As an important agricultural production area, Xinjiang Aksu region faces the problem of low energy efficiency of its agricultural small base stations. The traditional RF power amplifier has the disadvantages of high energy consumption and low spectral efficiency, which affects the construction of agricultural informationization. This study proposes an optimization method of RF power amplifier energy efficiency for agricultural small base station in Aksu area based on fuzzy logic control. The Sugeno fuzzy model is used to construct an adaptive fuzzy neural inference system, which is combined with the orthogonal least squares method to screen the polynomial coefficients, and an ant colony algorithm to find the optimal weight configuration. The experimental results show that the fuzzy logic control algorithm is outstanding in energy efficiency optimization, and its energy efficiency is 38% higher than the SIC algorithm and 88% higher than the OMP algorithm when the number of RF links is 2. The energy efficiency is 71% higher than the SIC algorithm when the maximum transmitting power is 60 dBm. The spectrum efficiency is 9% higher than the SIC algorithm and the energy efficiency is 66% higher than the SIC algorithm when the number of transmitting antennas of the base station reaches 200. At the same time, the energy efficiency is improved by 66%. In addition, after adding fuzzy logic control, the power spectrum output is closer to the input signal, the maximum difference is only 60dBW, and the BER is significantly reduced to about 0.2. The study proves that the fuzzy logic control can effectively solve the RF amplifier nonlinearity problem of agricultural small base station, and significantly improve the energy efficiency while guaranteeing the spectral efficiency, which provides an effective solution for the construction of agricultural communication infrastructure in Aksu region.
