Energy-efficient LTE transmission techniques: introducing Green Radio from resource allocation perspective
Abstract
Energy consumption has recently become a key issue from both environmental and economic
considerations. A typical mobile phone network in the UK may consume approximately 40-
50 MW, contributing a significant proportion of the total energy consumed by the information
technology industry. With the worldwide growth in the number of mobile subscribers, the
associated carbon emissions and growing energy costs are becoming a significant operational
expense, leading to the need for energy reduction. The Mobile VCE Green Radio Project has
been launched, which targets to achieve 100x energy reduction of the current wireless networks
by 2020. In this thesis, energy-efficient resource allocation strategies have been investigated
taking the LTE system as an example.
Firstly, theoretical analysis of energy-efficient design in cellular environments is provided according
to the Shannon Theory. Based on a two-link scenario the performance of simultaneous
transmission and orthogonal transmission for network power minimization under the specified
rate constraints is investigated. It is found that simultaneous transmission consumes less
power than orthogonal transmission close to the base station, but much more power in the cell-edge
area. Also, simulation results suggest that the energy-efficient switching margins between
these two schemes are dominated by the sum total of their required data rates. New definitions
of power-utility and fairness metrics are further proposed, following by the design of weighted
resource allocation approaches based on efficiency-fairness trade-offs.
Apart from energy-efficient multiple access between different links, the energy used by individual
base stations can also be reduced. For example, deploying sleep modes is an effective
approach to reduce radio base station operational energy consumption. By periodically switching
off the base station transmission, or using fewer transmit antennas, the energy consumption
of base station hardware may decrease. By delivering less control signalling overhead, the
radio frequency energy consumption can also be reduced. Simulation results suggest that up
to 90% energy reduction can be obtained in low traffic conditions by employing time-domain
optimization in each radio frame. The optimum on/off duty cycle is derived, enabling the
energy consumption of the base station to scale with traffic loads. In the spatial-domain, an
antenna selection criterion is proposed, indicating the most energy-efficient antenna configuration
with the knowledge of users’ locations and quality of service requirements. Without
time-domain sleep modes, using fewer transmit antennas could outperform full antenna transmission.
However, with time-domain sleep modes, using all available antennas is generally the
most energy-efficient choice.