Adaptive Subcarrier Grouping for MMSE-SMI Adaptive Array Interference Suppression
Inter-user interference (IUI) suppression is a prime matter for mobile communication systems. Channel state information (CSI), meanwhile, is severely affected by the receiver additive noise effect. Sample matrix inversion (SMI) based minimum mean square error (MMSE) adaptive array is a powerful mean...
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| Veröffentlicht in: | IEEE access 2021, Vol.9, p.18361-18372 |
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| creator | Shima, Kosuke Kojima, Shun Ito, Koki Maruta, Kazuki Ahn, Chang-Jun |
| description | Inter-user interference (IUI) suppression is a prime matter for mobile communication systems. Channel state information (CSI), meanwhile, is severely affected by the receiver additive noise effect. Sample matrix inversion (SMI) based minimum mean square error (MMSE) adaptive array is a powerful means to suppress noise enhancement with the aid of data symbols. However, its effectiveness is limited under an insufficient number of symbols available. Based on the multi-carrier transmission system, this paper proposes an adaptive subcarrier grouping to expand the number of received symbols for a covariance matrix calculation. The grouping size is adaptively adjusted by observing the dispersion of adjacent subcarriers. Simulative results reveal the effectiveness of the proposed adaptive algorithm; superior bit error rate (BER) performance can be attained under various Rician K factors. |
| doi_str_mv | 10.1109/ACCESS.2021.3053989 |
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Channel state information (CSI), meanwhile, is severely affected by the receiver additive noise effect. Sample matrix inversion (SMI) based minimum mean square error (MMSE) adaptive array is a powerful means to suppress noise enhancement with the aid of data symbols. However, its effectiveness is limited under an insufficient number of symbols available. Based on the multi-carrier transmission system, this paper proposes an adaptive subcarrier grouping to expand the number of received symbols for a covariance matrix calculation. The grouping size is adaptively adjusted by observing the dispersion of adjacent subcarriers. Simulative results reveal the effectiveness of the proposed adaptive algorithm; superior bit error rate (BER) performance can be attained under various Rician <inline-formula> <tex-math notation="LaTeX">K </tex-math></inline-formula> factors.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2021.3053989</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Adaptive algorithms ; Adaptive array ; Adaptive systems ; Arrays ; Bandwidth ; Bit error rate ; channel estimation ; Coherence ; Complexity theory ; Covariance matrix ; Interference ; Interference suppression ; Mobile communication systems ; Rayleigh channels ; Rician channels ; Rician fading ; sample matrix inversion ; subcarrier grouping ; Subcarriers ; Symbols</subject><ispartof>IEEE access, 2021, Vol.9, p.18361-18372</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c544t-7dc40606a06c9f46a25b6e9d74b5e75157323d974883124b4ed3b107f7eb37813</citedby><cites>FETCH-LOGICAL-c544t-7dc40606a06c9f46a25b6e9d74b5e75157323d974883124b4ed3b107f7eb37813</cites><orcidid>0000-0003-4197-3397 ; 0000-0001-9635-3182 ; 0000-0002-4475-4387 ; 0000-0001-9227-4663</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9335018$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,864,2100,4021,27631,27921,27922,27923,54931</link.rule.ids></links><search><creatorcontrib>Shima, Kosuke</creatorcontrib><creatorcontrib>Kojima, Shun</creatorcontrib><creatorcontrib>Ito, Koki</creatorcontrib><creatorcontrib>Maruta, Kazuki</creatorcontrib><creatorcontrib>Ahn, Chang-Jun</creatorcontrib><title>Adaptive Subcarrier Grouping for MMSE-SMI Adaptive Array Interference Suppression</title><title>IEEE access</title><addtitle>Access</addtitle><description>Inter-user interference (IUI) suppression is a prime matter for mobile communication systems. Channel state information (CSI), meanwhile, is severely affected by the receiver additive noise effect. Sample matrix inversion (SMI) based minimum mean square error (MMSE) adaptive array is a powerful means to suppress noise enhancement with the aid of data symbols. However, its effectiveness is limited under an insufficient number of symbols available. Based on the multi-carrier transmission system, this paper proposes an adaptive subcarrier grouping to expand the number of received symbols for a covariance matrix calculation. The grouping size is adaptively adjusted by observing the dispersion of adjacent subcarriers. Simulative results reveal the effectiveness of the proposed adaptive algorithm; superior bit error rate (BER) performance can be attained under various Rician <inline-formula> <tex-math notation="LaTeX">K </tex-math></inline-formula> factors.</description><subject>Adaptive algorithms</subject><subject>Adaptive array</subject><subject>Adaptive systems</subject><subject>Arrays</subject><subject>Bandwidth</subject><subject>Bit error rate</subject><subject>channel estimation</subject><subject>Coherence</subject><subject>Complexity theory</subject><subject>Covariance matrix</subject><subject>Interference</subject><subject>Interference suppression</subject><subject>Mobile communication systems</subject><subject>Rayleigh channels</subject><subject>Rician channels</subject><subject>Rician fading</subject><subject>sample matrix inversion</subject><subject>subcarrier grouping</subject><subject>Subcarriers</subject><subject>Symbols</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNkU9Lw0AQxRdRsNR-gl4CnlP3bzZ7LKXWQItI9LxsNpOSUrNxkgp-e1NTinOZYZjfewOPkDmjC8aoeVquVus8X3DK2UJQJUxqbsiEs8TEQonk9t98T2Zdd6BDpcNK6Ql5W5au7etviPJT4R1iDRhtMJzautlHVcBot8vXcb7LouvlEtH9RFnTA1aA0Pgz3LYIXVeH5oHcVe7YwezSp-Tjef2-eom3r5tstdzGXknZx7r0kiY0cTTxppKJ46pIwJRaFgq0YkoLLkqjZZoKxmUhoRQFo7rSUAidMjEl2ahbBnewLdafDn9scLX9WwTcW4d97Y9gJaOOKZNyxrkURVmUlVLMe6a81tXgNCWPo1aL4esEXW8P4YTN8L7lMk2UEXoAp0SMVx5D1yFUV1dG7TkKO0Zhz1HYSxQDNR-pGgCuhBFCUZaKX1jjgok</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Shima, Kosuke</creator><creator>Kojima, Shun</creator><creator>Ito, Koki</creator><creator>Maruta, Kazuki</creator><creator>Ahn, Chang-Jun</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| subjects | Adaptive algorithms Adaptive array Adaptive systems Arrays Bandwidth Bit error rate channel estimation Coherence Complexity theory Covariance matrix Interference Interference suppression Mobile communication systems Rayleigh channels Rician channels Rician fading sample matrix inversion subcarrier grouping Subcarriers Symbols |
| title | Adaptive Subcarrier Grouping for MMSE-SMI Adaptive Array Interference Suppression |
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