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Hybrid Massive MIMO Precoding in Cloud-RAN

Ruikai Mai, Tho Le-Ngoc

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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Elektronik, Elektrotechnik, Nachrichtentechnik

Beschreibung

This book covers the design and optimization of hybrid RF-baseband precoding for massive multiple-input multiple-output (MIMO)-enabled cloud radio access networks (RANs), where use cases such as millimeter-wave wireless backhauling, fully-loaded cellular networks are of interest. The suitability and practical implementation of the proposed precoding solutions for the Cloud RAN architecture are also discussed.

Novel techniques are examined for RF precoding optimization in combination with nonlinear precoding at baseband, and the superiority of joint RF-baseband design is verified. Moreover, the efficacy of hybrid RF-baseband precoding to combat intercell interference in a multi-cell environment with universal frequency reuse is investigated, which is concluded to be a promising enabler for the dense deployment of base stations.

 This book mainly targets researchers and engineers interested in the challenges, optimization, andimplementation of massive MIMO precoding in 5G Cloud RAN. Graduate students in electrical engineering and computer science interested in the application of mathematical optimization to model and solve precoding problems in massive MIMO cellular systems will also be interested in this book.


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Schlagwörter

two-timescale channel state information, approximate joint diagonalization, Cayle transformation, hybrid RF-baseband precoding/combining, Kalman filtering, joint RF-baseband optimization, minimum mean square errors, discrete monotonic optimization, semi-definite programming, channel tracking, Massive multiple-input multiple-output (MIMO), coordinated multi-point (CoMP), matrix manifold optimization, wireless backhauling, nonlinear precoding, vector perturbation