Performance Comparison of Bluetooth LDI, Modified LDI, and NSD Receivers
Bibliographic record
Abstract
Two new Bluetooth receiver designs, the so-called modified limiter-discriminator detector with integrate and dump filtering (LDI) and noncoherent sequence detection (NSD), have recently been proposed in the literature. These receivers have been shown to improve the Bluetooth system performance in terms of physical-layer measures like bit-error rate (BER) and packet-error rate (PER) compared to the conventional LDI receiver. In this paper, we present a more comprehensive performance comparison for these receivers, which includes consideration of the spatial distribution of Bluetooth devices, channel propagation, data traffic, scheduling, automatic repeat request (ARQ), and baseband packet selection. The performance is measured in terms of practically relevant metrics such as end-to-end delay and throughput. Our numerical and simulation results verify that incorporating the new receivers into Bluetooth devices can considerably improve data-rate and quality-of-service performance compared to employing state-of-the-art LDI receivers.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".