Distributed User Association in Energy Harvesting Small Cell Networks: A Probabilistic Bandit Model

We investigate a distributed downlink user association problem in a dynamic small cell network, where every small base station (SBS) obtains its required energy through ambient energy harvesting. On the one hand, energy harvesting is inherently opportunistic, so that the amount of available energy is a random variable. On the other hand, users arrive at random and require different wireless services, rendering the energy consumption a random variable. In this paper, we develop a probabilistic framework to mathematically model and analyze the random behavior of energy harvesting and energy consumption. We further analyze the probability of QoS satisfaction (success probability), for each user with respect to every SBS. The proposed user association scheme is distributed in the sense that every user independently selects its corresponding SBS with the success probability serving as the performance metric. The success probability however depends on a variety of random factors such as energy harvesting, channel quality, and network traffic, whose distribution or statistical characteristics might not be known at users. Since acquiring the knowledge of these random variables (even statistical) is very costly in a dense network, we develop a bandit-theoretical formulation for distributed SBS selection when no prior information is available at users. The performance is analyzed both theoretically and numerically.