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There are already several power models to estimate the power consumption of base stations at system level. However, there is so far no model that can predict power consumption of the future base station designs based on algorithms and hardware selections with insufficient physical information. We present such an energy model for typical base stations. This model can help designers in estimating, evaluating and optimizing energy/power consumption of candidate designs in early design stages. The proposed model is verified by an LTE extreme scenario. The estimated results show that digital front-end, channel equalization and channel decoding are three major power greedy modules(consuming 39.4%, 16.3%, 13.4%) in a digital baseband subsystem. The power estimation error of the proposed power amplifier(PA) power model is 3.5%(macro cell). The major contribution of this paper is that the proposed models can rapidly estimate energy/power consumption of 4G and the future base stations(such as 5G) in early design stages with well acceptable precision, even without sufficient implementation information.
There are already several power models to estimate the power consumption of base stations at system level. However, there is so far no model that can predict power consumption of the future base station designs based on algorithms and hardwarelections with insufficient physical information. We present Such proposed energy model for typical base stations. This model can help designers in estimating, evaluating and optimizing energy / power consumption of candidate designs in early design stages. The estimated results show that digital front -end, channel equalization and channel decoding are three major power greedy modules (consuming 39.4%, 16.3%, 13.4%) in a digital baseband subsystem. The power estimation error of the proposed power amplifier (PA) power model is 3.5% The major contribution of this paper is that the proposed models can rapidly estimate energy / power consumption of 4G and the future base stations (such as 5G ) in early design stages with well acceptable precision, even without sufficient implementation information.