A Network Performance Study of LTE in Unlicensed Spectrum

Hillery, W.J.; Mangalvedhe, Nitin; Bartlett, R. J.; Huang, Zhubo; Kovács, István Z.

doi:10.1109/glocomw.2015.7414108

Cited by 6 publications

(10 citation statements)

References 7 publications

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“…In our work, we rather study details regarding frame collisions, IEEE 802.11 MAC protocol and all duty cycle parameters. In [5], TDM-based LTE-U has been examined to coexist with Wi-Fi through simulations. Authors claimed that "LTE-U can be configured to be fair to Wi-Fi" without providing any further information about how to achieve it.…”

Section: Related Workmentioning

confidence: 99%

“…Besides, they did not model the possible collisions between the two systems. Unlike [5] that approximates the Duty Cycled LTE-U scheme because of their proprietary simulator limitation, we integrate an exact Duty Cycled LTE-U in the well-known NS3 simulator. The probability of channel access for Wi-Fi stations is computed in [6] in presence of Duty Cycled LTE-U.…”

Section: Related Workmentioning

confidence: 99%

“…Our simulation results show that both approximations are acceptable. Solving (14) (or (15)), (5) and (1) yields τ . To calculate the throughput in (12), we determine…”

Section: Fig 2: Duty Cycled Lte (Lte-u)mentioning

confidence: 99%

“…Up to this point of the analysis, equations (23), (5) and (1) represent our new fixed point formulation. Now, we compute differently the throughput based on counting the number of successful Wi-Fi frames during off-periods unlike (12).…”

Section: Fig 4: Frame-by-frame Random Walk Model For Wi-fimentioning

confidence: 99%

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Modeling and performance analysis of Wi-Fi networks coexisting with LTE-U

Abdelfattah

Malouch

2017

IEEE INFOCOM 2017 - IEEE Conference on Computer Communications

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In order to cope with the exponential growth of mobile traffic, mobile operators need to access more spectrum resources. LTE in unlicensed spectrum (LTE-U) has been proposed to extend the usual operation of LTE in licensed spectrum to cover also unlicensed spectrum. However, this extension poses significant challenges especially regarding the coexistence between LTE-U and legacy systems like Wi-Fi. In case of LTE-U adopts Time-Division Multiplexing (TDM) schemes to share the spectrum with Wi-Fi, we expect performance degradations of Wi-Fi networks. In this paper, we quantify the impact of TDM schemes on Wi-Fi performance in a coexistence scenario. We provide detailed analytical models using two different random walk approaches to compute the probability of collision faced by Wi-Fi stations and their throughput performance. Besides, we derive the performance results using an exponential approximation which shows its insufficiency to capture the exact behavior. We implement the coexistence in the NS3 simulator and we show that the models estimate accurately the collision probability and the throughput experienced by Wi-Fi. The models are then used to study and compare different coexistence schemes showing for instance that the Wi-Fi frame size has a non-negligible impact on the performance of Wi-Fi users.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

“…Our simulation results show that both approximations are acceptable. Solving (14) (or (15)), (5) and (1) yields τ . To calculate the throughput in (12), we determine…”

Section: Fig 2: Duty Cycled Lte (Lte-u)mentioning

confidence: 99%

Section: Fig 4: Frame-by-frame Random Walk Model For Wi-fimentioning

confidence: 99%

See 2 more Smart Citations

Modeling and performance analysis of Wi-Fi networks coexisting with LTE-U

Abdelfattah

Malouch

2017

IEEE INFOCOM 2017 - IEEE Conference on Computer Communications

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“…However, due to the presence of several spectrum holes smaller than 6 MHz (but larger than 5 MHz), spectrum holes of 5 MHz are also considered in this work, and so = 5 MHz. Contrary to IEEE 802.22 that does not consider spectrum holes smaller than 6 MHz, there are other wireless standards such as unlicensed LTE where this kind of empty spaces can be used [23,24]. The four spectrum holes considered are the elements of the set = { 1 = 5, 2 = 6, 3 = 7, 4 = 8}.…”

Section: Duty Cycle (Dc )mentioning

confidence: 99%

Reducing Spectrum Handoffs and Energy Switching Consumption of MADM-Based Decisions in Cognitive Radio Networks

Aguilar-Gonzalez

Cardenas-Juarez

Pineda-Rico

et al. 2016

Mobile Information Systems

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In a cognitive radio network (CRN), the number of spectrum handoffs increases energy consumption of cognitive (or secondary) users due to the channel switching process. This might limit the operation of the CRN, especially in scenarios where secondary users terminals are battery-powered. Thus, reducing the number of times a cognitive user involved in a transmission switch to different spectrum holes is required to increase battery life-time. In this regard, available spectrum holes possess different attributes (e.g., bandwidth) that can be exploited to satisfy specific secondary users requirements (i.e., connection profile) for data transmission while saving energy. Here, three multiple attribute decision-making (MADM) algorithms for the spectrum decision functionality are evaluated using real spectrum measurements of TV bands. This is performed by proposing six decision parameters, which are extracted from the spectrum data to characterize its suitability. Then, these are used as inputs of the MADM algorithms to select the most suitable spectrum hole for a cognitive user. Thus, an enhanced MADM-based decision process is proposed to reduce the number of handoffs considering energy consumption due to channel switching (ECCS). Results quantify savings from 30% to 90% in ECCS and spectrum handoffs reductions from 47% to 90%.

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Spectrum Decision Mechanisms in Cognitive Radio Networks

Aguilar-Gonzalez

Ramos

2018

Emerging Wireless Communication and Network Technologies

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A Network Performance Study of LTE in Unlicensed Spectrum

Cited by 6 publications

References 7 publications

Modeling and performance analysis of Wi-Fi networks coexisting with LTE-U

Modeling and performance analysis of Wi-Fi networks coexisting with LTE-U

Reducing Spectrum Handoffs and Energy Switching Consumption of MADM-Based Decisions in Cognitive Radio Networks

Spectrum Decision Mechanisms in Cognitive Radio Networks

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