A closed-loop training approach for massive MIMO beamforming systems

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There has been a growing interest in wireless systems that employ a very large number of transmit antennas. Some theoretical results have shown that substantial improvements in network capacity are possible. Despite this work, a major challenge is how these large transmit arrays should perform training to allow receiver channel estimation. Without new techniques, the heavy burden of training could overwhelm the system and mitigate any possible improvements, especially in systems using frequency division duplexing (FDD) where channel reciprocity cannot be exploited. In this work, we propose the use of closedloop training. In this framework, the transmitted training signal is optimized to improve data communications performance by using prior information about the current channel obtained from past channel estimates. The work focuses on block-fading channels with temporal and spatial correlation. Simulation results show improved performance. © 2013 IEEE.
Publisher
IEEE
Issue Date
2013-03
Language
English
Citation

2013 47th Annual Conference on Information Sciences and Systems, CISS 2013

DOI
10.1109/CISS.2013.6552252
URI
http://hdl.handle.net/10203/267614
Appears in Collection
RIMS Conference Papers
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