Rate adaptation algorithms for IEEE 802.11 networks: A survey and comparison

Biaz, Saad; Wu, Shaoen

doi:10.1109/iscc.2008.4625680

Cited by 79 publications

(55 citation statements)

References 13 publications

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“…In IEEE 802.11b, the transmission rates are 11, 5.5, 2, and 1 Mbps, whereas IEEE 802.11a/g offers 54, 48, 36, 24, 18, 12, 9, and 6 Mbps. These protocols specify multiple transmission rates, and the appropriate transmission rate can be selected so as not to exceed a certain bit error or frame error rate [15]. The appropriate transmission rate is usually selected by the original vendor algorithm † .…”

Section: Multi-rate Transmission Of Ieee80211 and Existing Throughpumentioning

confidence: 99%

Improvement of Throughput Prediction Scheme Considering Terminal Distribution in Multi-Rate WLAN Considering Both CSMA/CA and Frame Collision

Hamamoto

Takano

Obata

et al. 2016

IEICE Trans. Inf. & Syst.

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SUMMARYWireless Local Area Networks (WLANs) based on the IEEE 802.11 standard have been increasingly used. Access Points (APs) are being established in various public places, such as railway stations and airports, as well as private residences. Moreover, the rate of public WLAN services continues to increase. Throughput prediction of an AP in a multi-rate environment, i.e., predicting the amount of receipt data (including retransmission packets at an AP), is an important issue for wireless network design. Moreover, it is important to solve AP placement and selection problems. To realize the throughput prediction, we have proposed an AP throughput prediction method that considers terminal distribution. We compared the predicted throughput of the proposed method with a method that uses linear order computation and confirmed the performance of the proposed method, not by a network simulator but by the numerical computation. However, it is necessary to consider the impact of CSMA/CA in the MAC layer, because throughput is greatly influenced by frame collision. In this paper, we derive an effective transmission rate considering CSMA/CA and frame collision. We then compare the throughput obtained using the network simulator NS2 with a prediction value calculated by the proposed method. Simulation results show that the maximum relative error of the proposed method is approximately 6% and 15% for UDP and TCP, respectively, while that is approximately 17% and 21% in existing method.

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Section: Multi-rate Transmission Of Ieee80211 and Existing Throughpumentioning

confidence: 99%

Improvement of Throughput Prediction Scheme Considering Terminal Distribution in Multi-Rate WLAN Considering Both CSMA/CA and Frame Collision

Hamamoto

Takano

Obata

et al. 2016

IEICE Trans. Inf. & Syst.

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“…It is known that f = η satisfies (2) (2) in H. This solution is an optimal approximation of η in the least squares sense [27,Lem. 5].…”

Section: Adaptive Kernel Regressionmentioning

confidence: 99%

“…The IEEE 802.11 standards specify the use of a common MCS for all subcarriers. Link adaptation for 802.11-like systems is traditionally based on evaluation of the packet errors and/or simple one-dimensional features such as average SNR [2]. The autorate fallback (ARF) algorithm [3] as well as receiver-based autorate (RBAR) [4] are classic examples.…”

Section: Introductionmentioning

confidence: 99%

Link adaptation for BICM-OFDM through adaptive kernel regression

Wahls

Poor

2013

2013 IEEE International Conference on Acoustics, Speech and Signal Processing

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The packet error rate (PER) of wireless BICM-OFDM systems is notoriously difficult to predict analytically. This remains true even if all subcarriers use a common modulation and coding scheme (MCS). Link adaptation, which here shall be understood as the process of adapting the MCS in order to maximize goodput, therefore remains a major challenge. Non-parametric learning is an elegant way to evade the lack of robust analytical models. Learning from multidimensional features is particularly interesting because onedimensional features can characterize frequency-selective channels only roughly. However, most of the literature discusses methods that are not truly online. Either the computational costs become unbearable over time or the method saturates and effectively stops learning. The modified k nearest neighbors algorithm (k-NN) seems to be the only exception currently. However, k-NN has well-known weaknesses in learning from small sample sets. Two adaptive kernel regression (AKR) methods are therefore proposed instead. Simulation results are reported for a setup in which several practically relevant conditions that have been mostly ignored in previous studies using multidimensional features (imperfect channel knowledge, Doppler shift, feedback delay, collisions) are modeled.

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“…The data rate is configured according to the distance from AP in (c). Although there are other methods of configuring the data rate [10], we use the most typical approach, configuring it according to the distance from AP. The relationship between the distance and the data rate is different at each wireless device or vendor.…”

Section: A Scenariosmentioning

confidence: 99%

“…1) Total throughput: First, to make sure the effect of Bianchi's model, we vary the number of stations in the range of [10,100] and measure the total throughput. Figure 2 shows the total throughput for basic-CSMA/CA, CSMA/CA with RTS/CTS, Bianchi's model and Bianchi's model with RTS/CTS.…”

Section: (A)ideal Scenariomentioning

confidence: 99%

Multiple access in MAC layer based on surrounding conditions of wireless stations

Matsumoto

Oguchi

2012

2012 the 11th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net)

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Many parameters of wireless communications are uniquely configured, regardless of their communication environments. However, we believe that stations are able to achieve efficiency in communications using surrounding information. One of the systems that is expected to improve the performance of wireless communications is Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) in the MAC Layer. In this paper, we propose a new model to improve network performance using information about the number of stations in the backoff algorithm of CSMA/CA. Although there are already some proposals for the use of the backoff algorithm, most of them are proposed under an ideal scenario, in which the communication conditions of all the stations are the same. However, we propose a model that can adapt to scenarios in which the communication conditions of each station are different. The performance of CSMA/CA enhanced with our algorithm is extensively investigated in simulations performed under multiple scenarios. The obtained results indicate that our model can simultaneously achieve good communication performance and fairness.

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Rate adaptation algorithms for IEEE 802.11 networks: A survey and comparison

Cited by 79 publications

References 13 publications

Improvement of Throughput Prediction Scheme Considering Terminal Distribution in Multi-Rate WLAN Considering Both CSMA/CA and Frame Collision

Improvement of Throughput Prediction Scheme Considering Terminal Distribution in Multi-Rate WLAN Considering Both CSMA/CA and Frame Collision

Link adaptation for BICM-OFDM through adaptive kernel regression

Multiple access in MAC layer based on surrounding conditions of wireless stations

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