Proceedings ArticleDOI
STRALE: Mobility-aware PHY rate and frame aggregation length adaptation in WLANs
Seongho Byeon,Yoon Kangjin,Changmok Yang,Sunghyun Choi +3 more
- pp 1-9
TLDR
STRALE, a standard-compliant and mobility-aware PHY rate and A-MPDU length adaptation scheme with ease of implementation, is developed and demonstrated that STRALE achieves up to 2.9x higher throughput, compared to a fixed duration setting according to IEEE 802.11 standard.Abstract:
IEEE 802.11n/ac wireless local area network (WLAN) supports frame aggregation, called aggregate medium access control (MAC) protocol data unit (A-MPDU), to enhance MAC efficiency by reducing protocol overhead. However, the current channel estimation process conducted only once during the preamble reception is known to be insufficient to ensure robust delivery of long A-MPDU frames in mobile environments. To cope with this problem, we first build a model which represents the impact of mobility with a noise vector in the I-Q plane, and then analyze how the mobility affects the A-MPDU reception performance. Based on our analysis, we develop STRALE, a standard-compliant and mobility-aware PHY rate and A-MPDU length adaptation scheme with ease of implementation. Through extensive simulations with 802.11ac using ns-3 and prototype implementation with commercial 802.11n devices, we demonstrate that STRALE achieves up to 2.9x higher throughput, compared to a fixed duration setting according to IEEE 802.11 standard.read more
Citations
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Journal ArticleDOI
Energy-Efficient Frame Aggregation Scheme in IoT Over Fiber-Wireless Networks
TL;DR: The proposed scheme adaptively adjusts the length of the aggregated frame to reduce the energy consumption caused by the frequent preemption of wireless channel and the numerous retransmission of data frames resulted by poor channel quality.
Journal ArticleDOI
MAC-layer rate control for 802.11 networks: a survey
TL;DR: This paper provides a comprehensive survey and analysis of the existing solutions from the two fundamental aspects of rate control—metrics and algorithms, and shows issues that need to be addressed in the design of new rate control mechanisms suitable for technologies and applications.
Proceedings ArticleDOI
NeuRA: Using Neural Networks to Improve WiFi Rate Adaptation
TL;DR: An offline algorithm that uses information about the fate of future frames to make statistically optimal frame aggregation and rate adaptation decisions is designed, called NeuRA, which provides an upper bound on the throughput that can be obtained by practical online algorithms and enables us to evaluate rate adaptation algorithms with respect to this upper bound.
Journal ArticleDOI
Evaluation of Rate Adaptation Algorithms in IEEE 802.11 Networks
Ibrahim Sammour,Gerard Chalhoub +1 more
TL;DR: This paper categorizes some of the popular rate adaptation schemes according to their design and functionalities in terms of the strategies that are used to estimate channel conditions and decision making, and implemented some algorithms from the different categories in the network simulator NS-3 in order to evaluate their performance.
Journal ArticleDOI
T-SIMn: A trace collection and simulation framework for 802.11n networks
TL;DR: The design, implementation and evaluation of a new framework for the trace-based evaluation of 802.11n networks, which is called T-SIMn, are described and the framework can be used to accurately simulate several scenarios and demonstrate the fidelity of SIMn by uncovering problems with the initial evaluation methodology.
References
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TL;DR: In this paper, the authors propose a multiuser communication architecture for point-to-point wireless networks with additive Gaussian noise detection and estimation in the context of MIMO networks.
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Proceedings ArticleDOI
Performance analysis of A-MPDU and A-MSDU aggregation in IEEE 802.11n
B. Ginzburg,A. Kesselman +1 more
TL;DR: A novel analytic model for estimating the performance of a 802.11n high throughput wireless link between a station and an Access Point (AP) is presented and it is shown that A-MPDU aggregation outperforms A-MSDU aggregation, whose performance considerably degrades for high packet error rates and high PHY rates.