Uncompressed HD and Ultra-HD Video Streaming Using Terahertz Wireless Communications
Bibliographic record
Abstract
Taming the Terahertz waves (100 GHz-10 THz) is considered the next frontier in wireless communications. While components for the ultra-high bandwidth Terahertz wireless communications were in rapid development over the past several years, however, their commercial availability is still lacking. Nevertheless, as we demonstrate in this work, due to recent advances in the microwave and infrared photonics hardware, it is now possible to assemble high performance hybrid THz communication systems for real-life applications. We present design and performance evaluation of the photonics-based Terahertz wireless communication system for the transmission of uncompressed 4K video feed that is built using all commercially available system components. The Terahertz carrier frequency is fixed at 138 GHz and the system is characterized by measuring the bit error rate for the pseudo random bit sequences at 5.5 Gbps. By optimizing the link geometry and decision parameters, an error-free (BER-10) transmission at a link distance of 1m is achieved. Finally, we detail integration of a professional 4K camera into the THz communication link and demonstrate live streaming of the uncompressed HD and 4K video followed by analysis of the link quality.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".