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A New Channel Quantization Strategy for MIMO Interference Alignment with Limited Feedback
In K-user multiple-input multiple-output (MIMO) interference channels, it was shown that interference alignment (IA) achieves a full spatial multiplexing gain when perfect channel state information (CSI) is available at each transmitter in the network. When the CSI is fed back from receivers using t...
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Published in: | IEEE transactions on wireless communications 2012-01, Vol.11 (1), p.358-366 |
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creator | KIM, Jin-Sung MOON, Sung-Hyun LEE, Sang-Rim LEE, Inkyu |
description | In K-user multiple-input multiple-output (MIMO) interference channels, it was shown that interference alignment (IA) achieves a full spatial multiplexing gain when perfect channel state information (CSI) is available at each transmitter in the network. When the CSI is fed back from receivers using the limited number of feedback bits, a significant performance loss is inevitable in the IA due to quantized channel knowledge. In this paper, we propose a new channel quantization strategy to optimize the performance of the IA with limited feedback. In our proposed scheme, we introduce an additional receive filter to minimize the chordal distance which accounts for the quantization error on Grassmann manifold. Besides, we analyze a reduction in terms of the chordal distance in our scheme compared to conventional methods. Simulation results verify that the proposed scheme provides substantially better performance than the conventional method as the number of feedback bits is increased. We show that our scheme exhibits 30% and 40% sum rate gains compared to the conventional scheme when the numbers of the feedback bits are 10 and 15, respectively, with two antennas per node. |
doi_str_mv | 10.1109/TWC.2011.111211.110810 |
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When the CSI is fed back from receivers using the limited number of feedback bits, a significant performance loss is inevitable in the IA due to quantized channel knowledge. In this paper, we propose a new channel quantization strategy to optimize the performance of the IA with limited feedback. In our proposed scheme, we introduce an additional receive filter to minimize the chordal distance which accounts for the quantization error on Grassmann manifold. Besides, we analyze a reduction in terms of the chordal distance in our scheme compared to conventional methods. Simulation results verify that the proposed scheme provides substantially better performance than the conventional method as the number of feedback bits is increased. 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(IEEE) Jan 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c365t-bc8046cc9a68954eaa230c106a219185b695b99421d3ee23426f5478d6a1c2973</citedby><cites>FETCH-LOGICAL-c365t-bc8046cc9a68954eaa230c106a219185b695b99421d3ee23426f5478d6a1c2973</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6092791$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,4024,27923,27924,27925,54796</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=25594795$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>KIM, Jin-Sung</creatorcontrib><creatorcontrib>MOON, Sung-Hyun</creatorcontrib><creatorcontrib>LEE, Sang-Rim</creatorcontrib><creatorcontrib>LEE, Inkyu</creatorcontrib><title>A New Channel Quantization Strategy for MIMO Interference Alignment with Limited Feedback</title><title>IEEE transactions on wireless communications</title><addtitle>TWC</addtitle><description>In K-user multiple-input multiple-output (MIMO) interference channels, it was shown that interference alignment (IA) achieves a full spatial multiplexing gain when perfect channel state information (CSI) is available at each transmitter in the network. When the CSI is fed back from receivers using the limited number of feedback bits, a significant performance loss is inevitable in the IA due to quantized channel knowledge. In this paper, we propose a new channel quantization strategy to optimize the performance of the IA with limited feedback. In our proposed scheme, we introduce an additional receive filter to minimize the chordal distance which accounts for the quantization error on Grassmann manifold. Besides, we analyze a reduction in terms of the chordal distance in our scheme compared to conventional methods. Simulation results verify that the proposed scheme provides substantially better performance than the conventional method as the number of feedback bits is increased. 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When the CSI is fed back from receivers using the limited number of feedback bits, a significant performance loss is inevitable in the IA due to quantized channel knowledge. In this paper, we propose a new channel quantization strategy to optimize the performance of the IA with limited feedback. In our proposed scheme, we introduce an additional receive filter to minimize the chordal distance which accounts for the quantization error on Grassmann manifold. Besides, we analyze a reduction in terms of the chordal distance in our scheme compared to conventional methods. Simulation results verify that the proposed scheme provides substantially better performance than the conventional method as the number of feedback bits is increased. 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subjects | Alignment Antennas Applied sciences channel quantization Channels Detection, estimation, filtering, equalization, prediction Exact sciences and technology Feedback Gain Information, signal and communications theory Interference Interference alignment Interference channels limited feedback MIMO Multiplexing Quantization Receivers Sampling, quantization Signal and communications theory Signal, noise Strategy Studies Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Transmission and modulation (techniques and equipments) Transmitters Vectors |
title | A New Channel Quantization Strategy for MIMO Interference Alignment with Limited Feedback |
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