TY - JOUR
T1 - Generic iterative downlink interference alignment
AU - Shin, Won Yong
AU - Yoon, Jangho
N1 - Publisher Copyright:
Copyright © 2015 The Institute of Electronics, Information and Communication Engineers.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2015/5/1
Y1 - 2015/5/1
N2 - In this paper, we introduce a promising iterative interference alignment (IA) strategy for multiple-input multiple-output (MIMO) multi-cell downlink networks, which utilizes the channel reciprocity between uplink/downlink channels. We intelligently combine iterative beamforming and downlink IA issues to design an iterative multiuser MIMO IA algorithm. The proposed scheme uses two cascaded beamforming matrices to construct a precoder at each base station (BS), which not only efficiently reduce the effect of inter-cell interference from other-cell BSs, referred to as leakage of interference, but also perfectly eliminate intra-cell interference among spatial streams in the same cell. The transmit and receive beamforming matrices are iteratively updated until convergence. Numerical results indicate that our IA scheme exhibits higher sum-rates than those of the conventional iterative IA schemes. Note that our iterative IA scheme operates with local channel state information, no time/frequency expansion, and even relatively a small number of mobile stations (MSs), unlike opportunistic IA which requires a great number of MSs.
AB - In this paper, we introduce a promising iterative interference alignment (IA) strategy for multiple-input multiple-output (MIMO) multi-cell downlink networks, which utilizes the channel reciprocity between uplink/downlink channels. We intelligently combine iterative beamforming and downlink IA issues to design an iterative multiuser MIMO IA algorithm. The proposed scheme uses two cascaded beamforming matrices to construct a precoder at each base station (BS), which not only efficiently reduce the effect of inter-cell interference from other-cell BSs, referred to as leakage of interference, but also perfectly eliminate intra-cell interference among spatial streams in the same cell. The transmit and receive beamforming matrices are iteratively updated until convergence. Numerical results indicate that our IA scheme exhibits higher sum-rates than those of the conventional iterative IA schemes. Note that our iterative IA scheme operates with local channel state information, no time/frequency expansion, and even relatively a small number of mobile stations (MSs), unlike opportunistic IA which requires a great number of MSs.
UR - http://www.scopus.com/inward/record.url?scp=84928885830&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84928885830&partnerID=8YFLogxK
U2 - 10.1587/transcom.E98.B.834
DO - 10.1587/transcom.E98.B.834
M3 - Article
AN - SCOPUS:84928885830
VL - E98B
SP - 834
EP - 841
JO - IEICE Transactions on Communications
JF - IEICE Transactions on Communications
SN - 0916-8516
IS - 5
ER -