AoI-Aware Multi-Level Dynamic Power Control With Sum-Power Constraint in Downlink Networks

Age of information (AoI), a metric for data freshness in status update systems, has received growing attention in various applications. This paper focuses on dynamic power control to minimize the average AoI of all users in a sum-power constrained downlink network, where each user has multi-level selectable powers in every slot. By relaxing instantaneous sum-power constraint to a time-averaged sum-power constraint, we decompose the Lagrangian minimization problem into multiple independent power allocation subproblems with each corresponding to a particular user. We show that the optimal policy of each subproblem under a given Lagrange multiplier holds a multi-threshold property, based on which the full indexability property can be possessed by every subproblem. By comparing the Whittle indices and the Lagrange multiplier, the full indexability allows us to obtain the Lagrange multiplier which can effectively utilize the power budget. Given this, a low-complexity power allocation approach is proposed to solve the problem. Moreover, we prove the proposed approach is asymptotic optimality when the number of selectable powers are three. Simulation results verify the analysis and show that our proposed approach outperforms benchmark policies.

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Publication Details

Journal
IEEE Transactions on Communications
Published
2025-08-04
DOI
https://doi.org/10.1109/tcomm.2025.3595759
Primary Topic
Power Line Communications and Noise
Type
article
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article

AoI-Aware Multi-Level Dynamic Power Control With Sum-Power Constraint in Downlink Networks

Chongtao Guo, Xijun Wang, Zhiyuan Huang
IEEE Transactions on Communications
Power Line Communications and Noise
article

AoI-Aware Multi-Level Dynamic Power Control With Sum-Power Constraint in Downlink Networks

Chongtao Guo, Xijun Wang, Zhiyuan Huang
article en

Abstract

Age of information (AoI), a metric for data freshness in status update systems, has received growing attention in various applications. This paper focuses on dynamic power control to minimize the average AoI of all users in a sum-power constrained downlink network, where each user has multi-level selectable powers in every slot. By relaxing instantaneous sum-power constraint to a time-averaged sum-power constraint, we decompose the Lagrangian minimization problem into multiple independent power allocation subproblems with each corresponding to a particular user. We show that the optimal policy of each subproblem under a given Lagrange multiplier holds a multi-threshold property, based on which the full indexability property can be possessed by every subproblem. By comparing the Whittle indices and the Lagrange multiplier, the full indexability allows us to obtain the Lagrange multiplier which can effectively utilize the power budget. Given this, a low-complexity power allocation approach is proposed to solve the problem. Moreover, we prove the proposed approach is asymptotic optimality when the number of selectable powers are three. Simulation results verify the analysis and show that our proposed approach outperforms benchmark policies.

IEEE Transactions on CommunicationsVol. 73(12)
Sun Yat-sen University (CN), Shenzhen University (CN)
Affordable and clean energy
Openalex Percentile: Top 82%
Power Line Communications and Noise
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AoI-Aware Multi-Level Dynamic Power Control With Sum-Power Constraint in Downlink Networks — Chongtao Guo, Xijun Wang, et al. · IEEE Transactions on Communications (2025) | TGRS Research Map | TGRS