On the Role of Transmit Correlation Diversity in Multiuser MIMO Systems

Abstract

Correlation across transmit antennas, in multiple antenna systems (MIMO), has been studied in various scenarios and has been shown to be detrimental or provide benefits depending on the particular system and underlying assumptions. In this paper, we investigate the effect of transmit correlation on the capacity of the Gaussian MIMO broadcast channel (BC), with a particular interest in the large-scale array (or massive MIMO) regime. To this end, we introduce a new type of diversity, referred to as transmit correlation diversity, which captures the fact that the channel vectors of different users may have different, and often nearly mutually orthogonal, large-scale channel eigen-directions. In particular, when taking the cost of downlink training properly into account, transmit correlation diversity can yield significant capacity gains in all regimes of interest. Our analysis shows that the system multiplexing gain can be increased by a factor up to $\lfloor M/r\rfloor$, where $M$ is the number of antennas and $r\le M$ is the common rank of the users transmit correlation matrices, with respect to standard schemes that are agnostic of the transmit correlation and treat the channels as if they were isotropically distributed. Thus, this new form of diversity reveals itself as a valuable "new resource" in multiuser communications.

38 pages, 8 figures, submitted to IEEE Transaction on Information Theory. arXiv admin note: substantial text overlap with arXiv:1401.7114

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Cited by in corpus (6)

• Impact of Line-of-Sight and Unequal Spatial Correlation on Uplink MU-MIMO Systems
• Capacity Scaling of Massive MIMO in Strong Spatial Correlation Regimes
• Uplink Analysis of Large MU-MIMO Systems With Space-Constrained Arrays in Ricean Fading
• Evaluation of Low Complexity Massive MIMO Techniques Under Realistic Channel Conditions
• Transmit Correlation Diversity: Generalization, New Techniques, and Improved Bounds
• Sum Capacity Loss Quantification With Optimal and Sub-Optimal Precoding in Heterogeneous Multiuser Channels