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Record W2887675532 · doi:10.1109/tifs.2018.2859593

Wireless-Powered Full-Duplex Relay and Friendly Jamming for Secure Cooperative Communications

2018· article· en· W2887675532 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 Transactions on Information Forensics and Security · 2018
Typearticle
Languageen
FieldEngineering
TopicFull-Duplex Wireless Communications
Canadian institutionsUniversity of Alberta
FundersShahrekord University
KeywordsRelayJammingComputer scienceWirelessPhysical layerInterference (communication)SecrecyChannel state informationChannel (broadcasting)Energy (signal processing)Signal-to-noise ratio (imaging)Duplex (building)Computer networkTelecommunicationsMathematicsComputer securityPhysicsStatisticsBiologyGenetics

Abstract

fetched live from OpenAlex

Wireless energy harvesting, physical-layer security, and full-duplex wireless are important, emerging fifth generation (5G) technologies. In this paper, we thus investigate a source-destination link with an energy-harvesting full-duplex relay and a jammer (to degrade the eavesdropper channel) in the presence of an eavesdropper. Thus, to exploit energy harvesting and to improve security, we propose a full-duplex jammer (FDJ) protocol and its half-duplex version (HDJ). Two cases for availability of the eavesdropper channel state information (ECSI) are considered: complete ECSI and incomplete ECSI. For both FDJ and HDJ protocols and for complete ECSI, we derive the instantaneous and average secrecy rates and compute optimal time split for energy harvesting. To gain more insights, we consider a practical interference-limited scenario and derive closed-form cumulative distribution function of the signal-to-interference plus noise ratio at the destination and eavesdropper nodes. Comparatively, we show that FDJ improves instantaneous secrecy rate over HDJ. However, the degree of improvement is highly dependent on time split for energy harvesting, amount of self-interference, the channel gains, and locations of the nodes. Our findings reveal that FDJ increases the average secrecy rate 150% over HDJ and 260% over HD relaying without jammer. For incomplete ECSI scenario, we derive asymptotic secrecy outage and show that FDJ performs better for small-to-medium values of source powers; otherwise, HDJ yields a higher gain.

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 categoriesMeta-epidemiology (narrow)
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 score0.674
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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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