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RIS Enabled Multi-User SWIPT for URLLC

2022· article· en· W4312378239 on OpenAlexaff
Anirban Bhowal, Sonia Aı̈ssa, Mohsen Naseri

Bibliographic record

Venue2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Technologies
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsComputer scienceMaximum power transfer theoremNetwork packetData transmissionWirelessInformation transferChannel (broadcasting)Transmission (telecommunications)Block (permutation group theory)Real-time computingLatency (audio)Computer networkPower (physics)Telecommunications

Abstract

fetched live from OpenAlex

We consider an ultra-reliable low-latency system in which a reconfigurable intelligent surface (RIS) is deployed to assist the simultaneous wireless information and power transfer between the access point and multiple devices. The data transmission, in the form of short packets, is performed using the rate splitting mechanism with chase-combining hybrid automatic repeat request error control. Using a realistic channel model and considering operation in the presence of hardware impairments at the RIS and the devices, the system performance is investigated in two folds. First, the average block error rate and the outage probability in the information transfer are evaluated. Then, the battery recharging time in the power transfer and its statistics are determined. Numerical results are provided to illustrate the system performance and quantify the impacts of key parameters including the packet size, the maximum number of packet retransmissions, and the RIS size.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
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
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.018
GPT teacher head0.275
Teacher spread0.257 · 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.

Study designNot applicable
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

Citations4
Published2022
Admission routes1
Has abstractyes

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