A Novel Nonlinear Precoding Algorithm for the Downlink of Multiple Antenna Multi-User Systems
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Bibliographic record
Abstract
By pre-equalizing inter-layer interference at the transmitter, Tomlinson-Harashima precoding (THP) algorithm provides a solution for the downlink of multiple antenna multi-user systems, in which the decentralized structure of the receivers makes the receiver-processing algorithms impossible. However, for the zero-forcing (ZF) THP algorithm developed in the literature there are significant performance differences between specific mobile stations. In this paper, a novel version of the THP algorithm is proposed. It greatly improves the worst mobile's performance and ensures balanced performance of all the mobiles. For the new THP algorithm, better performance can be obtained by suitably ordering the rows of the channel matrix. We show that the "best-first" ordering method achieves optimal order for BER performance in 2/spl times/2 systems and achieves near optimal order in systems of larger dimensions. Simulation is used to show the advantages of the new THP algorithm and the "best-first" ordering method.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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