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Relay Selection and Resource Allocation for Multi-User Cooperative OFDMA Networks

2013· article· en· W2153016179 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

VenueIEEE Transactions on Wireless Communications · 2013
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceRelaySubcarrierResource allocationSubgradient methodOrthogonal frequency-division multiple accessQuality of serviceThroughputFrequency-division multiple accessComputer networkTelecommunications linkMathematical optimizationOptimization problemOrthogonal frequency-division multiplexingPower (physics)WirelessTelecommunicationsAlgorithmMathematicsChannel (broadcasting)

Abstract

fetched live from OpenAlex

The resource allocation problem is investigated for relay-based multi-user cooperative Orthogonal Frequency Division Multiple Access (OFDMA) uplink system, considering heterogeneous services. A quality of service (QoS) aware optimal relay selection, power allocation and subcarrier assignment scheme under a total power constraint is proposed. The relay selection, power allocation and subcarrier assignment problem is formulated as a joint optimization problem with the objective of maximizing the system throughput, which is solved by means of a two level dual decomposition and subgradient method. To further reduce the computational cost, two low-complexity suboptimal schemes are also proposed. The performance of the proposed schemes is demonstrated through computer simulations based on LTE-A network. Numerical results show that the proposed schemes support heterogeneous services while guaranteeing each user's QoS requirements with slight total system throughput degradation.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.294
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