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A multi-access wireless network with N transmitting nodes, each equipped withan energy harvesting (EH) device and a rechargeable battery of finite capacity,is studied. At each time slot (TS) a node is operative with a certainprobability, which may depend on the availability of data, or the state of itschannel. The energy arrival process at each node is modelled as an independenttwo-state Markov process, such that, at each TS, a node either harvests oneunit of energy, or none. At each TS a subset of the nodes is scheduled by theaccess point (AP). The scheduling policy that maximises the total throughput isstudied assuming that the AP does not know the states of either the EHprocesses or the batteries. The problem is identified as a restless multiarmedbandit (RMAB) problem, and an upper bound on the optimal scheduling policy isfound. Under certain assumptions regarding the EH processes and the batterysizes, the optimality of the myopic policy (MP) is proven. For the generalcase, the performance of MP is compared numerically to the upper bound.

Multi-Access Communications with Energy Harvesting: A Multi-Armed Bandit Model and the Optimality of the Myopic Policy