Title: A Decentralized Optimization Framework for Energy Harvesting Devices,
Abstract: Designing decentralized policies for wireless communication networks is a
crucial problem, which has only been partially solved in the literature so far.
In this paper, we propose the Decentralized Markov Decision Process (Dec-MDP)
framework to analyze a wireless sensor network with multiple users which access
a common wireless channel. We consider devices with energy harvesting
capabilities, so that they aim at balancing the energy arrivals with the data
departures and with the probability of colliding with other nodes. Randomly
over time, an access point triggers a SYNC slot, wherein it recomputes the
optimal transmission parameters of the whole network, and distributes this
information. Every node receives its own policy, which specifies how it should
access the channel in the future, and, thereafter, proceeds in a fully
decentralized fashion, without interacting with other entities in the network.
We propose a multi-layer Markov model, where an external MDP manages the jumps
between SYNC slots, and an internal Dec-MDP computes the optimal policy in the
near future. We numerically show that, because of the harvesting, a fully
orthogonal scheme (e.g., TDMA-like) is suboptimal in energy harvesting
scenarios, and the optimal trade-off lies between an orthogonal and a random
access system.