Performance of BICM-OFDM systems in UWB interference
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
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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