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

Abstract

We consider a distributed downlink user association problem in a small cell network, where small cells obtain the required energy for providing wireless services to users through ambient energy harvesting. Since energy harvesting is opportunistic in nature, the amount of harvested energy is a random variable, without any a priori known characteristics. Moreover, since users arrive in the network randomly and require different wireless services, the energy consumption is a random variable as well. In this paper, we propose a probabilistic framework to mathematically model and analyze the random behavior of energy harvesting and energy consumption in dense small cell networks. Furthermore, as acquiring (even statistical) channel and network knowledge is very costly in a distributed dense network, we develop a bandit-theoretical formulation for distributed user association when no information is available at users

27 Pages, Single-Column

References in corpus (2)

• Channel Selection for Network-assisted D2D Communication via No-Regret Bandit Learning with Calibrated Forecasting
• A context-aware matching game for user association in wireless small cell networks

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