University of Oulu

J. Kaleva, N. J. Myers, A. Tölli, R. W. Heath and U. Madhow, "Short Range 3D MIMO mmWave Channel Reconstruction via Geometry-aided AoA Estimation," 2019 53rd Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 2019, pp. 427-431, doi: 10.1109/IEEECONF44664.2019.9048890

Short range 3D MIMO mmWave channel reconstruction via geometry-aided AoA estimation

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Author: Kaleva, Jarkko1; Myers, Nitin Jonathan2; Tölli, Antti1;
Organizations: 1Centre for Wireless Communications, University of Oulu, Finland
2Department of Electrical and Computer Engineering, The University of Texas at Austin, USA
3Department of Electrical and Computer Engineering, University of California at Santa Barbara, USA
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
Persistent link:
Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-05-26


In some millimeter wave (mmWave) applications, such as wearables, the distance between the transceivers is relatively short. Further, the channel has significant angular spread in both azimuth and elevation domains even in line-of-sight (LoS). Under such conditions, hybrid mmWave architectures with multiple analog uniform planar arrays (UPAs) potentially allow spatial multiplexing even in LoS provided that the high rank structure of the channel is captured. The conventional far-field channel estimation methods are not generally suitable for these scenarios and perform poorly. We consider parametrized spatial channel estimation, where the known antenna array geometry is exploited to recover the angle-of-arrivals (AoAs) of the 3D multiple-input multiple-output (MIMO) channel. The channel is then reconstructed using these AoA estimates and the known geometry. We show that conventional maximum a posteriori (MAP) estimation of the channel parameters suffers from high computational complexity and may not be not applicable for low powered devices. To this end, we propose a lower complexity message passing algorithm for short range channel estimation. We show, by numerical examples, that the proposed technique achieves good performance with fewer pilot resources when compared to compressed sensing or antenna specific pilot based channel estimation.

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Series: Asilomar Conference on Signals, Systems & Computers
ISSN: 1058-6393
ISSN-E: 1058-6393
ISSN-L: 1058-6393
ISBN: 978-1-7281-4300-2
ISBN Print: 978-1-7281-4301-9
Pages: 427 - 431
DOI: 10.1109/IEEECONF44664.2019.9048890
Host publication: 2019 53rd Asilomar Conference on Signals, Systems, and Computers Nov 3-6, 2019 Pacific Grove, CA, USA
Host publication editor: Matthews, Michael B.
Conference: Annual Asilomar Conference on Signals, Systems, and Computers
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This research is supported by the Academy of Finland under grant numbers 311741 and 318927 (6Genesis Flagship), and by the U.S. National Science Foundation under grant numbers CNS-1702800 and ECCS-1711702.
Academy of Finland Grant Number: 311741
Detailed Information: 311741 (Academy of Finland Funding decision)
318927 (Academy of Finland Funding decision)
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