IEICE TRANSACTIONS on Communications
Generic Iterative Downlink Interference Alignment
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E98-B No.5 pp.834-841
- Publication Date
- 2015/05/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E98.B.834
- Type of Manuscript
- PAPER
- Category
- Fundamental Theories for Communications
Authors
Won-Yong SHIN
Dankook University
Jangho YOON
KAIST
Keyword
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Won-Yong SHIN, Jangho YOON, "Generic Iterative Downlink Interference Alignment" in IEICE TRANSACTIONS on Communications,
vol. E98-B, no. 5, pp. 834-841, May 2015, doi: 10.1587/transcom.E98.B.834.
Abstract: 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.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E98.B.834/_p
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@ARTICLE{e98-b_5_834,
author={Won-Yong SHIN, Jangho YOON, },
journal={IEICE TRANSACTIONS on Communications},
title={Generic Iterative Downlink Interference Alignment},
year={2015},
volume={E98-B},
number={5},
pages={834-841},
abstract={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.},
keywords={},
doi={10.1587/transcom.E98.B.834},
ISSN={1745-1345},
month={May},}
Copy
TY - JOUR
TI - Generic Iterative Downlink Interference Alignment
T2 - IEICE TRANSACTIONS on Communications
SP - 834
EP - 841
AU - Won-Yong SHIN
AU - Jangho YOON
PY - 2015
DO - 10.1587/transcom.E98.B.834
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E98-B
IS - 5
JA - IEICE TRANSACTIONS on Communications
Y1 - May 2015
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.
ER -
English
