Space-time-coded CDMA uplink transmission with MUI-free reception
Bibliographic record
Abstract
The problem of adopting space-time block coding (STBC) in the uplink of direct sequence code division multiple access (DS-CDMA) systems is addressed. A novel system architecture is proposed for space-time (ST)-coded uplink transmissions over multipath fading channels with multiple user interference (MUI)-free reception. This proposed system is a combination of single-carrier time-reversal zero-padding (SC-TR-ZP)-based STBC with chip-interleaved block-spread (CIBS)-CDMA. Simulation results show that a substantial performance improvement can be achieved by adopting ST coding compared to the original CIBS-CDMA scheme without ST coding. Optimal maximum likelihood sequence estimation (MLSE) may be computationally prohibitive for long channels and/or with high-level modulation. Hence, the performance of different decision feedback sequence estimation (DFSE) schemes is investigated for the proposed ST-coded uplink system. In the case of whitened DFSE (WDFSE), a linear prediction (LP)-based approach is adapted for designing a whitening prefilter. Furthermore, a new scheme, which is a combination of linear equalization (LE) and modified unwhitened DFSE (MUDFSE) is proposed. The proposed combined LE-MUDFSE (Comb. LE-MUDFSE) scheme is very attractive as error-floor behavior appearing in other unwhitened DFSE schemes is eliminated. The simulation results indicate that a substantial performance improvement over the minimum mean-square error (MMSE) equalizer can be achieved by using either Comb. LE-MUDFSE scheme or WDFSE scheme.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".