Federated Learning of Jamming Classifiers: From Global to Personalized Models

Peng Wu
Peng Wu
¹Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
Helena Calatrava,
Helena Calatrava,
¹Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
Tales Imbiriba
Tales Imbiriba
¹Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
and Pau Closas
Pau Closas
¹Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA

NAVIGATION: Journal of the Institute of Navigation
March 2025,
72
(1)
navi.688;
DOI: https://doi.org/10.33012/navi.688

FIGURE 6

Example results from FedAvg across 400 rounds with a non-IID data set (a) Accuracy of different number of clients. (b) Confusion matrix for M = 20 clients. (c) Confusion matrix for M = 40 clients.

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Federated Learning of Jamming Classifiers: From Global to Personalized Models

Peng Wu

Peng Wu

Helena Calatrava,

Helena Calatrava,

Tales Imbiriba

Tales Imbiriba

and Pau Closas

Pau Closas

Institute of Navigation

March 2025,

72

(1)

navi.688;

DOI: 10.33012/navi.688

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Federated Learning of Jamming Classifiers: From Global to Personalized Models

Peng Wu

Peng Wu

Helena Calatrava,

Helena Calatrava,

Tales Imbiriba

Tales Imbiriba

and Pau Closas

Pau Closas

Institute of Navigation

March 2025,

72

(1)

navi.688;

DOI: 10.33012/navi.688

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