Renewable Powered Cellular Networks: Energy Field Modeling and Network Coverage

International audiencePowering radio access networks using renewables,such as wind and solar power, promises dramatic reduction inthe network operation cost and the network carbon footprints.However, the spatial variation of the energy field can leadto fluctuations in power supplied to the network and therebyaffects its coverage. This warrants research on quantifying theaforementioned negative effect and designing countermeasuretechniques, motivating the current work. First, a novel energyfield model is presented, in which fixed maximum energy intensity γ occurs at Poisson distributed locations, called energy centers.The intensities fall off from the centers following an exponentialdecay function of squared distance and the energy intensity atan arbitrary location is given by the decayed intensity from thenearest energy center. The product between the energy centerdensity and the exponential rate of the decay function, denotedasψ, is shown to determine the energy field distribution. Next,the paper considers a cellular downlink network powered byharvesting energy from the energy field and analyzes its networkcoverage. For the case of harvesters deployed at the samesites as base stations (BSs), asγ increases, the mobile outageprobability is shown to scale as(cγ−πψ+p), wherep is the outageprobability corresponding to a flat energy field andc is a constant.Subsequently, a simple scheme is proposed for counteracting theenergy randomness by spatial averaging. Specifically, distributedharvesters are deployed in clusters and the generated energyfrom the same cluster is aggregated and then redistributed toBSs. As the cluster size increases, the power supplied to each BSis shown to converge to a constant proportional to the numberof harvesters per BS. Several additional issues are investigatedin this paper, including regulation of the power transmission lossin energy aggregation and extensions of the energy field mode