Whitespace evaluation software (WEST) and its applications to whitespace in Canada and Australia
Notice bibliographique
Résumé
Spectrum whitespaces and dynamic spectrum sharing have become important and interesting topics in recent years. The USA authorized the use of TV whitespaces in 2008 and the UK and Canada followed suit in early 2015. In light of the PCAST report of 2012, additional bands are being evaluated for spectrum sharing in the USA and abroad. With the increasing momentum of spectrum whitespaces, it is more important than ever to understand the consequences of regulatory decisions. For example, what is the effect of increasing the separation distance from 10km to 15km? Regulators need the ability to understand tradeoffs like this so that they can make informed decisions based on actual, not hypothetical or supposed, impact. Despite the clear need, data-driven analyses appear to be quite rare among regulators, industry members, and researchers alike. Although the data is often freely available, employing it can be an onerous task. In order to reduce this barrier, we have created an open-source software package, WEST, that quickly allows a user to estimate the amount of whitespace in a given region. For example, after collecting the requisite data, we produced estimates of the amount of whitespace in Canada in under an hour. To demonstrate the power of our software, we present novel results on whitespace availability in Canada and Australia. However, the true potential of WEST lies in the ability to configure it to use existing or hypothetical rulesets. We thus use WEST to compare the FCC and Industry Canada (IC) rulesets, showing that each citizen loses approximately one whitespace channel, mainly due to the increased size of IC's separation distances as compared to the FCC's. We also showed that although the effect of taboo channel exclusions (a notion introduced in the IC ruleset) is small in Canada, it would be much larger if applied to the USA. The identification of the real-world effects of these regulatory decisions was made possible by WEST's ability to create “chimera rulesets,” i.e. mosaics of the IC and FCC rules, so that we could examine each variable in isolation. Finally, we describe the high-level design of WEST. The modular design makes it easy for users to combine, replace, modify, or remove various components to achieve the desired effect. We sincerely hope that the community will use and contribute to WEST, turning it into an even more powerful tool than it is today. If real-world data were at your fingertips and easy to use, what would you do?
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».