AuthorsR. Sharan, S. Deshmukh, S. R. B. Pillai and B. Beferull-Lozano
TitleEnergy Efficient AoI Minimization in Opportunistic NOMA/OMA Broadcast Wireless Networks
AfilliationCommunication Systems
Project(s)Signal and Information Processing for Intelligent Systems
Publication TypeJournal Article
Year of Publication2021
JournalIEEE Transactions on Green Communications and Networking
Place PublishedIEEE Transactions on Green Communications and Networking

The concept of Age of Information (AoI) minimization in wireless networks has garnered huge interest in recent times. While current literature focuses on scheduling for AoI minimization, there is also a need to efficiently utilize the underlying physical layer resources. In this paper, we consider the problem of energy-efficient scheduling for AoI minimization in an opportunistic NOMA/OMA downlink broadcast wireless network, where the user equipment operate with diverse QoS requirements. We first formulate a resource allocation problem to minimize the average AoI of the network, with energy-efficiency factored in by restricting the long term average transmit power to a predetermined threshold. A heuristic adaptation of the driftplus-penalty approach from the Lyapunov framework is then utilized to solve the original long-term mixed-integer nonlinear problem on a per time-slot basis. The single time-slot problem is further decomposed into multiple sub-problems, solving for power allocation and user scheduling separately. However, the attained power allocation sub-problems being non-convex, we propose an efficient piece-wise linear approximation to obtain a tractable solution. The scheduling sub-problem is solved optimally by using the integrality property of the linear program. Finally, we provide extensive numerical simulations to show that our proposed approach outperforms the state of the art.


This research work was carried out at University of Agder and completed after the SIGIPRO Department was created. This work was supported by the Research Council of Norway through FRIPRO TOPPFORSK under Grant WISECART 250910/F20.

Citation Key28421

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