Analysis of Narrowband Communication Systems Impaired by MB-OFDM UWB Interference
Bibliographic record
Abstract
In this paper, we investigate the effect of multi-band orthogonal frequency division multiplexing (MB-OFDM) ultra-wideband (UWB) interference on narrowband (NB) receivers. For this purpose, we first derive the exact moment generating function of MB-OFDM UWB interference. Based on this result, we develop analytical expressions for the amplitude probability distribution (APD) and the bit error rate (BER) of a binary phase-shift keying NB receiver. These expressions can be efficiently numerically evaluated and the presented analysis is general enough to encompass non-fading and various fading NB channels. We show that for NB signals with, respectively, much smaller and much larger bandwidths than the MB-OFDM sub-carrier spacing a Gaussian approximation (GA) and an impulsive GA (IGA) of the MB-OFDM UWB interference lead to accurate performance predictions. However, for most NB channel models and signal bandwidths the exact BER analysis has to be used to obtain meaningful results. An exception is the Rayleigh fading NB channel where both GA and IGA yield tight approximations of the exact BER regardless of the NB signal bandwidth.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".