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Record W2158382665 · doi:10.1109/wcnc.2010.5506295

Interference Cancellation at the Relay in Two User Wireless Relay Networks

2010· article· en· W2158382665 on OpenAlexaff
Liangbin Li, Yindi Jing, Hamid Jafarkhani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRelayComputer scienceSingle antenna interference cancellationTime division multiple accessComputer networkInterference (communication)Relay channelSymbol rateAntenna (radio)Electronic engineeringDecoding methodsTelecommunicationsBit error rateEngineeringChannel (broadcasting)Physics

Abstract

fetched live from OpenAlex

This paper is on interference cancellation (IC) schemes for a two-user relay network where users are allowed to communicate simultaneously. The considered networks have one double-antenna half-duplex relay, single-antenna receiver but three scenarios on both users: single-antenna, double-antenna, and four-antenna. We apply the IC scheme, which was originally proposed for multi-antenna multi-user direct communication systems, to multi-user relay networks and propose a protocol called IC-Relay-TDMA, in which the relay cancels user interference and then amplifies and forwards the interference-free (int-free) user information to the receiver in TDMA. The maximum likelihood (ML) decoding at the receiver can be conducted symbol by symbol for both networks with single-antenna users and double-antenna users. Compared to the full TDMA scheme in which each user is allocated different time slots from end to end to avoid interference, IC-Relay-TDMA achieves the same diversity with a higher symbol rate when both users have two or four antennas.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.934
Threshold uncertainty score0.990

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 communication0.0000.000
Open science0.0010.001
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 head0.023
GPT teacher head0.288
Teacher spread0.265 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2010
Admission routes1
Has abstractyes

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