A practical approach to rate adaptation for multi-antenna systems

Nguyen, Duy Duc; Garcia-Luna-Aceves, J.J.

doi:10.1109/icnp.2011.6089072

Cited by 35 publications

(23 citation statements)

References 17 publications

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“…Even without the training mechanism, ARAMIS outperforms other algorithms with throughput gains of up to 26% over Minstrel HT, 124% over Ath9k, and 287% over RAMAS. 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-freecontrasting

confidence: 55%

“…We compare the performance of ARAMIS to that of two widely used open source 802.11n RA solutions, Ath9k [7] and Minstrel HT [6], and RAMAS [4], which was recently shown to be one of the best performing 802.11n RA solutions. We run RAMAS using the implementation made available by its authors.…”

Section: A Testbed Environmentmentioning

confidence: 99%

“…We compare ARAMIS to leading RA solutions for 802.11n, namely Ath9k [7], Minstrel HT [6], and RAMAS [4]. We evaluate the solutions under various scenarios, including interference, mobility, and hidden nodes.…”

Section: Introductionmentioning

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-freecontrasting

confidence: 55%

Section: A Testbed Environmentmentioning

confidence: 99%

Section: Introductionmentioning

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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Utilising SCM – MIMO Channel Model Based on V-BLAST Channel Coding in V2V Communication

Al-Khalil

Turner

Al-Sherbaz

2015

Lecture Notes in Computer Science

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Abstract. Vehicular ad hoc networks VANETs has recently received significant attention in intelligent transport systems (ITS) research. It provides the driver with information regarding traffic and road conditions which is needed to reduce accidents, which will save many people's lives. In Vehicle-to-vehicle V2V communication the high-speed mobility of the nodes is the challenge, which significantly affects the reliability of communication. In this paper the utilising of SCM-MIMO channel model, (which is based on V-BLAST channel coding) is present to evaluate the performance of the PHY layer in V2V communication. The simulation results observed that the SCM model can overcome the propagation issues such as path loss, multipath fading and shadowing loss. The simulation considered three different environments, high, medium and low disruptions in urban traffic.

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A practical approach to rate adaptation for multi-antenna systems

Cited by 35 publications

References 17 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

Utilising SCM – MIMO Channel Model Based on V-BLAST Channel Coding in V2V Communication

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