System Modeling and Precoding Design for Multi-beam Dual-polarized Satellite MIMO System
Bibliographic record
Abstract
Background: As the multimedia service develops and the transmission rate in terrestrial communication systems increases rapidly, satellite communication needs to improve the transmission rate and throughput. Multiple Input Multiple Output (MIMO) techniques can increase the system capacity significantly by introducing the space dimension, as the system bandwidth remains the same. Therefore, utilization of MIMO for satellite communications to increase the capacity is an important research topic. So MIMO techniques for multibeam satellite communications are researched in the dissertation. Objective: The goal of this work is improving the capacity of the satellite system. Multi-beam and dual-polarized technologies are applied to a satellite system to improve the capacity further. Methods: In this paper, we first introduce a multi-beam dual-polarized satellite multi-put and multiout (MBDP-S-MIMO) system which combines the full frequency multiplexing and dual-polarization technologies. Then the system model and channel model are first constructed. At last, to improve the capacity further, BD and BD-ZF precoding algorithms are applied to MBDP-S-MIMO and their performance is verified by simulation. Results: Simulation results show the performance of the BD precoding algorithm gets better with the growth of the XPD at the receiver and is almost not affected by the growth of the channel polarization correlation coefficient. In addition, with the growth of the users’ speed, the performance becomes worse. Conclusion: The multi-beam dual-polarized satellite MIMO system has high capacity, and it has certain application prospects for satellite communication.
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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 | 0.001 | 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 | 0.000 | 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".