Tensor Decomposition Based Beamspace ESPRIT for Millimeter Wave MIMO Channel Estimation
Paper in proceedings, 2018

We propose a search-free beamspace tensor-ESPRIT algorithm for millimeter wave MIMO channel estimation. It is a multidimensional generalization of beamspace-ESPRIT method by exploiting the multiple invariance structure of the measurements. Geometry-based channel model is considered to contain the channel sparsity feature. In our framework, an alternating least squares problem is solved for low rank tensor decomposition and the multidimensional parameters are automatically associated. The performance of the proposed algorithm is evaluated by considering different transformation schemes.

Author

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Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

[Person 5ff2e170-164b-47d9-aa52-c03eabf7b6f2 not found]

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

[Person 9b3b3828-372b-4edc-b1da-e95b2f8f7988 not found]

Technische Universität Graz

[Person b4ffffc2-439c-4d19-8d51-adfd9ca58ecd not found]

Technische Universität Graz

[Person 5e4253a3-d9a5-424a-82ce-a7dd793e28c0 not found]

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

IEEE Global Communications Conference
Abu Dhabi, United Arab Emirates,

Massive MIMO location for 5G networks, MassLOC

European Commission (EC), 2017-04-18 -- 2019-04-13.

Fifth Generation Communication Automotive Research and innovation (5GCAR)

European Commission (EC), 2017-06-01 -- 2019-05-31.

Areas of Advance

Information and Communication Technology

Subject Categories

Communication Systems

DOI

10.1109/GLOCOM.2018.8647176

More information

Latest update

12/9/2019