An Adaptive Energy Consumption Optimization Method Based on Channel Correlation Information in Massive MIMO Systems

High energy efficiency of massive MIMO system is the nuclear demand in 5G communication. Considering the Shannon capacity, the capacity gains have a clear upper and lower bound: the too high or too low SNR (signal-to-noise ratio) may be ineffective to boost the channel capacity. Therefore, the best operating SNR point suited optimal energy consumption is inevitable and significant. Based on this, the ECO (energy consumption optimization) theory is proposed to seek the minimum energy cost per bit, which provides a best compromise between the energy consumption and channel capacity. To this purpose, an adaptively MIMO antenna energy distribution algorithm with varying channel characteristics is presented. Consequently, the analysis and simulation results show that the optimal energy consumption is existing and obtainable, and the 5% energy cost improvement per bit can be obtained by use of ECO method.