Enhanced Limited Feedback Schemes for DL MU-MIMO ZF Precoding
This paper proposes new limited-feedback Channel State Information (CSI) calculation schemes for Zero Forcing (ZF)-precoded downlink Multi-User Multiple-Input Multiple-Output (MU-MIMO) systems. It is a common understanding that the feedback quantized by the codebook limits the performance of MU-MIMO...
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| Vydáno v: | IEEE transactions on wireless communications Ročník 12; číslo 4; s. 1554 - 1561 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York, NY
IEEE
01.04.2013
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1536-1276, 1558-2248 |
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| Abstract | This paper proposes new limited-feedback Channel State Information (CSI) calculation schemes for Zero Forcing (ZF)-precoded downlink Multi-User Multiple-Input Multiple-Output (MU-MIMO) systems. It is a common understanding that the feedback quantized by the codebook limits the performance of MU-MIMO. In this paper, through a quasi-ZF or a quasi-Minimum Mean-Squared Error (MMSE) weight, the channel matrix is transferred to one of the codebook vectors, based on which, the CSI is calculated. Thus, the quantization error is minimized. Meanwhile, the selection for the codebook vector guarantees the maximizing of the estimated Signal to Interference plus Noise Ratio (SINR). We verify that the proposed scheme obtains accurate feedback information, and the predicted weight can be the same as the optimal linear decoder as if the receiver knew all the precoder information that is fed-forward from the BS, as long as the number of antennas for each receiver equals that for the transmitter, and equals that for the total transmit data streams. Compared to the commonly used Precoding Matrix Index (PMI) based method, which uses rank-one single user (SU)-MIMO feedback, simulation results show that the proposed schemes achieve higher sum capacities in different scenarios. Moreover, since the weight can be directly used as the decoder, the feed-forward overhead is reduced. |
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| AbstractList | This paper proposes new limited-feedback Channel State Information (CSI) calculation schemes for Zero Forcing (ZF)-precoded downlink Multi-User Multiple-Input Multiple-Output (MU-MIMO) systems. It is a common understanding that the feedback quantized by the codebook limits the performance of MU-MIMO. In this paper, through a quasi-ZF or a quasi-Minimum Mean-Squared Error (MMSE) weight, the channel matrix is transferred to one of the codebook vectors, based on which, the CSI is calculated. Thus, the quantization error is minimized. Meanwhile, the selection for the codebook vector guarantees the maximizing of the estimated Signal to Interference plus Noise Ratio (SINR). We verify that the proposed scheme obtains accurate feedback information, and the predicted weight can be the same as the optimal linear decoder as if the receiver knew all the precoder information that is fed-forward from the BS, as long as the number of antennas for each receiver equals that for the transmitter, and equals that for the total transmit data streams. Compared to the commonly used Precoding Matrix Index (PMI) based method, which uses rank-one single user (SU)-MIMO feedback, simulation results show that the proposed schemes achieve higher sum capacities in different scenarios. Moreover, since the weight can be directly used as the decoder, the feed-forward overhead is reduced. |
| Author | Wei Wang Kayama, Hidetoshi Harada, Atsushi |
| Author_xml | – sequence: 1 surname: Wei Wang fullname: Wei Wang email: wangw@docomolabs-beijing.com.cn organization: DOCOMO Beijing Commun. Labs. Co., Ltd., Beijing, China – sequence: 2 givenname: Atsushi surname: Harada fullname: Harada, Atsushi email: harada@docomolabs-beijing.com.cn organization: DOCOMO Beijing Commun. Labs. Co., Ltd., Beijing, China – sequence: 3 givenname: Hidetoshi surname: Kayama fullname: Kayama, Hidetoshi email: kayama@docomolabs-beijing.com.cn organization: DOCOMO Beijing Commun. Labs. Co., Ltd., Beijing, China |
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| Cites_doi | 10.1109/JSAC.2008.081015 10.1109/GLOCOM.2009.5425392 10.1109/PIMRC.2008.4699429 10.1109/TIT.2006.883550 10.1109/TIT.2006.880064 10.1109/GLOCOM.2010.5683816 10.1109/JSAC.2007.070920 10.1109/TSP.2008.924638 10.1109/GLOCOM.2010.5683625 10.1109/JSAC.2005.862421 10.1109/TIT.2003.813523 10.1109/TSP.2003.821107 10.1109/TIT.2003.817421 10.1109/TIT.1983.1056659 10.1109/TSP.2007.893908 |
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| Keywords | Performance evaluation MIMO system Multiple access Parameter estimation Quantization error Coding circuit Transmitter Feedback regulation Downlink MU-MIMO Decoding Mean square error feedback Codebook Simulation Coding Channel estimation Broadcast channels Intermediate frequency Pretreatment Feedforward Signal to interference plus noise ratio Receiving antenna |
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| SubjectTerms | Antennas Applied sciences broadcast channels Channels Coding, codes Decoders Decoding Detection, estimation, filtering, equalization, prediction Downlink Errors Exact sciences and technology Feedback Information, signal and communications theory Interference Mathematical analysis MU-MIMO Quantization (signal) Radiocommunications Receivers Signal and communications theory Signal to noise ratio Signal, noise Studies Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Transmission and modulation (techniques and equipments) Vectors Vectors (mathematics) Weight reduction |
| Title | Enhanced Limited Feedback Schemes for DL MU-MIMO ZF Precoding |
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