Massive MIMO: Communicating in the Near Field of a Large Aperture
Massive Array System
Supervisor
Elisabeth de Carvalho, edc@es.aau.dk
Project Description
Figure 1. Example of deployment of a large aperture
array in an indoor environment
Massive MIMO [RPL+12] has been recently introduced for cellular networks. In a massive
array system, the base stations are equipped with a very large number of antennas. While 4G
base stations are expected to have at most 8 antennas, massive BS will be equipped with a
number of antennas, larger than 100 and as high as 1000. The main enabler of such systems is
the multi-antenna processing at the massive array, which focuses the energy very precisely
towards the end user. Therefore no energy is lost in other directions. This enables a longer
communication reach, hence a better coverage, very high rates, extreme energy efficiency and
reduced inter-cell interference.
In this project, we propose to extend to concept of massive MIMO to an indoor scenario where
a massive array of large aperture is deployed to serve as access points for wireless
communications in new infrastructures, such as airport halls, shopping malls, stadium, concert
stages, etc. Such a large aperture massive array system (LA-MASS) is conceived as part of the
new infrastructure and is integrated in its construction. Our general objective is the study of
LA-MASS in such a hot-spot area in a multi-user setting where a large array serves multiple
users simultaneously. The main characteristic of LA-MASS is that communications happen in
the near-field of the array.
The project contains 2 main components:

Channel characterization: the purpose is to exhibit the main properties of the channel
in the near field of the massive array, including the following aspects: number of
degrees of freedom in the channel, conditioning of the channel, correlation between
users, 2D and 3D array configurations. Note that a simulator has been already
developed accounting for the line of sight propagation [A06] [JI05] [SN05]. The
students are expected to build on the existing simulator where different scattering
distribution will be included.

Communication design: the purpose is an appropriate beamforming design that is
adapted to channel characteristics in the near-field. The focus will be given on designs
that have a low computational complexity. Schemes that are based on full channel
knowledge, or only statistics of the channel can be considered.
Expected Outcome
The students will acquire a deep knowledge on MIMO communications, including
propagation, signal processing and information theory aspects. The students will learn and
simulate the main MIMO transmission techniques and adapt them to a propagation
environment that is different from the environment for which MIMO has been originally
proposed.
Prerequisites



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Mathematical and statistics fundamentals
Linear Algebra
Propagation fundamentals
Matlab.
References
[RPL+12] F. Rusek, D. Persson, B. K. Lau, E. G. Larsson, T. L. Marzetta, O. Edfors and F.
Tufvesson, “Scaling up MIMO: Opportunities and Challenges with Very Large Arrays”, IEEE
Signal Processing Magazine, 2012, http://arxiv.org/abs/1201.3210.
[A06] J.B. Andersen, “Propagation aspects of MIMO channel modelling”, Space-Time
Wireless Systems: From Array Processing to MIMO Communications. ed. / H. Bolcskei; C.
Papadias; D. Gesbert; A-J van der Veen. Cambridge University Press, 2006.
[JI05] Jeng-Shiann Jiang and M.-A Ingram, "Spherical-wave model for short-range MIMO,"
IEEE Transactions on Communications, Sept. 2005.
[SN05] I. Sarris and A.R. Nix, "Maximum MIMO Capacity in Line-of-Sight," Fifth
International Conference on Information, Communications and Signal Processing, 2005.