Rapid Prototyping Hardware Platforms for the Development and Testing of OFDM Based Communication 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
Implementation of modern digital transceivers requires an expertise in numerous fields. Conventional transceiver design methods are no longer sufficient to guarantee a fast conversion from initial concept to final product. Moreover, in the testing phase, system simulations alone cannot provide the full insight into the system parameters and performance, especially at the RF stages, where the modeling of power amplifier non-linearities is a highly complex task. To address these design gaps, this paper utilizes software radio solutions. Specifically, it elaborates on transceiver architectural methods at the baseband involving hardware/software partitioning, as well as automatic digital signal processing (DSP) coding strategies that allow for rapid prototyping, testing and verification of algorithms developed in the design simulation stages. In particular, DSP processor and field programmable gate array (FPGA)-based testbeds are described that offer different advantages in the transceiver rapid prototyping methodology. These testbeds were designed to eventually be used in experiments geared towards demonstrating the effectiveness of compensation algorithms for wireless systems like wireless local area network (WLAN) and digital audio broadcasting (DAB), where orthogonal frequency division multiplexed (OFDM) signaling is deployed.
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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 | 0.001 | 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 | 0.001 | 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 it