimator, while the semiblind estimator outperforms the MMSE estimator for the stipulated SNR and the number of antennas. NMSE is computed for the different estimators and compared with the semi-blind estimator giving the lowest NMSE.
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