Signal Space Diversity-Based Distributed RIS-Aided Dual-Hop Mixed RF-FSO Systems
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.
Bibliographic record
Abstract
Reconfigurable intelligent surface (RIS) is a recently emerged promising technology for beyond-5G (B5G)/6G wireless networks. In this letter, we propose to employ a signal space diversity (SSD) technique to improve the performance of distributed RIS-aided dual-hop mixed radio frequency (RF)-free-space optical (FSO) communication systems. The source-relay, source-RIS, and RIS-relay links are assumed to undergo independent but not identically distributed (i.n.i.d.) Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> fading. The destination node is equipped with multiple FSO apertures and the relay-destination links follow Gamma-Gamma (GG) distributed atmospheric turbulence (AT) model with pointing errors (PEs). Novel approximate closed-form expressions for the system’s symbol error rate (SER) are derived for both the exhaustive RIS-aided (ERA) and opportunistic RIS-aided (ORA) configurations. The numerical results show that using the SSD technique at both the RF and FSO links significantly improves the spectral efficiency and the diversity order of the system considered.
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 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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| 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 it