Performance of BICM-OFDM systems in UWB interference
Bibliographic record
Abstract
In this paper, we develop an analytical framework for performance analysis of generic bit-interleaved coded modulation orthogonal frequency-division multiplexing (BICMOFDM) systems impaired by ultra-wideband (UWB) interference. For practical relevance we consider multi-band OFDM (MB-OFDM), direct-sequence UWB (DS-UWB), and impulseradio UWB (IR-UWB) interference formats following recent IEEE/ECMA standards or standard proposals. Besides the exact analysis we calculate the bit error rate (BER) for the case when the UWB interference is modeled as additional Gaussian noise. Our results show that in general the BER of the BICM-OFDM system strongly depends on the UWB format and the OFDM sub-carrier spacing. While the Gaussian approximation is very accurate for DS-UWB, it may severely overor underestimate the true BER for MB-OFDM and IR-UWB interference. Our analysis is applicable to e.g. IEEE 802.11 wireless local area networks (WLANs), IEEE 802.16 wireless access systems (WiMAX), and 4th generation mobile communication systems. Furthermore, since the ECMA MB-OFDM standard is also based on the BICM-OFDM concept, our analysis can also be used to evaluate the impact of other UWB signals on ECMA MB-OFDM UWB systems.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".