Enhancing Secrecy Capacity in Alternate AF Relaying Networks with Inter-Relay Interference
Bibliographic record
Abstract
This paper exploits the physical layer security and signal processing to support confidentiality in two-path amplify-and-forward (AF) relay networks. In these systems, successive relaying enhances the capacity of wireless networks through simultaneous spectrum utilization by a source and relays which in turn leads to inter-relay interference (IRI). In the proposed signaling schemes, by controlling the IRI through power adjustment unique to relay-destination channel state information (CSI), IRI and fading channels are turned into a source of secrecy in a broadcasting environment where signal overhearing is unavoidable. Specifically, the IRI is fully mitigated at the intended receiver, while at the eavesdropper, without requiring additional system resources, the IRI is increasing the noise level. Conventional signaling and superposition coding (SC) schemes are considered when analyzing the secrecy capacity of different systems. Furthermore, network coding (NC) is investigated to improve the secrecy capacity. The impact of intended receiver and eavesdropper positions is examined using stochastic geometry principles. Numerical analysis and simulations show that with a single data stream, even though noise enhancement degrades the intended receiver's signal-to-noise ratio (SNR) in zero-forcing IRI cancelation, successive relaying system using the proposed scheme achieves higher secrecy capacity in deterministic environments and ergodic secrecy capacity in fading environments compared to the conventional half-duplex relaying system. Furthermore, SC scheme shows great promise in terms of providing different levels of secrecy rates for different data streams represented by different power allocations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".