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http://dx.doi.org/10.3837/tiis.2014.01.007

Distributed Compressive Sensing Based Channel Feedback Scheme for Massive Antenna Arrays with Spatial Correlation  

Gao, Huanqin (College of Communication & Information Engineering, Nanjing University of Posts & Telecommunications)
Song, Rongfang (College of Communication & Information Engineering, Nanjing University of Posts & Telecommunications)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.8, no.1, 2014 , pp. 108-122 More about this Journal
Abstract
Massive antenna array is an attractive candidate technique for future broadband wireless communications to acquire high spectrum and energy efficiency. However, such benefits can be realized only when proper channel information is available at the transmitter. Since the amount of the channel information required by the transmitter is large for massive antennas, the feedback is burdensome in practice, especially for frequency division duplex (FDD) systems, and needs normally to be reduced. In this paper a novel channel feedback reduction scheme based on the theory of distributed compressive sensing (DCS) is proposed to apply to massive antenna arrays with spatial correlation, which brings substantially reduced feedback load. Simulation results prove that the novel scheme is better than the channel feedback technique based on traditional compressive sensing (CS) in the aspects of mean square error (MSE), cumulative distributed function (CDF) performance and feedback resources saving.
Keywords
Massive-MIMO; distributed compressive sensing; channel state information; feedback reduction;
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