linearization of m-linc systems using gmp and particle swarm optimization for wireless communications

In this paper, an efficient algorithm for the efficiency maximization of the multilevel linear amplification using nonlinear components (m-linc) systems is proposed regarding the linearity of the system. in this algorithm, we use the generalized memory polynomial (gmp) to provide a behavioral model for the power amplifier (pa) and calculate the power spectral density (psd) of the output signal of the system instead of using complicated analytical methods or time-consuming circuit level simulations. in order to have a reliable model, a modeling process which validates the static and dynamic behaviors of the obtained model is provided, and the validation is performed through the time domain signals, psd, and am-am characteristics. as an example, we optimize the efficiency of a 6 level linc system with a 2.4 ghz 25 w doherty pa and a 15 mhz three-tone signal using the particle swarm optimization (pso) method where an upper bound on the adjacent channel leakage ratio (aclr) is considered as the linearity constraint. our results show that for each given aclr limit by a communication standard, the efficiency can be maximized with a certain number of levels in m-linc system. furthermore, the results unveil the trade-off between linearity and efficiency in m-linc systems.