Gradient-free Online Resource Allocation Algorithms for Dynamic Wireless Networks

Alexandre Marcastel (1) , Elena-Veronica Belmega (1) , Panayotis Mertikopoulos (2) , Inbar Fijalkow (1)

1 ETIS - UMR 8051 - Equipes Traitement de l'Information et Systèmes
2 POLARIS - Performance analysis and optimization of LARge Infrastructures and Systems

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allocation policies that are able to adapt on-the-fly to the network dynamics while relying on little and possibly outdated information.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.

Mots clés: online optimization; zeroth-order feedback; arbitrarily time-varying networks; Index Terms-Highly mobile devices

Domaines: Traitement du signal et de l'image [eess.SP]; Réseaux et télécommunications [cs.NI]

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⟩