Abstract
Millimeter wave provides a promising approach for meeting the ever-growing traffic demand in next generation wireless networks. It is crucial to obtain the channel state information in order to perform beamforming and combining to compensate for severe path loss in this band. In contrast to lower frequencies, a typical millimeter wave channel consists of a few dominant paths. Thus it is generally sufficient to estimate the path gains, angles of departure (AoDs), and angles of arrival (AoAs) of those paths. Proposed in this paper is a dual timescale model to characterize abrupt channel changes (e.g., blockage) and slow variations of AoDs and AoAs. This work focuses on tracking the slow variations and detecting abrupt changes. A Kalman filter based tracking algorithm and an abrupt change detection method are proposed. The tracking algorithm is compared with the adaptive algorithm due to Alkhateeb, Ayach, Leus and Heath (2014) in the case with a single radio frequency chain. Simulation results show that to achieve the same tracking performance, the proposed algorithm requires much lower signal-to-noise ratio (SNR) and much fewer pilots than the other algorithm. Moreover, the change detection method can always detect abrupt changes with moderate number of pilots and SNR.
Original language | English (US) |
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Title of host publication | 2016 IEEE International Conference on Communications, ICC 2016 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781479966646 |
DOIs | |
State | Published - Jul 12 2016 |
Event | 2016 IEEE International Conference on Communications, ICC 2016 - Kuala Lumpur, Malaysia Duration: May 22 2016 → May 27 2016 |
Publication series
Name | 2016 IEEE International Conference on Communications, ICC 2016 |
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Other
Other | 2016 IEEE International Conference on Communications, ICC 2016 |
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Country/Territory | Malaysia |
City | Kuala Lumpur |
Period | 5/22/16 → 5/27/16 |
Funding
This work was partly supported by the China Major State Basic Research Development Program (973 Program) No. 2012CB316100(2), National Natural Science Foundation of China No. 61201203. The work of D. Guo was supported in part by a gift from Futurewei Technologies and by the National Science Foundation under Grant No. ECCS-1231828.
Keywords
- Kalman filter
- Millimeter wave
- change detection
- tracking
ASJC Scopus subject areas
- Computer Networks and Communications