Improving Energy Efficiency through Reduction of Power Consumption in a Cell Site using Ann Controller

The low performance of communication network base station is a technical malady as a result of highpower consumption that will reduce the economic growth of the establishment. This high-power consumption was tackled by introducing improved energy efficiency through reduction of power consumption in base station or a cell site using artificial neural network (ANN) controller. It is done first by characterizing the network understudy, then developing a SIMULINK model for the cell site understudy, and training ANN to enhance the energy efficiency of the base station and integrating the trained ANN to SIMULINK model for the cell site understudy. The results obtained are the lowest conventional congestion experienced in the base station is 1500b/s in 2s while the lowest congestion observed in the base station when ANN controller was imbibed in the system at the same 2s was 1376b/s, the stable conventional power consumed at the base station was 532kW and that occurred at time duration of 4s through 10s. On the other hand, when ANN controller was injected into the system its power consumption reduced to 520.6kW, the stable conventional energy efficiency in the base station was 54% at time of 4s through 10s. Meanwhile, when ANN controller is incorporated in the system the energy efficiency observed in the base station increased to 58.89% thereby enhancing the performance of the network. With these results, the percentage improvement in the energy efficiency when ANN controller is imbibed in the system was 4.89%