Energy Harvesting Wireless Communications: A Review of Recent Advances

This article summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed as well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications (Special Issue: Wireless Communications Powered by Energy Harvesting and Wireless Energy Transfer

Renewable Powered Cellular Networks: Energy Field Modeling and Network Coverage

Powering radio access networks using renewables, such as wind and solar power, promises dramatic reduction in the network operation cost and the network carbon footprints. However, the spatial variation of the energy field can lead to fluctuations in power supplied to the network and thereby affects its coverage. This warrants research on quantifying the aforementioned negative effect and countermeasure techniques, motivating the current work. First, a novel energy field model is presented, in which fixed maximum energy intensity $\gamma$ occurs at Poisson distributed locations, called energy centers. The intensities fall off from the centers following an exponential decay function of squared distance and the energy intensity at an arbitrary location is given by the decayed intensity from the nearest energy center. The product between the energy center density and the exponential rate of the decay function, denoted as $\psi$, is shown to determine the energy field distribution. Next, the paper considers a cellular downlink network powered by harvesting energy from the energy field and analyzes its network coverage. For the case of harvesters deployed at the same sites as base stations (BSs), as $\gamma$ increases, the mobile outage probability is shown to scale as $(c \gamma^{-\pi\psi}+p)$, where $p$ is the outage probability corresponding to a flat energy field and $c$ a constant. Subsequently, a simple scheme is proposed for counteracting the energy randomness by spatial averaging. Specifically, distributed harvesters are deployed in clusters and the generated energy from the same cluster is aggregated and then redistributed to BSs. As the cluster size increases, the power supplied to each BS is shown to converge to a constant proportional to the number of harvesters per BS.Comment: double-column, 13 pages; to appear in IEEE Transactions on Wireless Communication

Coverage of renewable powered cellular networks

Session: SS4 Energy‐Aware Communications: no. 1570002605Powering a radio access network using renewables such as wind and solar power promises dramatic reduction of the network operation cost and of the networks' carbon footprints. However, the spatial variation of the energy field can lead to fluctuation in power supplied to the network and thereby affects its coverage. To quantify the effect, the paper considers a cellular downlink network with hexagonal cells and powered by harvesting energy. The network coverage of mobiles is specified by an outage constraint. A novel model of the energy field is developed using stochastic geometry. In the model, fixed maximum energy intensity occurs at Poisson distributed locations, called energy centers; the intensities fall off from the centers following an exponential-decay function of squared distance; the energy intensity at an arbitrary location is given by the decayed intensity from the nearest energy center. First, consider single harvesters deployed on the same sites as base stations (BSs). The mobile outage probability is shown to decrease exponentially with the product of the energy-field parameters: the energy-center density and exponential rate of the energy-decay function. Next, consider distributed harvesters whose generated energy is aggregated and then re-distributed to BSs. As the number of harvesters per aggregator increases, the power supplied to each BS is shown to converge to a constant proportional to the number of harvesters per BS, which counteracts the randomness of the energy field. © 2014 IEEE.published_or_final_versio

A joint scheduling and content caching scheme for energy harvesting access points with multicast

© 2017 IEEE. In this work, we investigate a system where users are served by an access point that is equipped with energy harvesting and caching mechanism. Focusing on the design of an efficient content delivery scheduling, we propose a joint scheduling and caching scheme. The scheduling problem is formulated as a Markov decision process and solved by an on-line learning algorithm. To deal with large state space, we apply the linear approximation method to the state-Action value functions, which significantly reduces the memory space for storing the function values. In addition, the preference learning is incorporated to speed up the convergence when dealing with the requests from users that have obvious content preferences. Simulation results confirm that the proposed scheme outperforms the baseline scheme in terms of convergence and system throughput, especially when the personal preference is concentrated to one or two contents