Stochastic Arrow-Hurwicz Algorithm for Path Selection and Rate Allocation in Self-Backhauled mmWave Networks

Abstract

ne of the key promoters of 5G deployment using millimetre waves is multi-hop self-backhauling. However, the rate allocation and path selection for these networks are challenging tasks. For this purpose, we consider a network utility maximization problem with probabilistic stability constraints. We propose a novel and simple method based on the stochastic Arrow-Hurcwicz algorithm to the optimization problem with gradient estimation using a smoothed functional technique. Numerical results show an improved utility and faster performance compared to the benchmark.