Enhanced statistics-based rate adaptation for 802.11 wireless networks

Rate adaptation is a common technique to exploit channel diversity in wireless networks. Despite the many rate adaptation algorithms proposed for 802.11 networks, statistics-based schemes remain the most widely adopted approaches in commercial 802.11 products due to their simplicity and practicality. However, statistics-based schemes suffer some disadvantages. Our previous research effort revealed the rate avalanche effect that could significantly degrade the network performance of heavily loaded 802.11 networks. In this work, we propose RADAR (Rate-Alert DynAmic Rts/cts exchange), a novel enhanced rate adaptation system that can effectively alleviate the impact of the rate avalanche effect. RADAR detects rate avalanche through maintaining a dynamic range-based mapping between rates and RSSI (received signal strength indicator) measurements. It judiciously exploits dynamic RTS/CTS exchanges to effectively suppress the rate avalanche effect while at the same time minimizes the transmission overhead of RTS/CTS exchanges. Being fully compatible with current 802.11 standards, RADAR can be readily implemented in the NIC driver. Through extensive simulations using realistic channel propagation and reception models, we demonstrate that RADAR is a practical and efficient performance enhancement approach for multi-rate 802.11 networks.

[1]  Xiaobo Zhou,et al.  Rate avalanche: The performance degradation in multi-rate 802.11 WLANs , 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

[2]  Reginald L. Lagendijk,et al.  Hybrid rate control for IEEE 802.11 , 2004, MobiWac '04.

[3]  Hongwei Zhang,et al.  On exploiting asymmetric wireless links via one-way estimation , 2007, MobiHoc '07.

[4]  Marco Zuniga,et al.  An analysis of unreliability and asymmetry in low-power wireless links , 2007, TOSN.

[5]  David Wetherall,et al.  Predictable 802.11 packet delivery from wireless channel measurements , 2010, SIGCOMM '10.

[6]  Xiaobo Zhou,et al.  RADAR: Rate-Alert Dynamic RTS/CTS Exchange for Performance Enhancement in Multi-Rate Wireless Networks , 2008, 2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing.

[7]  Chun-cheng Chen,et al.  Rate-Adaptive Framing for Interfered Wireless Networks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[8]  Periklis Chatzimisios,et al.  Delay Distribution Analysis of the RTS/CTS mechanism of IEEE 802.11 , 2006, Proceedings. 2006 31st IEEE Conference on Local Computer Networks.

[9]  Roland de Haan,et al.  Why RTS-CTS is not your ideal wireless LAN multiple access protocol , 2005, IEEE Wireless Communications and Networking Conference, 2005.

[10]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

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

[12]  Leo Monteban,et al.  WaveLAN®-II: A high-performance wireless LAN for the unlicensed band , 1997, Bell Labs Technical Journal.

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

[14]  Vaduvur Bharghavan,et al.  MACAW: a media access protocol for wireless LAN's , 1994, SIGCOMM 1994.

[15]  Anura P. Jayasumana,et al.  Effect of hidden terminals on the performance of IEEE 802.11 MAC protocol , 1998, Proceedings 23rd Annual Conference on Local Computer Networks. LCN'98 (Cat. No.98TB100260).

[16]  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.

[17]  Edward W. Knightly,et al.  Opportunistic media access for multirate ad hoc networks , 2002, MobiCom '02.

[18]  Jenhui Chen,et al.  The impact of RTS threshold on IEEE 802.11 MAC protocol , 2002, Ninth International Conference on Parallel and Distributed Systems, 2002. Proceedings..

[19]  David A. Maltz,et al.  Dynamic Source Routing in Ad Hoc Wireless Networks , 1994, Mobidata.

[20]  Victor C. M. Leung,et al.  A rate adaptation algorithm for IEEE 802.11 WLANs based on MAC-layer loss differentiation , 2005, 2nd International Conference on Broadband Networks, 2005..

[21]  Imad Aad.  Quality of service in wireless local area networks. (Qualité de service dans les réseaux locaux sans-fil) , 2002 .

[22]  P. Karn,et al.  MACA-a New Channel Access Method for Packet Radio , 1990 .

[23]  Paramvir Bahl,et al.  A rate-adaptive MAC protocol for multi-Hop wireless networks , 2001, MobiCom '01.

[24]  Songwu Lu,et al.  MIMO rate adaptation in 802.11n wireless networks , 2010, MobiCom.

[25]  Yantai Shu,et al.  RTS threshold self-tuning algorithm based on delay analysis on 802.11 DCF , 2005, Proceedings. 2005 International Conference on Wireless Communications, Networking and Mobile Computing, 2005..

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

[27]  Victor C. M. Leung,et al.  Design of an effective loss-distinguishable MAC protocol for 802.11 WLAN , 2005, IEEE Communications Letters.

[28]  Xiaobo Zhou,et al.  Rate avalanche: Effects on the performance of multi-rate 802.11 wireless networks , 2009, Simul. Model. Pract. Theory.

[29]  J. J. Garcia-Luna-Aceves,et al.  Floor acquisition multiple access (FAMA) for packet-radio networks , 1995, SIGCOMM '95.

[30]  I. Rubin,et al.  An adaptive RTS/CTS control mechanism for IEEE 802.11 MAC protocol , 2003, The 57th IEEE Semiannual Vehicular Technology Conference, 2003. VTC 2003-Spring..

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

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

[33]  Thierry Turletti,et al.  IEEE 802.11 rate adaptation: a practical approach , 2004, MSWiM '04.

[34]  Shruti Sanadhya,et al.  On link rate adaptation in 802.11n WLANs , 2011, 2011 Proceedings IEEE INFOCOM.

[35]  Sunghyun Choi,et al.  A Time Lag Analysis of R & D Effect ell Total Factor Productivity in Information and Communication Industry , 2006 .

[36]  P. Gburzynski,et al.  Hidden Problems with the Hidden Node Problem , 2006, 23rd Biennial Symposium on Communications, 2006.

[37]  Martin Reisslein,et al.  MPEG-4 and H.263 video traces for network performance evaluation , 2001, IEEE Netw..

[38]  Tomasz Imielinski,et al.  Mobile Computing , 1996 .

[39]  Kevin C. Almeroth,et al.  IQU: practical queue-based user association management for WLANs , 2006, MobiCom '06.

[40]  Seongkwan Kim,et al.  CARA: Collision-Aware Rate Adaptation for IEEE 802.11 WLANs , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.