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Record W4402916062 · doi:10.1109/jiot.2024.3467371

Zero-Padding Space-Time Block Code for Dual-Antenna Backscatter Tag

2024· article· en· W4402916062 on OpenAlexaff
Chen He, Huixu Luan, Z. Jane Wang

Bibliographic record

VenueIEEE Internet of Things Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversity of British Columbia
FundersNatural Science Foundation of Shaanxi ProvinceNational Natural Science Foundation of China
KeywordsComputer sciencePaddingBlock (permutation group theory)Code (set theory)Antenna (radio)Backscatter (email)Space timeTelecommunicationsComputer securityMathematicsWireless

Abstract

fetched live from OpenAlex

Backscatter communications is receiving increasing attention in Internet of Things (IoT), while one major challenge for backscatter communications is that the circuit complexity for high performance tag is also high. In this article, for dual-antenna backscatter tag, we propose a zero-padding space-time block code (ZPSTBC) that can simultaneously improve the tag performance and reduce the complexity of the tag circuit. An interesting thing is that padding zero into space-time block code (STBC) is not beneficial in conventional multi-input-multi-output (MIMO) channels, but may lead to performance improvement in MIMO backscatter channels, from perspectives of error rate and energy harvesting, and also reduce the circuit complexity of the tag. This is due to characteristic of the MIMO structures and tag circuit of backscatter communications. We provide rigorous mathematical analysis and numerical simulations to illustrate the performance improvement and the tag complexity reduction caused by the proposed ZPSTBC.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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