Joint domain localized adaptive processing with zero forcing for multi-cell CDMA systems
Bibliographic record
Abstract
An integrated beamforming (spatial processing) and multiuser detection (temporal processing) scheme is an effective approach to increase system capacity, but is also impractical due to the high associated computational costs. The authors previously proposed joint domain localized (JDL) processing which achieves significantly lower computational cost and a faster convergence rate in terms of number of training symbols. The paper justifies the choice of the transformation matrix that is the basis for the JDL algorithm. Building on JDL processing, we also introduce a new processor that combines JDL processing and zero forcing for multi-cell uplink CDMA systems. Simulations show that this approach achieves better performance and a faster convergence rate than the JDL algorithm as well as the reduced rank and iterative schemes introduced by other researchers. If restricted by short training sequences, it even outperforms the theoretically optimal processor.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".