Optimization of a pruned 2D Digital Predistortion Model Structure for Power Amplifiers Linearization Twodimensional digital predistortion (2D DPD) is one of the most commonly used approaches to linearize the concurrent dualband radio frequency (RF) power amplifiers (PA). This paper explores the use of a hillclimbing optimization heuristic to determine the optimal structure for 2D DPD. To improve convergence and reduce computation time, we propose a new parameterization for the 2D DPD model. The proposed search criterion is based on the generalized information criterion, which represents the tradeoff between the DPD linearization accuracy in both bands and the model complexity. A comparison against a compressedsensingbased method is also made. The effectiveness of the proposed method is validated with two 20 MHz longtermevolution (LTE) signals on two carriers with 100 MHz frequency separation.

PhysicallyDerived 3Box Power Amplifier Model In this work, a novel approach to reduce the complexity of memory polynomial model is presented. The proposed technique, named the coefficient decomposition (CD) technique, is based on reducing the search space for the memory polynomial coefficients based on memory effects generation mechanism. In this paper, the technique is demonstrated for power amplifier of classes A and AB. In this case, the physical analysis shows that the conventional twodimensional coefficient architecture of the memory polynomial could be simplified into a one dimensional architecture while keeping almost the same accuracy. The performance of the proposed approach is demonstrated and compared with other models using a 30 dBm commercial power amplifier with 20 MHz and 60 MHz LTE signals. The measurements and simulations showed that, the presented model achieves xe2x88x9234.2 dB of NMSE while needing only 13 coefficients compared with 25 needed for a memory polynomial model. Also, the DPD performance of the proposed model is the same as memory polynomial model and comparable with high complexity models like the PLUME and GMP.