Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels

As we know, the degree of freedom approximates the capacity of a network. To improve the achievable degree of freedom in the K -user interference network, we propose a rank minimization interference minimization algorithm. Unlike the existing methods concentrating on the promotion of degree of freed...

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Main Authors: Yi-bing Li, Xue-ying Diao, Qian-hui Dong
Format: Article
Language:English
Published: Wiley 2017-01-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1177/1550147716686351
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author Yi-bing Li
Xue-ying Diao
Qian-hui Dong
author_facet Yi-bing Li
Xue-ying Diao
Qian-hui Dong
author_sort Yi-bing Li
collection DOAJ
description As we know, the degree of freedom approximates the capacity of a network. To improve the achievable degree of freedom in the K -user interference network, we propose a rank minimization interference minimization algorithm. Unlike the existing methods concentrating on the promotion of degree of freedom, our rank optimization method works directly with the interference matrix rather than its projection using the receive beamformers. Moreover, we put the trace constraint of the square root of desired matrix into the rank optimization to prevent the received signal-to-interference-plus-noise ratio from reduction. The decoders are designed through a weight interference leakage minimization method. Considering that the practical obtainable signal-to-noise ratio may be limited, we improve the design of decoders in rank minimization interference minimization, and propose the rank minimization rate maximization. Rank minimization rate maximization aims to reduce the impact of interference on undesired users as much as possible while improving the desired data rate. Simulation results show that rank minimization interference minimization algorithm can provide more interference-free dimensions for desired signals than other rank minimization methods. Rank minimization rate maximization outperforms rank minimization interference minimization at low-to-moderate signal-to-noise ratios, and its performance gets closer to rank minimization interference minimization with the increase in signal-to-noise ratio. Furthermore, in an improper system, rank minimization rate maximization still performs well.
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spelling doaj-art-5ec24e272e314d0c8e8e7abf18e46d4a2025-08-20T03:34:33ZengWileyInternational Journal of Distributed Sensor Networks1550-14772017-01-011310.1177/1550147716686351Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channelsYi-bing LiXue-ying DiaoQian-hui DongAs we know, the degree of freedom approximates the capacity of a network. To improve the achievable degree of freedom in the K -user interference network, we propose a rank minimization interference minimization algorithm. Unlike the existing methods concentrating on the promotion of degree of freedom, our rank optimization method works directly with the interference matrix rather than its projection using the receive beamformers. Moreover, we put the trace constraint of the square root of desired matrix into the rank optimization to prevent the received signal-to-interference-plus-noise ratio from reduction. The decoders are designed through a weight interference leakage minimization method. Considering that the practical obtainable signal-to-noise ratio may be limited, we improve the design of decoders in rank minimization interference minimization, and propose the rank minimization rate maximization. Rank minimization rate maximization aims to reduce the impact of interference on undesired users as much as possible while improving the desired data rate. Simulation results show that rank minimization interference minimization algorithm can provide more interference-free dimensions for desired signals than other rank minimization methods. Rank minimization rate maximization outperforms rank minimization interference minimization at low-to-moderate signal-to-noise ratios, and its performance gets closer to rank minimization interference minimization with the increase in signal-to-noise ratio. Furthermore, in an improper system, rank minimization rate maximization still performs well.https://doi.org/10.1177/1550147716686351
spellingShingle Yi-bing Li
Xue-ying Diao
Qian-hui Dong
Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels
International Journal of Distributed Sensor Networks
title Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels
title_full Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels
title_fullStr Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels
title_full_unstemmed Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels
title_short Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels
title_sort spatial degree of freedom improvement of interference alignment in multi input multi output interference channels
url https://doi.org/10.1177/1550147716686351
work_keys_str_mv AT yibingli spatialdegreeoffreedomimprovementofinterferencealignmentinmultiinputmultioutputinterferencechannels
AT xueyingdiao spatialdegreeoffreedomimprovementofinterferencealignmentinmultiinputmultioutputinterferencechannels
AT qianhuidong spatialdegreeoffreedomimprovementofinterferencealignmentinmultiinputmultioutputinterferencechannels