Energy saving in a 5G separation architecture under different power model assumptions

In this paper, a framework is developed to study the impact of different power model assumptions on energy saving in a 5G separation architecture comprising high power Base Stations (BSs) responsible for coverage, and low power, small cell BSs handling data transmission. Starting with a linear power model function, the achievable energy saving are derived over short timescales by operating small cell BSs in low power states rather than higher power states (termed Low Power State Saving (LPSS) gains) for single and multiple BS scenarios. It is shown how energy saving varies with different power model assumptions over long timescales in accordance with short timescale LPSS. Simulation results show that energy saving in the separation architecture varies across the six power models examined as a function of model-specific significant LPSS state changes. Furthermore, it is shown that if the architecture is based on existing small cell BSs modelled by state-of-the-art (SotA) power models, energy saving will be mainly dependent on sleep state operation. Whereas, if it is based on future BSs modelled by visionary power models, both sleep and idle state operations provide energy saving gains. Moreover, with future BSs, energy saving of up to 42% is achievable when idle state overhead is considered, while a higher saving is possible otherwise