Modeling Multi-User WLANs Under Closed-Loop Traffic

Nayak, Peshal; Garetto, Michele; Knightly, Edward W.

doi:10.1109/tnet.2019.2899777

Cited by 5 publications

(3 citation statements)

References 21 publications

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“…However, unlike active probing, this methodology does not increase the trac load as it leverages layer-4 handshakes that would anyways occur due to TCP. Further, since uScope leverages the fundamental closed loop property of TCP (which still carries more than 80% of the internet trac today [4][5][6][7][8]) the handshakes can be a part of any TCP ow in which the target STA receives data (e.g., a Netix video stream).…”

Section: Uscope Framework 31 Tcp Handshake As a Virtual Probementioning

confidence: 99%

uScope

Nayak

Knightly

2021

Proceedings of the Twenty-Second International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Net

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This paper presents uScope, an AP-side framework for validation of delay-based SLAs. Specically, uScope enables in the estimation of WLAN uplink latency for any of the associated STAs and decomposition into its constituent components. uScope does not require any form of active probing, no special purpose software installations on the STAs, nor any additional infrastructure to collect more information, and makes estimations solely based on passive AP-side observations. We implement uScope on a commodity hardware platform and conduct extensive eld trials on a university campus and in a residential apartment complex. In over 1 million tests, uScope demonstrates a high estimation accuracy with mean estimation errors under 10% for all the estimated parameters.

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Section: Uscope Framework 31 Tcp Handshake As a Virtual Probementioning

confidence: 99%

uScope

Nayak

Knightly

2021

Proceedings of the Twenty-Second International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Net

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“…• MU-MIMO performance evaluation under traffic dynamics: Several works on performance evaluation of multi-user transmission have appeared in literature recently. Works such as [7][8][9][10][11] model and evaluate the performance of MU-MIMO under the impact of closed loop dynamics. This is orthogonal to our focus which is on open loop traffic dynamics.…”

Section: Related Workmentioning

confidence: 99%

Performance Evaluation of MU-MIMO Under the Impact of Open Loop Traffic Dynamics

Nayak

2021

Preprint

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Multi-user MIMO enhances throughput by simultaneously transmitting/receiving parallel data streams to/from a group of users. However, the throughput analysis does not account for variable data traffic. The research objective of this project is to analyze the effect of variable traffic as it will change the system behaviour. The two characteristic features of variable traffic viz. packet size variation and traffic burstiness have been considered for the analysis in this project. Their effects have been studied individually to provide an insight into the problem. Through simulations, we show that in certain scenarios the system performance of MU-MIMO deteriorates significantly due to both packet size variations and traffic burstiness individually even under ideal conditions with respect to channel variations, channel correlation, mobility, etc. Furthermore, we show that under bursty traffic with higher offered load the aggregate throughput first remains steady until a certain peak to average rate ratio and then deteriorates linearly instead of exponentially. Also, under high amount of traffic burstiness, the throughputs are independent of the aggregation rates. A thorough analysis is provided to explain these two phenomena. This is the first research work that considers the impact of variable traffic on the performance of MU-MIMO. Therefore, the implications for MAC protocol design are significant.

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“…We have drawn attention to a few examples, but several other authors have also based their analysis of WiFi performance on the method first demonstrated by Bianchi [15]- [17]. These papers all report steady-state results and measure performance as aggregate throughput.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Quality Attenuation of WiFi

Teigen

Davies²,

Ellefsen

et al. 2022

2022 IEEE 47th Conference on Local Computer Networks (LCN)

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WiFi is one of the most widely deployed networking technologies, and understanding WiFi performance is therefore of great importance. The WiFi MAC layer sometimes introduces significant and variable delays. No existing models of the WiFi protocol describe WiFi performance in terms of complete latency distributions. In this work, we present a novel model of WiFi performance. We explicitly define our model in terms of the latency introduced at each step in the protocol state machine, and the model produces complete latency distributions. We validate the model by comparing its outputs to previous modeling work and real-world measurements. Finally, we use our results to quantify the latency distribution of WiFi as a function of the duration of transmit opportunities and the number of stations competing for the channel. Quantifying this relation represents a significant improvement in our understanding of WiFi performance that would not be possible with existing models.

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Modeling Multi-User WLANs Under Closed-Loop Traffic

Cited by 5 publications

References 21 publications

uScope

uScope

Performance Evaluation of MU-MIMO Under the Impact of Open Loop Traffic Dynamics

Quantifying the Quality Attenuation of WiFi

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