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International Journal of Antennas and Propagation
Volume 2014 (2014), Article ID 628149, 11 pages
Research Article

Coordinated Beamforming with Altruistic Precoding and User Selection for MU-MIMO System

1Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China
2Information & Electronics Technology Lab, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
3China Mobile Group Design Institute Co., Ltd., Beijing 100080, China

Received 14 January 2014; Accepted 2 June 2014; Published 18 June 2014

Academic Editor: Yulong Zou

Copyright © 2014 Gaofeng Cui 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.


Other cell interference (OCI) degrades the achievable capacity of downlink multiuser multiple-input multiple-output (MU-MIMO) systems seriously. Among OCI mitigation schemes, methods that sacrifice degrees of freedom to nullify the OCI have been proven to be helpful to improve the cell edge throughput. However, since interference nulling schemes can only improve the signal to interference plus noise ratio (SINR) of users, they are not optimal in terms of average cell throughput, especially for low to medium OCI levels. We explore the question whether it is better to improve the SINR of every user in other cells rather than benefit users. An altruistic precoding method to minimize the sum of generated interference for all of the other cell users is proposed with degrees of freedom being sacrificed. With the altruistic precoding method, we deduce the lower bound on the capacity and solve the multicell user selection problem with a local optimal solution in which only eigenvalues of interfering channels are needed to be shared. Simulation results demonstrate that the proposed method outperforms the existing algorithms at any OCI level. Furthermore, we also analyze the best choice of degrees of freedom used to mitigate OCI through simulation.