Capture Effect in Ieee 802.11 Wireless Lans

Hadzi-Velkov, Zoran; Spasenovski, B.

doi:10.1142/9789812799562_0016

Cited by 12 publications

(11 citation statements)

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“…We apply two distinct capture models, denoted -1 and -2, which specify the likelihood that transferred data packets survive a collision with concurrently transferred packets [11,12,14,20]. The common assumption underlying both capture models is that in a collision of multiple packets, only the one with the strongest signal has a chance of successful capture.…”

Section: Capture Modelsmentioning

confidence: 99%

“…[2,22] both assume a constant number of persistently active sources and a simplified physical layer model. [11,12] consider a more realistic model of the physical layer. In particular, they study the impact of packet capture on the aggregate system throughput by two different capture models, which specify the likelihood that transferred data packets survive a collision with concurrently transferred packets.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Performance analysis of wireless LANs: an integrated packet/flow level approach

Litjens¹,

Roijers²,

Berg³

et al. 2003

Providing Quality of Service in Heterogeneous Environments, Proceedings of the 18th International Teletraffic Congress - ITC-18

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In this paper we present an integrated packet/flow level modelling approach for analysing flow throughputs and transfer times in 802.11 s. The packet level model captures the statistical characteristics of the transmission of individual packets at the layer, while the flow level model takes into account the system dynamics due to the initiation and completion of data flow transfers. The latter model is a processor sharing type of queueing model reflecting the 802.11 design principle of distributing the transmission capacity fairly among the active flows. The resulting integrated packet/flow level model is analytically tractable and yields a simple approximation for the throughput and flow transfer time. Extensive simulations show that the approximation is very accurate for a wide range of parameter settings. In addition, the simulation study confirms the attractive property following from our approximation that the expected flow transfer delay is insensitive to the flow size distribution (apart from its mean).

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Section: Capture Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance analysis of wireless LANs: an integrated packet/flow level approach

Litjens¹,

Roijers²,

Berg³

et al. 2003

Providing Quality of Service in Heterogeneous Environments, Proceedings of the 18th International Teletraffic Congress - ITC-18

View full text Add to dashboard Cite

show abstract

“…Moreover, Wi-Fi is limited in scalability and quality, and security issues still persist. In particular, IT managers are concerned about UL interference problems, poor range and unfair service quality, which is granted simply on the proximity of one UE to the access point (AP) compared to another, the so-called capture effect [11]. Looking more closely at Wi-Fi's limitations, several problems can be traced to the sharing mechanism between the UL and the DL, i.e.…”

Section: Introductionmentioning

confidence: 99%

LWIP and Wi-Fi Boost Flow Control

Liu

Ling

Kim

et al. 2017

2017 IEEE Wireless Communications and Networking Conference (WCNC)

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3GPP LWIP Release 13 technology and its prestandard version Wi-Fi Boost have recently emerged as an efficient LTE and Wi-Fi integration at the IP layer, allowing uplink on LTE and downlink on Wi-Fi. This solves all the contention problems of Wi-Fi and allows an optimum usage of the unlicensed band for downlink. In this paper, we present a new feature of Wi-Fi Boost, its radio link management, which allows to steer the downlink traffic between both LTE and Wi-Fi upon congestion detection in an intelligent manner. This customised congestion detection algorithm is based on IP probing, and can work with any Wi-Fi access point. Simulation results in a typical enterprise scenario show that LWIP R13 and Wi-Fi Boost can enhance network performance up to 5x and 6x over LTE-only, and 4x and 5x over Wi-Fi only networks, respectively, and that the the proposed radio link management can further improve Wi-Fi Boost performance over LWIP R13 up to 19 %. Based on the promising results, this paper suggests to enhance LWIP R13 user feedback in future LTE releases.

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“…Extensions to include physical layer details are given in e.g. [9], [16]. The extension to non-persistent sources is provided in [3], [14], where a flow level model is introduced that is analysed using a Processor Sharing queueing model.…”

Section: Introductionmentioning

confidence: 99%

Analysis of a Polling System Modeling QoS Differentiation in WLANs

Coenen

Berg

Boucherie

2008

Proceedings of the 3rd International Conference on Performance Evaluation Methodologies and Tools

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This paper investigates a polling system with a random polling scheme, a 1-limited service discipline and deterministic service requirement modeling WLANs with QoS differentation capability. The system contains high and low priority queues that are distinguished via the probability of being served next. We propose a new iteration algorithm to approximate the waiting time of customers in the high and low priority queues. As shown by simulation results, our approximation is accurate for light to moderately loaded networks.

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Capture Effect in Ieee 802.11 Wireless Lans

Cited by 12 publications

References 0 publications

Performance analysis of wireless LANs: an integrated packet/flow level approach

Performance analysis of wireless LANs: an integrated packet/flow level approach

LWIP and Wi-Fi Boost Flow Control

Analysis of a Polling System Modeling QoS Differentiation in WLANs

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