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Record W2775721062 · doi:10.1109/twc.2017.2777446

A Novel Self-Interference Cancellation Scheme for Channel-Unaware Differential Space-Time Two-Way Relay Networks

2017· article· en· W2775721062 on OpenAlexaff
Salime Bameri, Siamak Talebi, Ramy H. Gohary, Halim Yanıkömeroğlu

Bibliographic record

VenueIEEE Transactions on Wireless Communications · 2017
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsCarleton University
Fundersnot available
KeywordsRelayPairwise error probabilityUpper and lower boundsSingle antenna interference cancellationTopology (electrical circuits)Interference (communication)Channel state informationRelay channelComputer scienceMathematicsSignal-to-noise ratio (imaging)Diversity gainChannel (broadcasting)FadingTelecommunicationsWirelessPhysicsPower (physics)Mathematical analysis

Abstract

fetched live from OpenAlex

This paper considers channel-unaware two-way relay networks in which two single-antenna nodes exchange information via multiple non-regenerative relays, each with multiple antennas. A novel self-interference cancellation scheme for distributed differential space-time signalling is developed. Despite the absence of channel-state information, this scheme enables self-interference to be completely eliminated, thereby maximizing the signal-to-interference-plus-noise-ratio of the nodes. First, we obtain a lower bound on the pairwise error probability (PEP) under residual self-interference and we show that this bound approaches a non-zero constant at high signal-to-noise ratios (SNRs), indicating a zero diversity order and an asymptotic error floor. Second, we derive a necessary and sufficient condition for the proposed scheme to eliminate self-interference perfectly. Proper operation of this scheme requires the relays to have an even number of active antennas and for relays with odd number of active antennas, such a scheme does not exist. Third, we show that, when self-interference is cancelled perfectly, the error floor vanishes and an upper bound on the PEP approaches zero at high SNRs. In this case, it is shown that the diversity gain is equal to the number of relays and is independent of the number of antennas per relay. Finally, it is shown that the coding gain increases with increasing the number of antennas per relay and converges to a constant as the number of relay antennas becomes large.

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), Science and technology studies
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 score0.945
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
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0010.001
Open science0.0050.000
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 head0.051
GPT teacher head0.300
Teacher spread0.250 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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