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Dynamic Preamble Subset Allocation for RAN Slicing in 5G Networks

Overview of attention for article published in IEEE Access, March 2018
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

patent
5 patents

Readers on

mendeley
30 Mendeley
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Article details
Title
Dynamic Preamble Subset Allocation for RAN Slicing in 5G Networks
Published in
IEEE Access, March 2018
DOI 10.1109/access.2018.2800661
Authors

Serdar Vural, Ning Wang, Paul Bucknell, Gerard Foster, Rahim Tafazolli, Julien Muller

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Timeline Attention over time Attention Score history
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Activity
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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 6 20%
Student > Master 4 13%
Other 2 7%
Lecturer 2 7%
Researcher 2 7%
Other 3 10%
Unknown 11 37%
Readers by discipline
Readers by discipline Count As %
Engineering 10 33%
Computer Science 7 23%
Unknown 13 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 August 2026.
All research outputs
#6,148,001
of 28,059,601 outputs
Outputs from IEEE Access
#1,602
of 12,283 outputs
Outputs of similar age
#100,211
of 353,128 outputs
Outputs of similar age from IEEE Access
#47
of 281 outputs
Altmetric has tracked 28,059,601 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 12,283 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 79% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 353,128 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 281 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.