Gram–Schmidt orthogonalisation aided hybrid precoding in millimetre‐wave massive MIMO systems
Bibliographic record
Abstract
The authors introduce a novel hybrid precoding algorithm based on Gram–Schmidt orthogonalisation (GSO) in millimetre‐wave massive MIMO systems. Specifically, the columns of array response matrix orthogonalised by the GSO process are considered as a set of candidate analogue precoders, then traditional orthogonal matching pursuit (OMP) is utilised to find the optimal analogue and digital precoders. Since GSO is a recursive process that depends on the order in which the matrix columns are selected. A heuristic solution to the order of columns selection is suggested according to the array response vector along which the fully‐digital precoder has the maximum projection. The proposed algorithm, not only constrained to uniform linear arrays, can avoid the matrix inversion in designing the digital precoder compared to OMP. Simulation results show that the spectral efficiency and bit error rate of the proposed hybrid precoding solutions are close to that obtained with fully digital architectures. Furthermore, the results indicate that the proposed hybrid precoding solutions outperform the orthogonality‐based matching pursuit, which uses the columns of the DFT matrix as a set of candidate analogue precoders.
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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".