Abstract
Being capable of characterizing the freshness of information, Age of Information (AoI) has attracted much attention recently. To provide better real-time service over fading channels, efficient scheduling methods are highly desired for wireless transmissions with freshness requirements. However, due to the channel instability and arrival randomness, it is challenging to achieve the optimal AoI. In this paper, we are interested in the AoI-optimal transmissions with truncated channel inversion, which has a low complexity transceiver architecture exploiting fixed coding and modulation. More specifically, we utilize a probabilistic scheduling method to minimize the AoI while satisfying an average power constraint. By characterizing the probabilistic scheduling policy with a Constrained Markov Decision Process (CMDP), we formulate a Linear Programming (LP) problem. Further, we present a low complexity algorithm to obtain the optimal scheduling policy, which is proved to belong to a set of semi-threshold-based policies. Numerical results verify the reduction in computational complexity and the optimality of semithreshold-based policy, which indicates that we can achieve well real-time service with a low calculating complexity.
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