Design of 5G Full Dimension Massive MIMO Systems

Qurrat-Ul-Ain Nadeem, Abla Kammoun, Merouane Debbah, Mohamed-Slim Alouini

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107 Scopus citations


This work discusses full-dimension multiple-inputmultiple- output (FD-MIMO) technology, which is currently an active area of research and standardization in wireless communications for evolution towards Fifth Generation (5G) cellular systems. FD-MIMO utilizes an active antenna system (AAS) with a two-dimensional (2D) planar array structure, that not only allows a large number of antenna elements to be packed within feasible base station form factors but also provides the ability of adaptive electronic beamforming in the threedimensional (3D) space. However, the compact structure of largescale planar arrays drastically increases the spatial correlation in FD-MIMO systems. In order to account for its effects, the generalized spatial correlation functions for channels constituted by individual elements and overall antenna ports in the AAS are derived. Exploiting the quasi-static channel covariance matrices of users, the problem of determining the optimal downtilt weight vector for antenna ports, which maximizes the minimum signalto- interference ratio of a multi-user multiple-input-single-output system, is formulated as a fractional optimization problem. A quasi-optimal solution is obtained through the application of semi-definite relaxation and Dinkelbach’s method. Finally, the user-group specific elevation beamforming scenario is devised, which offers significant performance gains as confirmed through simulations. These results have direct application in the analysis of 5G FD-MIMO systems.
Original languageEnglish (US)
Pages (from-to)726-740
Number of pages15
JournalIEEE Transactions on Communications
Issue number2
StatePublished - Oct 13 2017

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The work of Q.-U.-A. Nadeem, A. Kammoun and M. -S. Alouini was supported by a CRG4 grant from the Office of Competitive Research Funding (OCRF) at KAUST. The work of M´erouane Debbah was supported by the ERC Starting Grant 305123 MORE (Advanced Mathematical Tools for Complex Network Engineering).


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