Abstract
Efficient implementation of sophisticated algorithms on digital signal processing (DSP) chips is a key issue in the implementation of software-defined radios. Here, focusing on beamforming and using the average calculation time and hardware usage as the two indicators of efficiency, a performance comparison between two versions of binary particle swarm optimization (PSO) and genetic algorithm, as the two popular evolutionary techniques, is presented. Using our proposed multirun strategy in DSP platforms, we show that modified PSO results in a reduction by 52% and 67% in the hardware utilization and calculation time as compared to genetic algorithm and binary PSO, respectively.
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