Misalignment-Robust Codebook-Based Beamforming for OAM Mode Multiplexing Systems
Bibliographic record
Abstract
In this paper, we present an algorithm to construct a misalignment-robust beamforming (BF) codebook for orbital angular momentum mode multiplexing (OAM-MM) systems. The BF codebook is constructed for a given set of antenna misalignment (AM) parameters, i.e., the AM type, rotation angles, and displacement values. We use the sorted QR-decomposition of the augmented misaligned channel matrix to design a BF codebook that is applied to received signals using phase shifters only. Subsequently, by employing the successive interference cancellation (SIC), the transmitted symbols corresponding to each OAM mode are estimated. The combination of codebook-based BF in the analog domain and the SIC in the digital domain offers an effective strategy to solve the AM problem without sacrificing the computational savings associated with the application of OAM-MM. Simulation results confirm that by adopting the proposed approach, the sum-rate of the misaligned OAM-MM system approaches the theoretical upper bound.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".