Abstract:
This paper investigates a multiuser scheduling problem within an uplink multiple-input multi-output (MIMO) status update network, consisting of a multi-antenna access poi...View moreMetadata
Abstract:
This paper investigates a multiuser scheduling problem within an uplink multiple-input multi-output (MIMO) status update network, consisting of a multi-antenna access point (AP) and multiple single-antenna devices. The presence of multiple an-tennas at the AP introduces spatial degrees-of-freedom, enabling concurrent transmission of status updates from multiple devices in each time slot. Our objective is to optimize network-wide information freshness, as measured by the age of information (AoI) metric, by determining how the AP can best schedule device transmissions, while taking into account the random arrival of status updates at the device side. It is worth noting that the AP has partial observations of the system time of the latest updates at each device when making scheduling decisions. To address this decision-making problem, we model it as a partially observable Markov decision process (POMDP) and establish that the evolution of belief states for different devices is independent. We also manage to characterize feasible belief states using three-dimensional vectors. Building on this foundation, we develop a dynamic scheduling (DS) policy to solve the POMDP and implement an action space reduction. Our numerical results indicate that the DS policy with the reduced action space performs almost identically to the original DS policy, and both outperform the baseline policy that schedules a fixed number of devices.
Published in: 2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)
Date of Conference: 24-27 August 2023
Date Added to IEEE Xplore: 22 December 2023
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