Optimal Design of Low Power CMOS Power Amplifier Using Particle Swarm Optimization Technique

We applied the stochastic salp swarm algorithm (SSA) to design high power amplifier (PA) and digital pre-distorter (DPD) using generalized memory polynomial model. This algorithm has high exploitation and convergence speed to solve the non-linear coefficient of memory polynomial. We considered a single carrier WCDMA input for the static non-linearity of the memory based high power amplifier. Various simulations have been conducted to validate the performance of SSA over PA and DPD using different memory depths and degrees combinations which demonstrates that the proposed approach is an effective solution for linearity of high generation wideband transmitters. The performance of SSA is compared with particle swarm optimization and shows the superiority of SSA in terms of lower adjacent channel power ratio, error vector magnitude, normalized mean square error and modeling error. The implementation of SSA on PA and DPD has been done separately and then cascaded to generate a resultant linear output.

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“…The non-linear coefficients of the PA and DPD model were identified using the SSA and PSO algorithms as stated below. (15)…”

Section: Simulation Study and Discussionmentioning

confidence: 99%

“…In [14], PSO was used to identify non-linear parameters and results into low memory cost and insignificant memory-units. The PSO was used in [15] to achieve a linearized PA, competent to efficiently recompense higher power aided efficiency and gain. A PSO with embedded ability of model-size estimation was proposed in [16].…”

Section: Related Workmentioning

confidence: 99%