In this paper, we study the problem of minimizing the age of information when a source can transmit status updates over two heterogeneous channels. Our work is motivated by recent developments in 5G mmWave technology, where transmissions may occur over an unreliable but fast (e.g., mmWave) channel or a slow reliable (e.g., sub-6GHz) channel. The unreliable channel is modeled as a time-correlated Gilbert-Elliot channel, where information can be transmitted at a high rate when the channel is in the ''ON'' state. The reliable channel provides a deterministic but lower data rate. The scheduling strategy determines the channel to be used for transmission with the aim to minimize the time-average age of information (AoI). The optimal scheduling problem is formulated as a Markov Decision Process (MDP), which in our setting poses some significant challenges because e.g., supermodularity does not hold for part of the state space. We show that there exists a multi-dimensional threshold-based scheduling policy that is optimal for minimizing the age. A low-complexity bisection algorithm is further devised to compute the optimal thresholds. Numerical simulations are provided to compare different scheduling policies.
翻译:在本文中, 我们研究在信息来源可以通过两个不同渠道传输状态更新信息时, 将信息年龄最小化的问题。 我们的工作是由5GmmWave技术的最新发展推动的, 5GmmWave技术的传输可能发生在不可靠但快速的频道( 例如, mmWave) 频道或一个缓慢的可靠频道( 例如, sub-6GHz) 。 不可靠的频道建模为一个与时间有关Gilbert- Elliot 频道, 当频道处于“ ON” 状态时, 信息可以以高速度传输。 可靠的频道提供了一种确定性但较低的数据率。 排期战略决定了传输的频道, 目的是尽可能缩短信息的平均时间年龄( AoI) 。 最佳的排程问题被写成一个Markov 决策过程( MDP ), 因为在我们的设置中, 超时标不会维持部分国家空间。 我们显示, 存在一种基于多维的阈值的调度政策, 最有利于最小化年龄。 低的双轴算算算算法进一步对比最佳的模型。