The effect of unlicensed cognitive device operation on digital television performance in the VHF/UHF band
Bibliographic record
Abstract
This paper analyzes the effects of recent development in Over-The-Air (OTA) Television Broadcasting that will allow for new full duplex digital services to be offered in the band. On February 17, 2009, the analog terrestrial television system will have fully transitioned to digital in the United States ending an era of analog TV broadcasting; Canada is to follow in August 2011. At that stage, broadcast RF spectrum will be only occupied by Digital Television (DTV) services making possible the co-existence of other (non-broadcast) digital services resulting from the improved spectrum efficiency offered by digital technology. This recent development allows for new digital services to be offered mainly to rural and remote areas where broadband Internet Multimedia Services (IMS), available in the urban and sub-urban areas are unlikely to be delivered by standard means. In an effort to improve even more the efficient use of the spectrum, the FCC issued a Notice of Proposed Rule Making (NPRM) for the development of a Cognitive Radio (CR) type Unlicensed Device (UD) that would be deployed in the television band. These UDs would operate in the vacant DTV spectrum, known as “white space”, thus fostering broadband access and IMS service delivery to end users. Concerns, however, have been raised by DTV broadcasters on the impact that these devices could have on DTV reception. To that end, studies were performed at CRC to quantify the level of interference generated by the Unlicensed Devices and their effect on DTV operations. The results from these studies will be presented in this paper and show that it is imperative that the UDs cognitive radio be able to detect and avoid channels being used by incumbents i.e., DTV and Cordless Microphones (CM). These cognitive radios will have to strictly abide by a set of rules such that harmful interference to the incumbents is avoided.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".