Adaptive Beam Tracking with the Unscented Kalman Filter for Millimeter Wave Communication
Millimeter wave (mmWave) communication links for 5G cellular technology require high beamforming gain to overcome channel impairments and achieve high throughput. While much work has focused on estimating mmWave channels and designing beamforming schemes, the time dynamic nature of mmWave channels q...
Gespeichert in:
| Veröffentlicht in: | arXiv.org 2018-04 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | arXiv.org |
| container_volume | |
| creator | Larew, Stephen G Love, David J |
| description | Millimeter wave (mmWave) communication links for 5G cellular technology require high beamforming gain to overcome channel impairments and achieve high throughput. While much work has focused on estimating mmWave channels and designing beamforming schemes, the time dynamic nature of mmWave channels quickly renders estimates stale and increases sounding overhead. We model the underlying time dynamic state space of mmWave channels and design sounding beamformers suitable for tracking in a Kalman filtering framework. Given an initial channel estimate, filtering efficiently leads to refined estimates and allows forward prediction for higher sustained beamforming gain during data transmission. From tracked prior channel estimates, adaptively chosen optimal and constrained suboptimal beams reduce sounding overhead while minimizing estimation error. |
| doi_str_mv | 10.48550/arxiv.1804.08640 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_arxiv</sourceid><recordid>TN_cdi_arxiv_primary_1804_08640</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2072081229</sourcerecordid><originalsourceid>FETCH-LOGICAL-a529-6a13ec0ea98e2204e4d5b811a5ae25256e25b64909206b4875b03e19af87861d3</originalsourceid><addsrcrecordid>eNotj09Lw0AUxBdBsNR-AE8ueE59-7KbbI61WCtWvFTEU3hJXu3W_KmbtOq3N229zDAwDPMT4krBWFtj4Jb8j9uPlQU9BhtpOBMDDEMVWI14IUZtuwEAjGI0JhyI90lB287tWd4xVXLpKf909Yf8dt1admuWr3Wbc91xIZ-orKiWM1d27OWq8fLZlaWr-BDfqJ-YNlW1q11OnWvqS3G-orLl0b8PxXJ2v5zOg8XLw-N0sgjIYBJEpELOgSmxjAiadWEyqxQZYjRool6zSCeQIESZtrHJIGSV0MrGNlJFOBTXp9kjd7r1riL_mx740yN_37g5Nba--dpx26WbZufr_lOKECNYhZiEf5X7XM8</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2072081229</pqid></control><display><type>article</type><title>Adaptive Beam Tracking with the Unscented Kalman Filter for Millimeter Wave Communication</title><source>arXiv.org</source><source>Free E- Journals</source><creator>Larew, Stephen G ; Love, David J</creator><creatorcontrib>Larew, Stephen G ; Love, David J</creatorcontrib><description>Millimeter wave (mmWave) communication links for 5G cellular technology require high beamforming gain to overcome channel impairments and achieve high throughput. While much work has focused on estimating mmWave channels and designing beamforming schemes, the time dynamic nature of mmWave channels quickly renders estimates stale and increases sounding overhead. We model the underlying time dynamic state space of mmWave channels and design sounding beamformers suitable for tracking in a Kalman filtering framework. Given an initial channel estimate, filtering efficiently leads to refined estimates and allows forward prediction for higher sustained beamforming gain during data transmission. From tracked prior channel estimates, adaptively chosen optimal and constrained suboptimal beams reduce sounding overhead while minimizing estimation error.</description><identifier>EISSN: 2331-8422</identifier><identifier>DOI: 10.48550/arxiv.1804.08640</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Adaptive filters ; Beamforming ; Beams (radiation) ; Cellular communication ; Channels ; Computer Science - Information Theory ; Data transmission ; Estimates ; Kalman filters ; Mathematics - Information Theory ; Millimeter waves ; Sounding ; Tracking</subject><ispartof>arXiv.org, 2018-04</ispartof><rights>2018. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,780,881,27904</link.rule.ids><backlink>$$Uhttps://doi.org/10.1109/LSP.2019.2944255$$DView published paper (Access to full text may be restricted)$$Hfree_for_read</backlink><backlink>$$Uhttps://doi.org/10.48550/arXiv.1804.08640$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Larew, Stephen G</creatorcontrib><creatorcontrib>Love, David J</creatorcontrib><title>Adaptive Beam Tracking with the Unscented Kalman Filter for Millimeter Wave Communication</title><title>arXiv.org</title><description>Millimeter wave (mmWave) communication links for 5G cellular technology require high beamforming gain to overcome channel impairments and achieve high throughput. While much work has focused on estimating mmWave channels and designing beamforming schemes, the time dynamic nature of mmWave channels quickly renders estimates stale and increases sounding overhead. We model the underlying time dynamic state space of mmWave channels and design sounding beamformers suitable for tracking in a Kalman filtering framework. Given an initial channel estimate, filtering efficiently leads to refined estimates and allows forward prediction for higher sustained beamforming gain during data transmission. From tracked prior channel estimates, adaptively chosen optimal and constrained suboptimal beams reduce sounding overhead while minimizing estimation error.