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Record W2219399812 · doi:10.1109/icc.2014.6884112

Multi-user scheduling schemes for simultaneous wireless information and power transfer

2014· article· en· W2219399812 on OpenAlexaff
Rania Morsi, Diomidis S. Michalopoulos, Robert Schober

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsScheduling (production processes)Computer scienceTelecommunications linkProportionally fairWirelessRound-robin schedulingFair-share schedulingAlgorithmReal-time computingMathematical optimizationComputer networkMathematicsTelecommunications

Abstract

fetched live from OpenAlex

In this paper, the downlink multi-user scheduling problem is studied for a time-slotted system with simultaneous wireless information and power transfer. In particular, in each time slot, a single user is scheduled to receive information, while the remaining users opportunistically harvest the ambient radio frequency (RF) energy. We devise novel scheduling schemes in which the tradeoff between the users' ergodic capacities and their average amount of harvested energy can be controlled. To this end, two fair scheduling schemes used in information-only transfer systems are modified. First, proportionally fair maximum normalized signal-to-noise ratio (N-SNR) scheduling is modified by scheduling the user having the j <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> ascendingly ordered (rather than the maximum) N-SNR. We refer to this scheme as order-based N-SNR scheduling. Second, conventional equal-throughput (ET) fair scheduling is modified by scheduling the user having the minimum moving average throughput among the set of users whose N-SNR orders fall into a certain set of allowed orders S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</sub> (rather than the set of all users). We refer to this scheme as order-based ET scheduling. The feasibility conditions required for the users to achieve ET with this scheme are also derived. It is shown that the smaller the selection order j for the order-based N-SNR scheme, and the lower the orders in S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</sub> for the order-based ET scheme, the higher the average amount of energy harvested by the users at the expense of a reduction in their ergodic capacities. The performance of the considered scheduling schemes is analyzed for independent and non-identically distributed (i.n.d.) Ricean fading channels, and closed-form results for the special case of i.n.d. Rayleigh fading are provided.

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.

How this classification was reachedexpand

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 score0.592
Threshold uncertainty score0.592

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 head0.006
GPT teacher head0.202
Teacher spread0.195 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2014
Admission routes1
Has abstractyes

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