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International Journal of Antennas and Propagation
Volume 2014 (2014), Article ID 614061, 12 pages
http://dx.doi.org/10.1155/2014/614061
Research Article

Performance Analysis of 3D Massive MIMO Cellular Systems with Collaborative Base Station

State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100786, China

Received 24 January 2014; Revised 16 May 2014; Accepted 24 June 2014; Published 10 July 2014

Academic Editor: Xuefeng Yin

Copyright © 2014 Xingwang Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Massive MIMO have drawn considerable attention as they enable significant capacity and coverage improvement in wireless cellular network. However, pilot contamination is a great challenge in massive MIMO systems. Under this circumstance, cooperation and three-dimensional (3D) MIMO are emerging technologies to eliminate the pilot contamination and to enhance the performance relative to the traditional interference-limited implementations. Motivated by this, we investigate the achievable sum rate performance of MIMO systems in the uplink employing cooperative base station (BS) and 3D MIMO systems. In our model, we consider the effects of both large-scale and small-scale fading, as well as the spatial correlation and indoor-to-outdoor high-rise propagation environment. In particular, we investigate the cooperative communication model based on 3D MIMO and propose a closed-form lower bound on the sum rate. Utilizing this bound, we pursue a “large-system” analysis and provide the asymptotic expression when the number of antennas at the BS grows large, and when the numbers of antennas at transceiver grow large with a fixed ratio. We demonstrate that the lower bound is very tight and becomes exact in the massive MIMO system limits. Finally, under the sum rate maximization condition, we derive the optimal number of UTs to be served.