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Designing decentralized policies for wireless communication networks is acrucial 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 accessa common wireless channel. We consider devices with energy harvestingcapabilities, so that they aim at balancing the energy arrivals with the datadepartures and with the probability of colliding with other nodes. Randomlyover time, an access point triggers a SYNC slot, wherein it recomputes theoptimal transmission parameters of the whole network, and distributes thisinformation. Every node receives its own policy, which specifies how it shouldaccess the channel in the future, and, thereafter, proceeds in a fullydecentralized fashion, without interacting with other entities in the network.We propose a multi-layer Markov model, where an external MDP manages the jumpsbetween SYNC slots, and an internal Dec-MDP computes the optimal policy in thenear future. We numerically show that, because of the harvesting, a fullyorthogonal scheme (e.g., TDMA-like) is suboptimal in energy harvestingscenarios, and the optimal trade-off lies between an orthogonal and a randomaccess system.

A Decentralized Optimization Framework for Energy Harvesting Devices