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Spatial DCT-Based Channel Estimation in Multi-Antenna Multi-Cell Interference Channels
KTH, School of Electrical Engineering (EES), Signal Processing.ORCID iD: 0000-0003-2298-6774
2015 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 63, no 6, 1404-1418 p.Article in journal (Refereed) Published
Abstract [en]

This work addresses channel estimation in multiple antenna multicell interference-limited networks. Channel state information (CSI) acquisition is vital for interference mitigation. Wireless networks often suffer from multicell interference, which can be mitigated by deploying beamforming to spatially direct the transmissions. The accuracy of the estimated CSI plays an important role in designing accurate beamformers that can control the amount of interference created from simultaneous spatial transmissions to mobile users. Therefore, a new technique based on the structure of the spatial covariance matrix and the discrete cosine transform (DCT) is proposed to enhance channel estimation in the presence of interference. Bayesian estimation and least squares estimation frameworks are introduced by utilizing the DCT to separate the overlapping spatial paths that create the interference. The spatial domain is thus exploited to mitigate the contamination which is able to discriminate across interfering users. Gains over conventional channel estimation techniques are presented in our simulations which are also valid for a small number of antennas.

Place, publisher, year, edition, pages
2015. Vol. 63, no 6, 1404-1418 p.
Keyword [en]
Channel estimation, discrete cosine transform, second order statistics, training sequence contamination
National Category
Engineering and Technology
URN: urn:nbn:se:kth:diva-162941DOI: 10.1109/TSP.2015.2393844ISI: 000350046600005ScopusID: 2-s2.0-84923239790OAI: diva2:800214

QC 20150402

Available from: 2015-04-02 Created: 2015-03-26 Last updated: 2015-04-02Bibliographically approved

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Ottersten, Björn E.
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