Paper Info
Title
Low complexity direction of arrival (DoA) estimation for 2D massive MIMO systems
Abstract
Mobile data traffic is expected to almost double every year from 2012 to 2016. In order to address the challenge, “massive MIMO” has been proposed as one of the enabling technologies to significantly increase the spectral-efficiency of a wireless system. In “massive MIMO” systems, a base station will rely on the uplink sounding signals from mobile stations to figure out the channel knowledge to perform MIMO beam-forming. Accordingly, direction-of-arrival estimation at the base station becomes crucial for “massive MIMO” systems to realize the predicted capacity gains. In this paper, we study DoA estimation for two-dimensional (2D) “massive MIMO” systems in mobile wireless systems. To be specific, we derive the Cramer-Rao lower bound for 2D “massive MIMO” systems and introduce a low complexity direction-of-arrival estimation algorithm to jointly estimate elevation and azimuth angles of the arrived signals based on unitary transformation. Results suggest that the dimension of the antenna array at the base station plays an important role in the estimation performance. It is also found that azimuth estimation is more vulnerable compared to elevation estimation. These insights will be useful for designing practical “massive MIMO” systems in future mobile wireless communications.
Year
DOI
Venue
2012
10.1109/GLOCOMW.2012.6477660
GLOBECOM Workshops
Keywords
Field
DocType
base station,unitary transformation,mobile station,mobile data traffic,uplink signal sounding,doa,cramer-rao lower bound,antenna arrays,direction of arrival estimation,mimo beamforming,mobile radio,mimo communication,mobile wireless communication system,spectral-efficiency,capacity gain prediction,elevation estimation,direction-of-arrival estimation,azimuth angle estimation,channel knowledge,telecommunication traffic,2d massive mimo system,antenna array
Base station,Mobile radio,Multi-user MIMO,3G MIMO,Wireless,Computer science,Direction of arrival,MIMO,Real-time computing,Telecommunications link
Conference
ISSN
ISBN
Citations 
2166-0069
978-1-4673-4940-6
18
PageRank 
References 
Authors
0.89
4
3
Name
Order
Citations
PageRank
Anding Wang1567.00
Lingjia Liu279992.58
Jianzhong (Charlie) Zhang321920.58