Wireless-Powered Full-Duplex Relay and Friendly Jamming for Secure Cooperative Communications
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".