MIMO rate adaptation in 802.11n wireless networks

Pefkianakis, Ioannis; Hu, Yun; Wong, Sui‐Lam; Yang, Hao; Lu, Songwu

doi:10.1145/1859995.1860025

Cited by 112 publications

(92 citation statements)

References 10 publications

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“…Note that our results for RAMAS are somewhat different from those reported [4], since they were obtained in different scenarios. RAMAS was previously evaluated only on the 2.4GHz frequency range, which significantly limits the performance benefits of 802.11n features [18], [5].…”

Section: Interference-freementioning

confidence: 99%

“…Rate Adaptation: Rate adaptation has been one of the most popular research topics in WLANs [10], [1], [19] and new algorithms for 802.11n networks have been proposed [2], [5], [20], [21]. Although solutions for legacy clients have been effective, they fall short when applied in 802.11n OFDM-MIMO settings [5].…”

Section: Related Workmentioning

confidence: 99%

“…Although solutions for legacy clients have been effective, they fall short when applied in 802.11n OFDM-MIMO settings [5]. Existing 802.11n solutions require either costly CSI [22], [2] or some form of a guided search (e.g., by probing candidate rates) to determine the best operating rate [5], which is inefficient when the search space is large. Other algorithms for MIMO environments do not consider other 802.11n features, such as channel bonding [23], or consider alternative energy efficiency goals [21].…”

Section: Related Workmentioning

confidence: 99%

“…However, complete CSI information is costly to obtain and store [3] and is therefore supported by very few 802.11n devices. Existing RA solutions adopt a practical approach and use a credit-based system [4] or rate sampling [5], [6], [7]. Instead of adapting the rate based on understanding the impact of environment conditions on 802.11n features, these solutions rely on a routine to converge to the best rate, which can be costly or misdirected.…”

Section: Introductionmentioning

confidence: 99%

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Joint rate and channel width adaptation for 802.11 MIMO wireless networks

Deek

García-Villegas

Belding

et al. 2013

2013 IEEE International Conference on Sensing, Communications and Networking (SECON)

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Abstract-The emergence of MIMO antennas and channel bonding in 802.11n wireless networks has resulted in a huge leap in capacity compared with legacy 802.11 systems. This leap, however, adds complexity to selecting the right transmission rate. Not only does the appropriate data rate need to be selected, but also the MIMO transmission technique (e.g., Spatial Diversity or Spatial Multiplexing), the number of streams, and the channel width. Incorporating these features into a rate adaptation (RA) solution requires a new set of rules to accurately evaluate channel conditions and select the appropriate transmission setting with minimal overhead. To address these challenges, we propose ARAMIS (Agile Rate Adaptation for MIMO Systems), a standard-compliant, closed-loop RA solution that jointly adapts rate and bandwidth. ARAMIS adapts transmission rates on a per-packet basis; we believe it is the first 802.11n RA algorithm that simultaneously adapts rate and channel width. We have implemented ARAMIS on Atheros-based devices and deployed it on our 15-node testbed. Our experiments show that ARAMIS accurately adapts to a wide variety of channel conditions with negligible overhead. Furthermore, ARAMIS outperforms existing RA algorithms in 802.11n environments with up to a 10 fold increase in throughput.

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Section: Interference-freementioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Joint rate and channel width adaptation for 802.11 MIMO wireless networks

Deek

García-Villegas

Belding

et al. 2013

2013 IEEE International Conference on Sensing, Communications and Networking (SECON)

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“…They can be classified into frame-based [13,[26][27][28][29][30][31], SNR-based [9,[32][33][34], and PHY-layer based [9][10][11]. Frame-based algorithms are often used in practice due to their simplicity but they are slow to respond to rapidly changing channel conditions in mobile environments.…”

Section: Rate Control and Client Roamingmentioning

confidence: 99%

Bringing Mobility-Awareness to WLANs using PHY Layer Information

Sen

Koutsonikolas

2014

Proceedings of the 10th ACM International on Conference on Emerging Networking Experiments and Technologies

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With the proliferation of smartphones and tablets, mobile devices are soon becoming a preferred medium of Internet access in Wireless LANs (WLANs). Due to their smaller form factor, these truly mobile devices allow the users to access the wireless networks while undergoing different types of mobility, posing new challenges to wireless protocols. Current history-based protocols that maximize performance in static settings do not work well in mobile settings where wireless conditions change rapidly. Thus, today's WLANs need to be able to determine the type of the client's mobility and employ appropriate strategies in order to sustain high performance. While previous work tried to detect mobility using hints from sensors available in today's mobile devices, in this work, we demonstrate how different mobility modes can be distinguished by using physical layer information -Channel State Information (CSI) and Time-of-Flight (ToF) -available at commodity APs, with no modifications on the client side.In addition, we demonstrate how fine-grained mobility determination can be exploited to improve performance of client roaming, rate control, frame aggregation, and MIMO beamforming. Our testbed experiments show that our mobility classification algorithm achieves more than 92% accuracy in a variety of scenarios, and the combined throughput gain of all four mobility-aware protocols over their mobility-oblivious counterparts can be more than 100%.

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Throughput, energy efficiency and interference characterisation of 802.11ac

Zeng

Pathak

Mohapatra

2015

Trans. Emerging Tel. Tech.

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This paper is the first of its kind in presenting a detailed characterisation of IEEE 802.11ac using real experiments. 802.11ac is the latest Wireless Local Area Network (WLAN) standard that is rapidly being adapted because of its potential to deliver very high throughput. The throughput increase in 802.11ac can be attributed to three factors—larger channel width (80/160 MHz), support for denser modulation (256 Quadrature Amplitude Modulation (QAM)) and increased number of spatial streams for Multiple‐input Multiple‐output (MIMO). We provide an experiment evaluation of these factors and their impact using a real 802.11ac testbed. Our findings provide numerous insights on benefits and challenges associated with using 802.11ac in practice. Because utilisation of larger channel width is one of the most significant changes in 802.11ac, we focus our study on understanding its impact on energy efficiency and interference. Using experiments, we show that utilising larger channel width is in general less energy efficient because of its higher power consumption in idle listening mode. Increasing the number of MIMO spatial streams is comparatively more energy efficient for achieving the same percentage increase in throughput. We also show that 802.11ac link witnesses severe unfairness issues when it coexists with legacy 802.11. We provide a detailed analysis to show how medium access in heterogeneous channel width environment leads to the unfairness issues. We believe that these and many other findings presented in this work will help in understanding and resolving various performance issues of next generation WLANs. Copyright © 2015 John Wiley & Sons, Ltd.

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MIMO rate adaptation in 802.11n wireless networks

Cited by 112 publications

References 10 publications

Joint rate and channel width adaptation for 802.11 MIMO wireless networks

Joint rate and channel width adaptation for 802.11 MIMO wireless networks

Bringing Mobility-Awareness to WLANs using PHY Layer Information

Throughput, energy efficiency and interference characterisation of 802.11ac

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