MétaCan
Menu
Back to cohort
Record W2098610567 · doi:10.1145/1454630.1454655

Downlink mixed-traffic scheduling with packet division multiplexing

2008· article· en· W2098610567 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceComputer networkQuality of serviceNetwork packetMultiplexingJitterScheduling (production processes)Statistical time division multiplexingTime-division multiplexingTelecommunications linkReal-time computingTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

With the tremendous growth in the wireless communications industry, wireless networks are envisioned to provide always-on, seamless and ubiquitous wireless data services with different Quality of Service (QoS) requirements to a large number of users using a mix of real-time and non-real-time multimedia traffic. In this paper, we propose an Adaptive Cross Layer (physical, MAC and application) Scheduling with Flow and User Multiplexing (ACLS-FUM) scheduling policy and quantify the considerable QoS performance gains in terms of user throughput, user latency, user packet drop probability and user jitter in a mixed traffic environment. Improvements from increased packing efficiency and time slot availability achieved with packet division multiplexing (PDM) (which permits the base station (BS) to service multiple users in the same physical encoder packet in a single time slot) are presented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.396
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.188
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations1
Published2008
Admission routes2
Has abstractyes

Explore more

Same topicAdvanced Wireless Network OptimizationFrench-language works237,207