Abstract:
Wireless communication has seen exponential growth in the past few decades due to
advancements in digital communication technologies resulting in emerging wireless
technologies such as LTE-A and WiMAX. Resultantly, wireless communication is
becoming the main choice for voice as well as data communication. However, the
increasing voice, data and internet services are costing heavy on resources. The
consequent resource constraint is driving the technology developers to look for
resource optimization solutions in all domains, particularly energy.
The future radio access networks (RAN) like 5G will comprise denser and diverse
heterogeneous networks (HetNets) of macro, micro, pico and femto BSs. Energy
resource management of such networks is of prime concern besides improving
throughput, latency and quality of service. This involves improving energy efficiency
of all elements such as back haul network, data centers, base stations and mobile
terminals. Amongst these, the base station is the most energy hungry entity,
consuming as much as 60% of the networks energy. Research is, therefore, focusing
component, system and network level energy efficiency improvements by employing
schemes such as 'energy cooperation' between base stations.
The number of BS sites, worldwide, are expected to increase to more than 11 million,
consuming 98 TWh annually, by year 2020. Consequently, it is resulting in increased
GHG emissions since most of the power comes from the fossil fuel based energy
sources. Thus, BSs have become a strong candidate for different energy efficient
techniques as well as incorporation of renewable energy sources (RES) such as solar
panels and wind turbines. Base stations are ideally suited to have renewable sources
installed because all four elements of energy generation, transmission, storage and
consumption are located at one place. RES are not only feasible for stand-alone or
off-grid BS, but also for on-grid BS, especially smart-grid tied.
Equipping base stations with renewable energy sources of solar and wind is feasible
for areas having good sunshine and windy conditions. By considering the fluctuations
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in the base station load because temporal and spatial variations in traffic, it is possible
to have energy cooperation between nodes. A base station having deficient green
(harvested) energy is encouraged to borrow it from a neighbor rather than acquire it
from GHG emitting sources such as diesel generator. A novel extension of this
scheme is designed to combine it with sleep mechanism in networks where lean base
stations are put to sleep and their energy and load are distributed in the network. The
strategies of energy resource optimization thus incorporated yield positive results in
energy cost savings for the network.
In this research, initially, a PV array of 7.8 kW and a wind turbine of 7.5 kW peak
power has been modeled for Islamabad region, for a BS consuming 2.35 kWh peak
energy. It is shown that base stations harvesting renewable energy may have surplus
energy that can be shared with other base stations or even sold back to the grid
through net metering. Since the energy consumption of a BS is not fixed and
fluctuates with the traffic load, the energy produced from renewable energy sources
may be more than the energy consumed, especially during off peak hours, opening the
venues for energy cooperation between nodes.
We consider a cellular network of N macro BSs equipped with energy harvesting
systems (solar, wind or both) modeled for site whose weather parameters are known.
The network is powered by the conventional grid (Utility), with a diesel generator
providing backup power at each BS. We consider a finite horizon time slotted system
where the decision to share energy is made for a definite time t (1 ≤ t ≤ T). The key
elements of our system model are; solar/wind energy harvesting base stations, a
battery bank for energy storage at the base station, inter-connectivity between the base
station through grid, smart grid or central controller, for energy transfer, and an
energy management unit at the base station running the algorithms.
We propose a frame work for traffic aware sustainable and environmental friendly
base station operation through energy cooperation (TASEEC) in grid connected green
cellular network, where each base station is encouraged to acquire energy from
renewable source and all base stations are also connected to the utility grid. The
mathematically modeled framework jointly takes care of static and traffic aware load
on the BS. In TASEEC, the optimizer always selects economical power source for
buying purposes. The frame-work is based on the fact that the base station operators
have an agreement on energy cooperation and on cooperation tariff. The main aim is
to jointly minimize the operational cost and greenhouse gas emissions. The cost
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includes self-generation cost, cost of energy purchased from other BSs and cost of
energy procured from grid. The non-linear problem is linearized by applying
McCormick approximation and solved through interior point method. The framework
is further extended to a heterogeneous umbrella network with base station on/off
switching incorporated in addition to energy cooperation scheme discussed above.
The results are shown for individual base stations and the energy cost savings -as a
result of proposed energy cooperation strategy - are depicted as a percentage
reduction in network’s energy consumption cost.