Robust MIMO Channel Estimation from Incomplete and Corrupted Measurements
Paper i proceeding, 2018

Location-aware communication is one of the enabling techniques for future 5G networks. It requires accurate temporal and spatial channel estimation from multidimensional data. Most of the existing channel estimation techniques assume that the measurements are complete and noise is Gaussian. While these approaches are brittle to corrupted or outlying measurements, which are ubiquitous in real applications. To address these issues, we develop a lp-norm minimization based iteratively reweighted higher-order singular value decomposition algorithm. It is robust to Gaussian as well as the impulsive noise even when the measurement data is incomplete. Compared with the state-of-the-art techniques, accurate estimation results are achieved for the proposed approach.


Fuxi Wen

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Zhongmin Wang

Xi'an Jiaotong University

Chen Liang

Xi'an Jiaotong University

2018 21st International Conference on Information Fusion (FUSION)

978-0-9964527-6-2 (ISBN)

International Conference on Information Fusion
Cambridge, United Kingdom,


Elektroteknik och elektronik



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