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Gradient-free Online Resource Allocation Algorithms for Dynamic Wireless Networks

Abstract : Future communication networks will be faced with supporting highly mobile, heterogeneous (including aerial) devices, which calls for new and ecient resource allocation policies that are able to adapt on-the-fly to the network dynamics while relying on little and possibly outdated information. The aim of this paper is twofold: to explicitly take into account the device mobility, their network connectivity patterns and behavior (which may be completely arbitrary and unpredictable); and to greatly reduce the information required at the transmitter. For this, we exploit the framework of online optimization and exponential learning to derive a provably ecient and gradient-free online power allocation algorithm relying only on a scalar-worth of feedback.
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Contributor : Alexandre Marcastel <>
Submitted on : Friday, July 19, 2019 - 9:53:40 AM
Last modification on : Wednesday, August 5, 2020 - 3:01:56 AM


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Alexandre Marcastel, Elena-Veronica Belmega, Panayotis Mertikopoulos, Inbar Fijalkow. Gradient-free Online Resource Allocation Algorithms for Dynamic Wireless Networks. SPAWC 2019 - 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, Jul 2019, Cannes, France. pp.1-4, ⟨10.1109/SPAWC.2019.8815409⟩. ⟨hal-02189108⟩



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