Joint Impact of Phase Error, Transceiver Hardware Impairments, and Mobile Interferers on RIS-Aided Wireless System Over <i>κ</i>-<i>μ</i> Fading Channels
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Bibliographic record
Abstract
Reconfigurable intelligent surface (RIS) has recently emerged as a promising technology that can potentially benefit the existing wireless communication technologies in addition to being able to fulfill the more stringent requirements of beyond- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5^{th}$ </tex-math></inline-formula> generation/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$6^{th}$ </tex-math></inline-formula> generation wireless networks. Motivated by the numerous benefits of RIS technology for improving the performance of wireless communication systems, in this letter, a RIS-aided wireless system is considered in which the destination node is surrounded by the mobile co-channel interferers (CCIs). Each mobile CCI follows the random waypoint (RWP) mobility pattern within a circular region centered around the destination node. Source-destination, source-RIS, RIS-destination, and each interferer-destination links follow the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\kappa - \mu $ </tex-math></inline-formula> distribution. Additionally, a more realistic system model is considered that also incorporates the impact of transceiver (transmitter as well as receiver) hardware distortions. The system’s performance is evaluated by deriving novel closed-form expressions for the coverage probability (CP) and ergodic capacity (EC) based on the cumulative distribution function and probability density function (PDF) of the received signal-to-interference-plus-distortion-plus-noise ratio (SIDNR).
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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 | 0.002 | 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 it