TY - JOUR
T1 - Agenet
T2 - Age of Information evaluation in wireless networks
AU - Basnayaka, Chathuranga M. Wijerathna
AU - Fachada, Nuno
N1 - info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04111%2F2020/PT#
info:eu-repo/grantAgreement/FCT/Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017%2F2018) - Financiamento Base/UIDB%2F00066%2F2020/PT#
info:eu-repo/grantAgreement/FCT/CEEC INST 2ed/CEECINST%2F00002%2F2021%2FCP2788%2FCT0001/PT#
Funding Information:
This research was partially funded by the Fundação para a Ciência e a Tecnologia (FCT, https://ror.org/00snfqn58) under Grants UIDB/04111/2020, UIDB/00066/2020, and CEECINST/00002/2021/CP2788/CT0001, as well as by the Instituto Lusófono de Investigação e Desenvolvimento (ILIND), Portugal under Projects COFAC/ILIND/COPELABS/1/2022 and COFAC/ILIND/COPELABS/1/2024.
Publisher Copyright:
© 2025 The Authors
PY - 2025/5
Y1 - 2025/5
N2 - The Age of Information (AoI) has emerged as a critical performance metric for evaluating time-sensitive wireless communications systems, where maintaining freshness of information and transmission reliability is crucial. In modern ultra-reliable low-latency communication networks, short-packet transmissions are essential for energy efficiency and low latency. This paper introduces Agenet, an open-source Python package designed to estimate AoI in cooperative wireless networks. It implements a system model over Rayleigh fading channels, combining finite blocklength information theory and AoI analysis. The package offers tools to calculate signal-to-noise ratio, block error rate, and both theoretical and simulated AoI. By enabling analysis of AoI performance under various network configurations, Agenet supports research and development of efficient wireless systems for time-critical applications.
AB - The Age of Information (AoI) has emerged as a critical performance metric for evaluating time-sensitive wireless communications systems, where maintaining freshness of information and transmission reliability is crucial. In modern ultra-reliable low-latency communication networks, short-packet transmissions are essential for energy efficiency and low latency. This paper introduces Agenet, an open-source Python package designed to estimate AoI in cooperative wireless networks. It implements a system model over Rayleigh fading channels, combining finite blocklength information theory and AoI analysis. The package offers tools to calculate signal-to-noise ratio, block error rate, and both theoretical and simulated AoI. By enabling analysis of AoI performance under various network configurations, Agenet supports research and development of efficient wireless systems for time-critical applications.
KW - Age of Information
KW - Short-packet transmission
KW - Wireless networks
UR - https://www.scopus.com/pages/publications/85217909937
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001430832000001
U2 - 10.1016/j.softx.2025.102086
DO - 10.1016/j.softx.2025.102086
M3 - Article
AN - SCOPUS:85217909937
SN - 2352-7110
VL - 30
SP - 1
EP - 10
JO - SoftwareX
JF - SoftwareX
M1 - 102086
ER -