</description><subject>Adaptive filters</subject><subject>Beamforming</subject><subject>Beams (radiation)</subject><subject>Cellular communication</subject><subject>Channels</subject><subject>Computer Science - Information Theory</subject><subject>Data transmission</subject><subject>Estimates</subject><subject>Kalman filters</subject><subject>Mathematics - Information Theory</subject><subject>Millimeter waves</subject><subject>Sounding</subject><subject>Tracking</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GOX</sourceid><recordid>eNotj09Lw0AUxBdBsNR-AE8ueE59-7KbbI61WCtWvFTEU3hJXu3W_KmbtOq3N229zDAwDPMT4krBWFtj4Jb8j9uPlQU9BhtpOBMDDEMVWI14IUZtuwEAjGI0JhyI90lB287tWd4xVXLpKf909Yf8dt1admuWr3Wbc91xIZ-orKiWM1d27OWq8fLZlaWr-BDfqJ-YNlW1q11OnWvqS3G-orLl0b8PxXJ2v5zOg8XLw-N0sgjIYBJEpELOgSmxjAiadWEyqxQZYjRool6zSCeQIESZtrHJIGSV0MrGNlJFOBTXp9kjd7r1riL_mx740yN_37g5Nba--dpx26WbZufr_lOKECNYhZiEf5X7XM8</recordid><startdate>20180423</startdate><enddate>20180423</enddate><creator>Larew, Stephen G</creator><creator>Love, David J</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>AKY</scope><scope>AKZ</scope><scope>GOX</scope></search><sort><creationdate>20180423</creationdate><title>Adaptive Beam Tracking with the Unscented Kalman Filter for Millimeter Wave Communication</title><author>Larew, Stephen G ; Love, David J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a529-6a13ec0ea98e2204e4d5b811a5ae25256e25b64909206b4875b03e19af87861d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Adaptive filters</topic><topic>Beamforming</topic><topic>Beams (radiation)</topic><topic>Cellular communication</topic><topic>Channels</topic><topic>Computer Science - Information Theory</topic><topic>Data transmission</topic><topic>Estimates</topic><topic>Kalman filters</topic><topic>Mathematics - Information Theory</topic><topic>Millimeter waves</topic><topic>Sounding</topic><topic>Tracking</topic><toplevel>online_resources</toplevel><creatorcontrib>Larew, Stephen G</creatorcontrib><creatorcontrib>Love, David J</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>arXiv Computer Science</collection><collection>arXiv Mathematics</collection><collection>arXiv.org</collection><jtitle>arXiv.org</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Larew, Stephen G</au><au>Love, David J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adaptive Beam Tracking with the Unscented Kalman Filter for Millimeter Wave Communication</atitle><jtitle>arXiv.org</jtitle><date>2018-04-23</date><risdate>2018</risdate><eissn>2331-8422</eissn><abstract>Millimeter wave (mmWave) communication links for 5G cellular technology require high beamforming gain to overcome channel impairments and achieve high throughput. While much work has focused on estimating mmWave channels and designing beamforming schemes, the time dynamic nature of mmWave channels quickly renders estimates stale and increases sounding overhead. We model the underlying time dynamic state space of mmWave channels and design sounding beamformers suitable for tracking in a Kalman filtering framework. Given an initial channel estimate, filtering efficiently leads to refined estimates and allows forward prediction for higher sustained beamforming gain during data transmission. From tracked prior channel estimates, adaptively chosen optimal and constrained suboptimal beams reduce sounding overhead while minimizing estimation error.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><doi>10.48550/arxiv.1804.08640</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | EISSN: 2331-8422 |
| ispartof | arXiv.org, 2018-04 |
| issn | 2331-8422 |
| language | eng |
| recordid | cdi_arxiv_primary_1804_08640 |
| source | arXiv.org; Free E- Journals |
| subjects | Adaptive filters Beamforming Beams (radiation) Cellular communication Channels Computer Science - Information Theory Data transmission Estimates Kalman filters Mathematics - Information Theory Millimeter waves Sounding Tracking |
| title | Adaptive Beam Tracking with the Unscented Kalman Filter for Millimeter Wave Communication |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-22T21%3A31%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_arxiv&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Adaptive%20Beam%20Tracking%20with%20the%20Unscented%20Kalman%20Filter%20for%20Millimeter%20Wave%20Communication&rft.jtitle=arXiv.org&rft.au=Larew,%20Stephen%20G&rft.date=2018-04-23&rft.eissn=2331-8422&rft_id=info:doi/10.48550/arxiv.1804.08640&rft_dat=%3Cproquest_arxiv%3E2072081229%3C/proquest_arxiv%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2072081229&rft_id=info:pmid/&rfr_iscdi=true |