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Record W2113876301 · doi:10.1109/icc.2006.254801

Novel Scheduling Algorithms for Multimedia Service in OFDM Broadband Wireless Systems

2006· article· en· W2113876301 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.

Bibliographic record

Venue2006 IEEE International Conference on Communications · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceLink adaptationWireless broadbandOrthogonal frequency-division multiplexingScheduling (production processes)AlgorithmWirelessSpectral efficiencyComputer networkWiMAXTime division multiple accessBroadband networksBroadbandWireless networkFadingChannel (broadcasting)Decoding methodsTelecommunicationsMathematical optimization

Abstract

fetched live from OpenAlex

Scheduling algorithms play a key role in overall system performance of broadband wireless systems (BWS) such as WLAN/WMAN. Maximal SNR (MaxSNR) and Round Robin (RR) are two conventional scheduling strategies which emphasize efficiency and fairness respectively. Proportional Fair (PF) algorithm provides tradeoff between efficiency and fairness and it has been well studied in TDMA and CDMA systems. In this paper, we apply the PF scheduling algorithm to IEEE 802.16a OFDM based BWS and call it OPF. In addition, we propose three algorithms for multimedia services: (1) Adaptive OPF (AOPF), (2) Multimedia AOPF (MAOPF) and (3) Normalized MAOPF (NMAOPF). Adaptive modulation and coding schemes are applied to combat the time varying nature of the wireless channels. System performances of all six algorithms are compared in terms of efficiency and fairness.. Joint PHY and MAC layer simulation results show that the proposed schemes provide better tradeoff between efficiency and fairness than conventional algorithms.

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: Methods · Consensus signal: none
Teacher disagreement score0.904
Threshold uncertainty score0.938

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 science0.0010.000
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 head0.069
GPT teacher head0.313
Teacher spread0.244 · 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