Rozproszone Wykrywanie Zajętości Widma Oparte na Uczeniu Federacyjnym
Fuente:
arXiv
Salvato in:
| Autori principali: | , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2024
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866909377929150464 |
|---|---|
| author | Kułacz, Łukasz Kliks, Adrian |
| author_facet | Kułacz, Łukasz Kliks, Adrian |
| contents | Spectrum occupancy detection is a key enabler for dynamic spectrum access, where machine learning algorithms are successfully utilized for detection improvement. However, the main challenge is limited access to labeled data about users transmission presence needed in supervised learning models. We present a distributed federated learning approach that addresses this challenge for sensors without access to learning data. The paper discusses the results of the conducted hardware experiment, where FL has been applied for DVB-T signal detection. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_03017 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Rozproszone Wykrywanie Zajętości Widma Oparte na Uczeniu Federacyjnym Kułacz, Łukasz Kliks, Adrian Networking and Internet Architecture Spectrum occupancy detection is a key enabler for dynamic spectrum access, where machine learning algorithms are successfully utilized for detection improvement. However, the main challenge is limited access to labeled data about users transmission presence needed in supervised learning models. We present a distributed federated learning approach that addresses this challenge for sensors without access to learning data. The paper discusses the results of the conducted hardware experiment, where FL has been applied for DVB-T signal detection. |
| title | Rozproszone Wykrywanie Zajętości Widma Oparte na Uczeniu Federacyjnym |
| topic | Networking and Internet Architecture |
| url | https://arxiv.org/abs/2411.03017 |