EM-Based Adaptive Frequency Domain Estimation of Doppler Shifts with CRLB Analysis for CDMA Systems
Bibliographic record
Abstract
Combating time and frequency selectivity in wireless channels is one of the most challenging tasks in next generation wireless networks. In this paper, we propose an adaptive estimation algorithm to estimate Doppler shifts in a direct sequence code division multiple access (DS-CDMA) radio system with multiple Doppler subpaths. By modeling doubly selective channels using a basis expansion model (BEM), an expectation-maximization (EM) algorithm based adaptive estimation method is developed to extract accurate Doppler shift information. The Cramer-Rao lower bound (CRLB) analysis is conducted to study the performance bound of the proposed estimation algorithm. Based on the estimated Doppler shift results, a frequency domain equalizer (FDE) based receiver architecture is developed to exploit Doppler diversity in the frequency domain. Our analysis and simulation results demonstrate that this receiver architecture features a low complexity while still achieving a good performance compared with traditional CDMA receivers.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".