Abstract
A subspace projection to improve channel estimation in massive multi-antenna systems is proposed and analyzed. Together with power-controlled hand-off, it can mitigate the pilot contamination problem without the need for coordination among cells. The proposed method is blind in the sense that it does not require pilot data to find the appropriate subspace. It is based on the theory of large random matrices that predicts that the eigenvalue spectra of large sample covariance matrices can asymptotically decompose into disjoint bulks as the matrix size grows large. Random matrix and free probability theory are utilized to predict under which system parameters such a bulk decomposition takes place. Simulation results are provided to confirm that the proposed method outperforms conventional linear channel estimation if bulk separation occurs.
Original language | English |
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Article number | 6756975 |
Pages (from-to) | 773-786 |
Journal | IEEE Journal on Selected Topics in Signal Processing |
Volume | 8 |
Issue number | 5 |
DOIs | |
Publication status | Published - 1 Oct 2014 |
MoE publication type | A1 Journal article-refereed |
Keywords
- channel estimation
- eigenvalue spectrum
- free probability
- massive MIMO
- Multiple antennas
- multiple-input multiple-output (MIMO) systems
- principal component analysis
- random matrices
- spread-spectrum