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Record W2065588728 · doi:10.1109/glocom.2013.6831682

Self-interference pricing for Full-Duplex MIMO systems

2013· article· en· W2065588728 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFull-Duplex Wireless Communications
Canadian institutionsMcGill University
Fundersnot available
KeywordsInterference (communication)Computer scienceMIMOTransmitterSpectral efficiencyCo-channel interferenceAdjacent-channel interferenceWirelessChannel (broadcasting)TelecommunicationsElectronic engineeringZero-forcing precodingCommunications systemSIGNAL (programming language)Duplex (building)Multi-user MIMOEngineeringPrecoding

Abstract

fetched live from OpenAlex

Full-Duplex (FD) wireless communication systems have recently been proposed as a potential technique for increasing the spectral efficiency of wireless systems. FD communication systems suffer from the self-interference generated from one's own transmitter to one's own receiver in the same time and frequency slot. The self-interference signal is typically significantly larger than the received signal. The majority of existing work focuses on the suppression of self-interference without focusing on the effect on the forward channel. This paper presents a self-interference pricing based approach to suppress the self-interference without overly penalizing the forward channel. Simulation results show that even in the case of high self-interference, the proposed approach can provide significant data-rate improvements.

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)0.000
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: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.609

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 head0.017
GPT teacher head0.220
Teacher spread0.203 · 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

Quick stats

Citations14
Published2013
Admission routes1
Has abstractyes

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