Cross-layer wireless bit rate adaptation
This paper presents SoftRate, a wireless bit rate adaptation protocol that is responsive to rapidly varying channel conditions. Unlike previous work that uses either frame receptions or signal-to-noise ratio (SNR) estimates to select bit rates, SoftRate uses confidence information calculated by the...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Association for Computing Machinery (ACM)
2013
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| Online Access: | http://hdl.handle.net/1721.1/79675 https://orcid.org/0000-0002-1455-9652 |
| _version_ | 1826195955995639808 |
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| author | Vutukuru, Mythili Balakrishnan, Hari Jamieson, Kyle |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Vutukuru, Mythili Balakrishnan, Hari Jamieson, Kyle |
| author_sort | Vutukuru, Mythili |
| collection | MIT |
| description | This paper presents SoftRate, a wireless bit rate adaptation protocol that is responsive to rapidly varying channel conditions. Unlike previous work that uses either frame receptions or signal-to-noise ratio (SNR) estimates to select bit rates, SoftRate uses confidence information calculated by the physical layer and exported to higher layers via the SoftPHY interface to estimate the prevailing channel bit error rate (BER). Senders use this BER estimate, calculated over each received packet (even when the packet has no bit errors), to pick good bit rates. SoftRate's novel BER computation works across different wireless environments and hardware without requiring any retraining. SoftRate also uses abrupt changes in the BER estimate to identify interference, enabling it to reduce the bit rate only in response to channel errors caused by attenuation or fading. Our experiments conducted using a software radio prototype show that SoftRate achieves 2X higher throughput than popular frame-level protocols such as SampleRate and RRAA. It also achieves 20% more throughput than an SNR-based protocol trained on the operating environment, and up to 4X higher throughput than an untrained SNR-based protocol. The throughput gains using SoftRate stem from its ability to react to channel variations within a single packet-time and its robustness to collision losses. |
| first_indexed | 2024-09-23T10:18:29Z |
| format | Article |
| id | mit-1721.1/79675 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T10:18:29Z |
| publishDate | 2013 |
| publisher | Association for Computing Machinery (ACM) |
| record_format | dspace |
| spelling | mit-1721.1/796752022-09-26T17:06:35Z Cross-layer wireless bit rate adaptation Vutukuru, Mythili Balakrishnan, Hari Jamieson, Kyle Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Vutukuru, Mythili Balakrishnan, Hari This paper presents SoftRate, a wireless bit rate adaptation protocol that is responsive to rapidly varying channel conditions. Unlike previous work that uses either frame receptions or signal-to-noise ratio (SNR) estimates to select bit rates, SoftRate uses confidence information calculated by the physical layer and exported to higher layers via the SoftPHY interface to estimate the prevailing channel bit error rate (BER). Senders use this BER estimate, calculated over each received packet (even when the packet has no bit errors), to pick good bit rates. SoftRate's novel BER computation works across different wireless environments and hardware without requiring any retraining. SoftRate also uses abrupt changes in the BER estimate to identify interference, enabling it to reduce the bit rate only in response to channel errors caused by attenuation or fading. Our experiments conducted using a software radio prototype show that SoftRate achieves 2X higher throughput than popular frame-level protocols such as SampleRate and RRAA. It also achieves 20% more throughput than an SNR-based protocol trained on the operating environment, and up to 4X higher throughput than an untrained SNR-based protocol. The throughput gains using SoftRate stem from its ability to react to channel variations within a single packet-time and its robustness to collision losses. National Science Foundation (U.S.) (Grant CNS-0721702) National Science Foundation (U.S.) (Grant CNS-0520032) Foxconn International Holdings Ltd. 2013-07-23T14:18:52Z 2013-07-23T14:18:52Z 2009 Article http://purl.org/eprint/type/ConferencePaper 9781605585949 http://hdl.handle.net/1721.1/79675 Mythili Vutukuru, Hari Balakrishnan, and Kyle Jamieson. 2009. Cross-layer wireless bit rate adaptation. In Proceedings of the ACM SIGCOMM 2009 conference on Data communication (SIGCOMM '09). ACM, New York, NY, USA, 3-14. https://orcid.org/0000-0002-1455-9652 en_US http://dx.doi.org/10.1145/1592568.1592571 Proceedings of the ACM SIGCOMM 2009 conference on Data communication (SIGCOMM '09) Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Association for Computing Machinery (ACM) Balakrishnan via Amy Stout |
| spellingShingle | Vutukuru, Mythili Balakrishnan, Hari Jamieson, Kyle Cross-layer wireless bit rate adaptation |
| title | Cross-layer wireless bit rate adaptation |
| title_full | Cross-layer wireless bit rate adaptation |
| title_fullStr | Cross-layer wireless bit rate adaptation |
| title_full_unstemmed | Cross-layer wireless bit rate adaptation |
| title_short | Cross-layer wireless bit rate adaptation |
| title_sort | cross layer wireless bit rate adaptation |
| url | http://hdl.handle.net/1721.1/79675 https://orcid.org/0000-0002-1455-9652 |
| work_keys_str_mv | AT vutukurumythili crosslayerwirelessbitrateadaptation AT balakrishnanhari crosslayerwirelessbitrateadaptation AT jamiesonkyle crosslayerwirelessbitrateadaptation |