Rate adaptation for 802.11 multiuser mimo networks
In multiuser MIMO (MU-MIMO) networks, the optimal bit rate of a user is highly dynamic and changes from one packet to the next. This breaks traditional bit rate adaptation algorithms, which rely on recent history to predict the best bit rate for the next packet. To address this problem, we introduce...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | en_US |
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Association for Computing Machinery
2014
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| Online Access: | http://hdl.handle.net/1721.1/87075 https://orcid.org/0000-0003-4854-4157 |
| _version_ | 1826188508358770688 |
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| author | Shen, Wei-Liang Tung, Yu-Chih Lee, Kuang-Che Lin, Kate Ching-Ju Gollakota, Shyamnath Katabi, Dina Chen, Ming-Syan |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Shen, Wei-Liang Tung, Yu-Chih Lee, Kuang-Che Lin, Kate Ching-Ju Gollakota, Shyamnath Katabi, Dina Chen, Ming-Syan |
| author_sort | Shen, Wei-Liang |
| collection | MIT |
| description | In multiuser MIMO (MU-MIMO) networks, the optimal bit rate of a user is highly dynamic and changes from one packet to the next. This breaks traditional bit rate adaptation algorithms, which rely on recent history to predict the best bit rate for the next packet. To address this problem, we introduce TurboRate, a rate adaptation scheme for MU-MIMO LANs. TurboRate shows that clients in a MU-MIMO LAN can adapt their bit rate on a per-packet basis if each client learns two variables: its SNR when it transmits alone to the access point, and the direction along which its signal is received at the AP. TurboRate also shows that each client can compute these two variables passively without exchanging control frames with the access point. A TurboRate client then annotates its packets with these variables to enable other clients to pick the optimal bit rate and transmit concurrently to the AP. A prototype implementation in USRP-N200 shows that traditional rate adaptation does not deliver the gains of MU-MIMO WLANs, and can interact negatively with MU-MIMO, leading to low throughput. In contrast, enabling MU-MIMO with TurboRate provides a mean throughput gain of 1.7x and 2.3x, for 2-antenna and 3-antenna APs respectively. |
| first_indexed | 2024-09-23T08:00:26Z |
| format | Article |
| id | mit-1721.1/87075 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T08:00:26Z |
| publishDate | 2014 |
| publisher | Association for Computing Machinery |
| record_format | dspace |
| spelling | mit-1721.1/870752022-09-23T10:15:04Z Rate adaptation for 802.11 multiuser mimo networks Shen, Wei-Liang Tung, Yu-Chih Lee, Kuang-Che Lin, Kate Ching-Ju Gollakota, Shyamnath Katabi, Dina Chen, Ming-Syan Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Katabi, Dina In multiuser MIMO (MU-MIMO) networks, the optimal bit rate of a user is highly dynamic and changes from one packet to the next. This breaks traditional bit rate adaptation algorithms, which rely on recent history to predict the best bit rate for the next packet. To address this problem, we introduce TurboRate, a rate adaptation scheme for MU-MIMO LANs. TurboRate shows that clients in a MU-MIMO LAN can adapt their bit rate on a per-packet basis if each client learns two variables: its SNR when it transmits alone to the access point, and the direction along which its signal is received at the AP. TurboRate also shows that each client can compute these two variables passively without exchanging control frames with the access point. A TurboRate client then annotates its packets with these variables to enable other clients to pick the optimal bit rate and transmit concurrently to the AP. A prototype implementation in USRP-N200 shows that traditional rate adaptation does not deliver the gains of MU-MIMO WLANs, and can interact negatively with MU-MIMO, leading to low throughput. In contrast, enabling MU-MIMO with TurboRate provides a mean throughput gain of 1.7x and 2.3x, for 2-antenna and 3-antenna APs respectively. National Science Council (China) (contract No. NSC 100-2221-E-001-005-MY2) National Science Foundation (U.S.) (NSF Grant CNS-1117194) 2014-05-21T20:27:20Z 2014-05-21T20:27:20Z 2012 Article http://purl.org/eprint/type/ConferencePaper 9781450311595 1543-5679 http://hdl.handle.net/1721.1/87075 Shen, Wei-Liang, Yu-Chih Tung, Kuang-Che Lee, Kate Ching-Ju Lin, Shyamnath Gollakota, Dina Katabi, and Ming-Syan Chen. “Rate Adaptation for 802.11 Multiuser Mimo Networks.” Proceedings of the 18th Annual International Conference on Mobile Computing and Networking - Mobicom ’12 (2012). https://orcid.org/0000-0003-4854-4157 en_US http://dx.doi.org/10.1145/2348543.2348551 Proceedings of the 18th annual international conference on Mobile computing and networking - Mobicom '12 Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Association for Computing Machinery Other univ. web domain |
| spellingShingle | Shen, Wei-Liang Tung, Yu-Chih Lee, Kuang-Che Lin, Kate Ching-Ju Gollakota, Shyamnath Katabi, Dina Chen, Ming-Syan Rate adaptation for 802.11 multiuser mimo networks |
| title | Rate adaptation for 802.11 multiuser mimo networks |
| title_full | Rate adaptation for 802.11 multiuser mimo networks |
| title_fullStr | Rate adaptation for 802.11 multiuser mimo networks |
| title_full_unstemmed | Rate adaptation for 802.11 multiuser mimo networks |
| title_short | Rate adaptation for 802.11 multiuser mimo networks |
| title_sort | rate adaptation for 802 11 multiuser mimo networks |
| url | http://hdl.handle.net/1721.1/87075 https://orcid.org/0000-0003-4854-4157 |
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