Energy Cooperation for Sustainable Base Station Deployments: Principles and Algorithms

Abstract

Abstract-Energy self-sufficiency is of prime importance for future mobile networks. The design of energy efficient and possibly self-sustainable base stations is key to reduce their impact on the environment, and diminish their operating expense. As a solution to this, we advocate base station deployments featuring energy harvesting and storage capabilities. Each base station can acquire energy from the environment, promptly use it to serve the local traffic or keep it in its storage for later use. In addition, a power packet grid (DC power lines and switches) is utilized to enable energy transfer (energy routing) across base stations, compensating for imbalance in the harvested energy or in the load. Most of the base stations are offgrid, i.e., they can only use the locally harvested energy and that transferred from other network elements, whereas some of them are ongrid, i.e., they can also purchase energy from the electrical grid. We formulate the optimal energy allocation and routing as a convex optimization problem with the goals of improving the energy self-sustainability of the network, while achieving high energy transfer efficiencies under dynamic load and energy harvesting processes. An optimal assignment based on the Hungarian method is also presented. Our numerical results reveal that the proposed convex policy: (i) substantially improves the energy self-sustainability of the system, (ii) decreases its outage probability to nearly zero, even when a small number of base stations are connected to the electrical grid, and (iii) the amount of energy purchased from the electrical grid per served user is respectively decreased of three and eight times with respect to using the Hungarian policy and a scenario where the energy exchange among base stations is not permitted.

Energy cooperation for sustainable IoT services within smart cities

“…where the energy consumption is eventually connected to the number of sensing nodes that are associated to the gateway, and the individual data rate of each sensor node. The energy transfer among gateways is performed following the same technique used in [7]. Energy losses are considered and depend on the distance ℓ between source and destination gateways, the resistivity of the wire connecting them (denoted as , measured in Ω mm 2 /m) and its cross sectional area ( , mm 2 ) [16]:…”

“…This variability in the energy harvesting model is taken into account as follows. ℎ ( ) is the amount of harvested energy in time slot for gateway [7]: it depends on the energy profile ( ) (equal for all gateways) and (0, ), which is sampled from a uniform probability distribution function in the open interval (0, ), where embodies the correlation among the harvested energy profiles across gateways:…”

“…Specifically, in each time slot , gateways can precisely define their roles in the energy cooperation scheme depending on the energy battery level and these energy thresholds. Hence, the behavior of gateway ∈ is set in the following way [7]:…”

“…A few works have investigated energy cooperation among base stations (BS). The authors of [7] propose an energy allocation scheme for energy harvesting BSs. A convex formulation is posed and the obtained energy allocation policies are compared against an assignment problem solved through the Hungarian method.…”

“…All the gateways are connected to a central node called the energy router, which determines the energy allocation among GWs and implement the needed energy transfers. This nomenclature is taken from [7]. Through the interconnected grid, energy is exchanged from high battery level GWs to energy scarce ones.…”