Channel Estimation for RIS-Assisted Multiuser mmWave Systems With Direct Channels Based on a Novel Space Projection Approach
Bibliographic record
Abstract
In this letter, we develop a novel two-stage joint direct and cascaded channel estimation strategy for reconfigurable intelligent surface (RIS)-assisted multi-user multiple-input single-output (MU-MISO) millimeter wave (mmWave) systems based on a novel space projection approach. Specifically, in Stage I, to obtain an equivalent signal for direct channel estimation, we carefully design the phase shifts of the RIS without switching off the RIS. In Stage II, the equivalent signal matrices for estimating the cascaded channels are obtained by employing the orthogonal complement space of the transmitted pilot sequence, which mitigates the component of the direct channels and thus completely prevents error propagation from the direct channels to the cascaded channels. Based on the proposed novel signal pre-processing method, the MU-MISO mmWave channels can be estimated by exploiting the sparsity and correlation. Comprehensive simulation results verify that the proposed method can improve the estimation accuracy and decrease pilot overhead.
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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 | 0.000 |
| 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".