Gradient-free Online Resource Allocation Algorithms for Dynamic Wireless Networks

International audienceFuture 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allocation policies that are able to adapt on-the-fly to the network dynamics whilerelying on little and possibly outdated information. The aim of this paper is twofold: to explicitly take into account the devicemobility, 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 exponentiallearning to derive a provably ecient and gradient-free online power allocation algorithm relying only on a scalar-worth offeedback