1. In a memory polynomial (MP) based digital predistorter (DPD) connected to a power amplifier, wherein the power amplifier has a feedback loop for inputting amplifier output parameters to the DPD, an MP based digital predistortion method, comprising the steps of: estimating an optimally small DPD memory length, L, and an optimally low nonlinearity order, K, wherein said estimating step further comprises the step of executing a l 0 norm-penalized particle swarm optimization (LP-PSO) procedure, said LP-PSO procedure including a step for calculating for each particle an objective function characterized by the relation, 
 J i CAT =( n )= J i ( n )+αƒ(∥ P i ∥ 0 ) where, J i CAT is a complexity-accuracy tradeoff (CAT) cost function, ∥P i ∥ 0 is the zero-norm of a particle's position vector, defined as  P i  0 = ∑ m = 1 D ⁢  P i ⁡ ( m )  0 and, J i ⁡ ( n ) = 10 ⁢ ⁢ log 10 ⁡ ( 1 N ⁢ ∑ n = 1 N ⁢  e ⁡ ( n )  2  d ⁡ ( n )  2 ) , where, d(n) is a desired output signal used to evaluate accuracy of the estimation, e(n) is a difference between an estimated output signal and the desired output signal, α is a regularization parameter used for scaling the zero-norm modifier part of the cost function, and N is a number of samples used for a training block of said LP-PSO procedure; setting said DPD with said optimally small DPD memory length L and said optimally low nonlinearity order K; and wherein said optimally small memory length L and said optimally low nonlinearity order K improves efficiency of the DPD in linearizing an output signal of the power amplifier.