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Coordinated multicell beamforming for massive MIMO : a random matrix approach
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Lakshminarayana, Subhash, Assaad, Mohamad and Debbah, Mérouane (2015) Coordinated multicell beamforming for massive MIMO : a random matrix approach. IEEE Transactions on Information Theory, 61 (6). pp. 3387-3412. doi:10.1109/TIT.2015.2421446 ISSN 0018-9448.
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WRAP-coordinated-multicell-beamforming-massive-random-matrix-Lakshminarayana-2015.pdf - Accepted Version - Requires a PDF viewer. Download (2458Kb) | Preview |
Official URL: http://dx.doi.org/10.1109/TIT.2015.2421446
Abstract
We consider the problem of coordinated multicell downlink beamforming in massive multiple input multiple output (MIMO) systems consisting of N cells, N t antennas per base station (BS) and K user terminals (UTs) per cell. In particular, we formulate a multicell beamforming algorithm for massive MIMO systems that requires limited amount of information exchange between the BSs. The design objective is to minimize the aggregate transmit power across all the BSs subject to satisfying the user signal-to-interference-noise ratio (SINR) constraints. The algorithm requires the BSs to exchange parameters which can be computed solely based on the channel statistics rather than the instantaneous channel state information (CSI). We make use of tools from random matrix theory to formulate the decentralized algorithm. We also characterize a lower bound on the set of target SINR values for which the decentralized multicell beamforming algorithm is feasible. We further show that the performance of our algorithm asymptotically matches the performance of the centralized algorithm with full CSI sharing. While the original result focuses on minimizing the aggregate transmit power across all the BSs, we formulate a heuristic extension of this algorithm to incorporate a practical constraint in multicell systems, namely the individual BS transmit power constraints. Finally, we investigate the impact of imperfect CSI and pilot contamination effect on the performance of the decentralized algorithm, and propose a heuristic extension of the algorithm to accommodate these issues. Simulation results illustrate that our algorithm closely satisfies the target SINR constraints and achieves minimum power in the regime of massive MIMO systems. In addition, it also provides substantial power savings as compared with zero-forcing beamforming when the number of antennas per BS is of the same orders of magnitude as the number of UTs per cell.
Item Type: | Journal Article | ||||||||||||
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Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | ||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||||||
Library of Congress Subject Headings (LCSH): | MIMO systems | ||||||||||||
Journal or Publication Title: | IEEE Transactions on Information Theory | ||||||||||||
Publisher: | IEEE | ||||||||||||
ISSN: | 0018-9448 | ||||||||||||
Official Date: | June 2015 | ||||||||||||
Dates: |
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Volume: | 61 | ||||||||||||
Number: | 6 | ||||||||||||
Page Range: | pp. 3387-3412 | ||||||||||||
DOI: | 10.1109/TIT.2015.2421446 | ||||||||||||
Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Reuse Statement (publisher, data, author rights): | © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||||||
Date of first compliant deposit: | 29 January 2019 | ||||||||||||
Date of first compliant Open Access: | 30 January 2019 | ||||||||||||
RIOXX Funder/Project Grant: |
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