Predictable 802.11 packet delivery from wireless channel measurements

RSSI is known to be a fickle indicator of whether a wireless link will work, for many reasons. This greatly complicates operation because it requires testing and adaptation to find the best rate, transmit power or other parameter that is tuned to boost performance. We show that, for the first time, wireless packet delivery can be accurately predicted for commodity 802.11 NICs from only the channel measurements that they provide. Our model uses 802.11n Channel State Information measurements as input to an OFDM receiver model we develop by using the concept of effective SNR. It is simple, easy to deploy, broadly useful, and accurate. It makes packet delivery predictions for 802.11a/g SISO rates and 802.11n MIMO rates, plus choices of transmit power and antennas. We report testbed experiments that show narrow transition regions (<2 dB for most links) similar to the near-ideal case of narrowband, frequency-flat channels. Unlike RSSI, this lets us predict the highest rate that will work for a link, trim transmit power, and more. We use trace-driven simulation to show that our rate prediction is as good as the best rate adaptation algorithms for 802.11a/g, even over dynamic channels, and extends this good performance to 802.11n.

[1]  S. Nanda,et al.  Frame error rates for convolutional codes on fading channels and the concept of effective E/sub b//N/sub 0/ , 1995, Proceedings of GLOBECOM 1995 Mini.

[2]  S. Nanda,et al.  Frame error rates for convolutional codes on fading channels and the concept of effective E/sub b//N/sub 0/ , 1998 .

[3]  Velio Tralli.  Efficient simulation of frame and bit error rate in wireless systems with convolutional codes and correlated fading channels , 1999, WCNC. 1999 IEEE Wireless Communications and Networking Conference (Cat. No.99TH8466).

[4]  Vaduvur Bharghavan,et al.  A power controlled multiple access protocol for wireless packet networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[5]  Wolfgang Zirwas,et al.  Misunderstandings about link adaptation for frequency selective fading channels , 2002, The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[6]  Ramesh Govindan,et al.  Understanding packet delivery performance in dense wireless sensor networks , 2003, SenSys '03.

[7]  Robert Tappan Morris,et al.  Link-level measurements from an 802.11b mesh network , 2004, SIGCOMM '04.

[8]  Bhaskar Krishnamachari,et al.  Experimental study of the effects of transmission power control and blacklisting in wireless sensor networks , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[9]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[10]  Abbas Jamalipour,et al.  Wireless communications , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[11]  John C. Bicket,et al.  Bit-rate selection in wireless networks , 2005 .

[12]  Fouad A. Tobagi,et al.  Packet Error Rate in OFDM-Based Wireless LANs Operating in Frequency Selective Channels , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[13]  Ratul Mahajan,et al.  Measurement-based models of delivery and interference in static wireless networks , 2006, SIGCOMM.

[14]  Vaduvur Bharghavan,et al.  Robust rate adaptation for 802.11 wireless networks , 2006, MobiCom '06.

[15]  Hao Liu,et al.  EESM Based Link Error Prediction for Adaptive MIMO-OFDM System , 2007, 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring.

[16]  Hari Balakrishnan,et al.  PPR: partial packet recovery for wireless networks , 2007, SIGCOMM '07.

[17]  Kate Ching-Ju Lin,et al.  ZipTx: Harnessing Partial Packets in 802.11 Networks , 2008, MobiCom '08.

[18]  Bernard H. Fleury,et al.  Mutual Information Metrics for Fast Link Adaptation in IEEE 802.11n , 2008, 2008 IEEE International Conference on Communications.

[19]  Hari Balakrishnan,et al.  Cabernet: vehicular content delivery using WiFi , 2008, MobiCom '08.

[20]  Haitao Wu,et al.  A Practical SNR-Guided Rate Adaptation , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[21]  Peter Steenkiste,et al.  Efficient channel-aware rate adaptation in dynamic environments , 2008, MobiSys '08.

[22]  Kien T. Truong,et al.  An Experimental Evaluation of Rate Adaptation for Multi-Antenna Systems , 2009, IEEE INFOCOM 2009.

[23]  Dina Katabi,et al.  Frequency-aware rate adaptation and MAC protocols , 2009, MobiCom '09.

[24]  Stephen G. Wilson,et al.  Partial Packet Recovery in Wireless Networks , 2009 .

[25]  Guillem Femenias,et al.  Cross-layer link adaptation for IEEE 802.11n , 2009, 2009 Second International Workshop on Cross Layer Design.

[26]  Hari Balakrishnan,et al.  Cross-layer wireless bit rate adaptation , 2009, SIGCOMM '09.

[27]  Marco Gruteser,et al.  Symphony: Synchronous Two-Phase Rate and Power Control in 802.11 WLANs , 2008, IEEE/ACM Transactions on Networking.

[28]  Srihari Nelakuditi,et al.  AccuRate: Constellation Based Rate Estimation in Wireless Networks , 2010, NSDI.

[29]  Edward W. Knightly,et al.  Modulation Rate Adaptation in Urban and Vehicular Environments: Cross-Layer Implementation and Experimental Evaluation , 2008, IEEE/ACM Transactions on Networking.