Generative adversarial networks for generating synthetic features for Wi-Fi signal quality.

ABSTRACT: Wireless networks are among the fundamental technologies used to connect people. Considering the constant advancements in the field, telecommunication operators must guarantee a high-quality service to keep their customer portfolio. To ensure this high-quality service, it is common to establish partnerships with specialized technology companies that deliver software services in order to monitor the networks and identify faults and respective solutions. A common barrier faced by these specialized companies is the lack of data to develop and test their products. This paper investigates the use of generative adversarial networks (GANs), which are state-of-the-art generative models, for generating synthetic telecommunication data related to Wi-Fi signal quality. We developed, trained, and comp

SUBMITTER: Castelli M 

PROVIDER: S-EPMC8610258 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature