Age-Optimal Low-Power Status Update over Time-Correlated Fading Channel
Age-Optimal Low-Power Status Update over Time-Correlated Fading Channel
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DOI：
10.1109/isit45174.2021.9517880
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发表时间：
2021-07
期刊：
影响因子：
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通讯作者：
Guidan Yao;A. Bedewy;N. Shroff
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文献类型：
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作者：
Guidan Yao;A. Bedewy;N. Shroff
在本文中，我们考虑传输调度的状态更新系统中，更新周期性地产生和传输的Gilbert-Elliott衰落信道。目标是在平均能量约束下最小化目的地的长期平均信息年龄（AoI）。信道状态通过传输的反馈（Ack/Nack）来揭示;而如果没有传输，则仍然未知。因此，我们必须设计一个调度策略，在能量、AoI、信道探索和信道利用之间进行权衡。该问题被制定为一个受约束的部分可观测马尔可夫决策过程问题（POMDP）。我们表明，最优策略是一个随机的混合不超过两个固定的确定性政策，其中每个是一个阈值型的信念上的通道。我们提出了一个有限状态近似我们的无限状态信念MDP和收敛。基于从研究这个问题中获得的理论见解，我们开发了一个最优算法使用的问题的结构。
In this paper, we consider transmission scheduling in a status update system, where updates are generated periodically and transmitted over a Gilbert-Elliott fading channel. The goal is to minimize the long-run average age of information (AoI) at the destination under an average energy constraint. The channel state is revealed by the feedback (Ack/Nack) of a transmission; while it remains unknown if there is no transmission. Thus, we have to design a scheduling policy that balances tradeoffs across energy, AoI, channel exploration, and channel exploitation. The problem is formulated as a constrained partially observable Markov decision process problem (POMDP). We show that the optimal policy is a randomized mixture of no more than two stationary deterministic policies each of which is of a threshold-type in the belief on the channel. We propose a finite-state approximation for our infinite-state belief MDP and show convergence. Based on the theoretical insights gained from studying this problem, we develop an optimal algorithm using the structure of the problem.