Iterative Equalization and Interference Alignment for Multiuser MIMO HetNets with Imperfect CSIReport as inadecuate

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Mobile Information Systems - Volume 2015 2015, Article ID 605250, 8 pages -

Research Article

Instituto de Telecomunicações, University of Aveiro, 3810-193 Aveiro, Portugal

Instituto de Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Lisboa, Portugal

Received 31 July 2015; Revised 23 October 2015; Accepted 8 December 2015

Academic Editor: Francesco Gringoli

Copyright © 2015 Daniel Castanheira 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.


In this paper we consider a scenario, where several small-cells work under the same coverage area and spectrum of a macrocell. The signals stemming from the small-cell macrocell users if not carefully dealt with will generate harmful interference into the macrocell small-cell. To tackle this problem interference alignment and iterative equalization techniques are considered. By using IA all interference generated by the small-cell macrocell users is aligned along a low dimensional subspace, at the macrocell small-cells. This reduces considerably the amount of resources allocated, to enable the coexistence of the two systems. However, perfect IA requires the availability of error-free channel state information CSI at the transmitters. Due to CSI errors one can have substantial performance degradation due to imperfect alignments. Since in this work the IA precoders are based on imperfect CSI, an efficient iterative space-frequency equalization is designed at the receiver side to cope with the residual aligned interference. The results demonstrate that iterative equalization is robust to imperfect CSI and removes efficiently the interference generated by the poorly aligned interference. Close to matched filter bound performance is achieved, with a very few number of iterations.

Author: Daniel Castanheira, Jorge Aido, Roberto Magueta, Adão Silva, Atilio Gameiro, and Rui Dinis



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