Optimizing the Age of Information in Mixed-Critical Wireless Communication Networks

Fuente: arXiv
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Autori principali: Reifert, Robert-Jeron, Roth, Stefan, Sezgin, Aydin
Natura: Preprint
Pubblicazione: 2022
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author Reifert, Robert-Jeron
Roth, Stefan
Sezgin, Aydin
author_facet Reifert, Robert-Jeron
Roth, Stefan
Sezgin, Aydin
contents Beyond fifth generation wireless communication networks (B5G) are applied in many use-cases, such as industrial control systems, smart public transport, and power grids. Those applications require innovative techniques for timely transmission and increased wireless network capacities. Hence, this paper proposes optimizing the data freshness measured by the age of information (AoI) in dense internet of things (IoT) sensor-actuator networks. Given different priorities of data-streams, i.e., different sensitivities to outdated information, mixed-criticality is introduced by analyzing different functions of the age, i.e., we consider linear and exponential aging functions. An intricate non-convex optimization problem managing the physical transmission time and packet outage probability is derived. Such problem is tackled using stochastic reformulations, successive convex approximations, and fractional programming, resulting in an efficient iterative algorithm for AoI optimization. Simulation results validate the proposed scheme's performance in terms of AoI, mixed-criticality, and scalability. The proposed non-orthogonal transmission is shown to outperform an orthogonal access scheme in various deployment cases. Results emphasize the potential gains for dense B5G empowered IoT networks in minimizing the AoI.
format Preprint
id arxiv_https___arxiv_org_abs_2211_05797
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Optimizing the Age of Information in Mixed-Critical Wireless Communication Networks
Reifert, Robert-Jeron
Roth, Stefan
Sezgin, Aydin
Information Theory
Signal Processing
Beyond fifth generation wireless communication networks (B5G) are applied in many use-cases, such as industrial control systems, smart public transport, and power grids. Those applications require innovative techniques for timely transmission and increased wireless network capacities. Hence, this paper proposes optimizing the data freshness measured by the age of information (AoI) in dense internet of things (IoT) sensor-actuator networks. Given different priorities of data-streams, i.e., different sensitivities to outdated information, mixed-criticality is introduced by analyzing different functions of the age, i.e., we consider linear and exponential aging functions. An intricate non-convex optimization problem managing the physical transmission time and packet outage probability is derived. Such problem is tackled using stochastic reformulations, successive convex approximations, and fractional programming, resulting in an efficient iterative algorithm for AoI optimization. Simulation results validate the proposed scheme's performance in terms of AoI, mixed-criticality, and scalability. The proposed non-orthogonal transmission is shown to outperform an orthogonal access scheme in various deployment cases. Results emphasize the potential gains for dense B5G empowered IoT networks in minimizing the AoI.
title Optimizing the Age of Information in Mixed-Critical Wireless Communication Networks
topic Information Theory
Signal Processing
url https://arxiv.org/abs/2211.05797