In-Flight Performance Analysis of a Wideband Radio Using SDR for Avionic Applications
Bibliographic record
Abstract
Along with the increase in the number of passengers, aviation industry also needs to be adapted to the increasing demands of new services and applications. As one of the leading features of the Industry 4.0 era, maintaining a constant and high quality internet connectivity in-flight (also known as the In-Flight Entertainment Connectivity, IFEC) is one of the most demanded services. Among the explored solutions, the Wideband Radio (WBR), first presented in 2017 as a module in the Multi-Mode Software Defined Avionic Radio (MM-SDAR), is the avionic module that addresses the ever-increasing demand for the IFEC application. Based on the Adaptive Coding and Modulation (ACM) scheme, this Software Defined Avionic Module (SDAM) promises to deliver an optimum data rate regarding the real-time condition of the transmission channels. Moreover, as an SDR-based module, it is reconfigurable and could be implemented in an IMA-compatible (Integrated Modular Avionics) fashion in the future RF avionic architecture. In order to evaluate the operation of this WBR module in real flight conditions, it was flight tested in 2017, and positive results were obtained. This paper aims to provide an analysis of the in-flight performance (with Bit Error Rate - BER mode and video streaming mode) of the WBR, and concentrates on demonstrating the capacity and the operation of the ACM mechanism in a complex environment. With a transmission power of 10 W and a bandwidth of 675 kHz, the maximum slant range of the WBR during these flights reached 5 NM, and the ACM mechanism helped the system maintain an average throughput of around 360 kbit/s.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".