TY - GEN
T1 - Tracking angles of departure and arrival in a mobile millimeter wave channel
AU - Zhang, Chuang
AU - Guo, Dongning
AU - Fan, Pingyi
N1 - Funding Information:
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.
Publisher Copyright:
© 2016 IEEE.
Copyright:
Copyright 2016 Elsevier B.V., All rights reserved.
PY - 2016/7/12
Y1 - 2016/7/12
N2 - 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.
AB - 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.
KW - Kalman filter
KW - Millimeter wave
KW - change detection
KW - tracking
UR - http://www.scopus.com/inward/record.url?scp=84981336657&partnerID=8YFLogxK
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U2 - 10.1109/ICC.2016.7510902
DO - 10.1109/ICC.2016.7510902
M3 - Conference contribution
AN - SCOPUS:84981336657
T3 - 2016 IEEE International Conference on Communications, ICC 2016
BT - 2016 IEEE International Conference on Communications, ICC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Conference on Communications, ICC 2016
Y2 - 22 May 2016 through 27 May 2016
ER -