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Record W2524190195 · doi:10.1109/jsyst.2015.2464238

Spectral–Energy Efficiency Tradeoff in Full-Duplex Two-Way Relay Networks

2015· article· en· W2524190195 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 Systems Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicFull-Duplex Wireless Communications
Canadian institutionsUniversity of Manitoba
FundersGuilin University of Electronic TechnologyNatural Science Foundation of Guangxi ProvinceNational Natural Science Foundation of China
KeywordsRelaySpectral efficiencyTransmission (telecommunications)Computer scienceResidualMathematical optimizationOptimization problemIterative methodEfficient energy usePower (physics)Interference (communication)Power optimizationElectronic engineeringMathematicsComputer networkAlgorithmTelecommunicationsEngineeringElectrical engineeringBeamformingPower consumption

Abstract

fetched live from OpenAlex

Owing to its high spectral efficiency (SE), two-way relaying (TWR) has aroused tremendous research interests. Recently, substantial progress in self-interference (SI) cancelation makes full-duplex (FD) TWR practical. For this new paradigm, analyzing spectral-energy efficiency (SE-EE) tradeoff is crucial, which has not been addressed in the existing works in the literature. In this paper, the SE-EE tradeoff in a FDTW relay network with amplify-and-forward (AF) relaying is studied by considering the residual SI at the relay. An optimization problem is formulated to maximize the EE under the SE requirement and the maximum transmission power constraints by adjusting the transmission power of the terminals and the amplification gain of the relay. A lower complexity iterative optimization algorithm is developed to solve the optimization problem. Simulation results show that: 1) the proposed algorithm can achieve optimal EE that is consistent to the one obtained by the exclusive searching method; 2) the FDTW relay network can achieve higher SE but lower optimal EE compared with the half-duplex (HD) one; and 3) the optimal EE is insensitive to the residual power of SI, when the relay is located near either terminal.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.025
GPT teacher head0.236
Teacher spread0.211 · 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