Performance Evaluation of Bluetooth Systems With LDI, Modified LDI, and NSD Receivers
Why this work is in the frame
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Bibliographic record
Abstract
Bluetooth is a popular short-range low-power radio standard for wireless personal area networks. Bluetooth transmitters employ Gaussian frequency shift keying (GFSK) and simple block codes for error correction. Recently, two new receiver designs for Bluetooth devices, which are the so-called modified limiter-discriminator detector with integrate-and-dump filtering (LDI) and noncoherent sequence detection (NSD), have been proposed in the literature. While the modified LDI receiver is a concatenation of a conventional LDI detector with an improved error-correction decoder, the NSD receiver fully takes into account the memory introduced by the GFSK. Both receivers have been shown to improve the Bluetooth system performance in terms of physical-layer metrics such as bit-error rate and packet-error rate. In this paper, we present a comprehensive performance evaluation considering practically more relevant metrics such as throughput, delay, and delay jitter at the medium-access control layer. To this end, we develop an evaluation framework, which includes the spatial distribution of Bluetooth devices, path loss, fading, realistic data traffic models, scheduling, automatic repeat request, and baseband packet selection. Our numerical and simulation results verify that the newly introduced Bluetooth receivers, especially NSD, offer a significant performance enhancement for Bluetooth systems in terms of practically relevant measures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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