SSA optimized digital pre-distorter for compensating non-linear distortion in high power amplifier
M Malhotra, AS Sappal - Telecommunication Systems, 2019 - Springer
M Malhotra, AS Sappal
Telecommunication Systems, 2019•SpringerWe 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 …
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 …
Abstract
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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