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Record W2075191765 · doi:10.1109/twc.2014.2337897

Multiuser Two-Way Relaying Schemes for UWB Communication

2014· article· en· W2075191765 on OpenAlexafffund
Zahra Ahmadian, Lutz Lampe, Jan Mietzner

Bibliographic record

VenueIEEE Transactions on Wireless Communications · 2014
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceRelayOptimization problemRakeMultipath propagationFadingInterference (communication)Rake receiverPairwise error probabilitySignal processingElectronic engineeringPower (physics)Computer networkAlgorithmTelecommunicationsDecoding methodsChannel (broadcasting)Engineering

Abstract

fetched live from OpenAlex

In this paper, we propose multiuser two-way relaying strategies for pairwise internode communication in a network consisting of ultrawideband transceivers with limited signal processing capability, via a central relay unit. We propose reducing the complexity associated with the design of filters at the relay by using pre/post-rake processing in conjunction with optimized filtering at the relay. Two relaying strategies relevant to multipath fading channels, namely, detect-and-forward and filter-and-forward with self-interference cancelation, are considered. For both methods, we start with a convex optimization problem formulation with closed-form solutions, then extend the design to the more general case, which is a nonconvex problem, and use an alternating optimization algorithm to solve the design problems. Furthermore, for both design schemes, widely linear design formulations are devised. The presented numerical results demonstrate the capability of the proposed design schemes in establishing a reliable communication link between nodes with limited signal processing power and in the absence of a direct link.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.905
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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0030.000
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 head0.021
GPT teacher head0.261
Teacher spread0.240 · 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
GenreMethods

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
Published2014
Admission routes2
Has abstractyes

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