Radiation pattern synthesis using hybrid fourier-woodward-lawson-neural networks for reliable mimo antenna systems

摘要: In this paper, we implement hybrid Woodward-Lawson Neural Networks and weighted Fourier method to synthesize antenna arrays. The neural networks (NN) is applied here simplify the modeling of MIMO arrays by assessing phases. main problem obviously find optimal weights linear array elements giving radiation pattern with minimum sidelobe level (SLL) hence ameliorating performance. To attain purpose, an for reliable Multiple-Input Multiple-Output (MIMO) applications frequency at 2.45 GHz implemented. validate suggested method, many examples uniformly excited patterns beam are put in direction useful signal. synthesis permits out interesting analytical equations highlights flexibility between system parameters input those output. performance optimization underlines how well suitable a wireless communication it participates reducing interference, as well.