Abstract
The recent time has witnessed more reliable and higher data rate transmission standard wireless communication. The wireless channel is to be optimized accordingly. The ISI component at the output of equalizer is forced to zero on use of LTI system having appropriate transfer function. The deteriorating effect of inter symbol interference ia adequately compensated by the method of adaptive equalization. In this paper, the channel has been equalized using Sign Regressor Functional Link Artificial Neural Network model. QAM modulation technique is utilized in this piece of work. Further the weights of the model are optimized using Genetic Algorithm. The result of sign regressor adaptive algorithms have been compared and sign regressor FLANN shows better performance than other algorithm. Finally the optimized result of sign regressor FLANN model is exhibited for QAM in terms of error. Also, the eye pattern is shown f or the result as an evidence.
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Sahoo, J., Mishra, L., Mohanty, M.N. (2017). GA Based Optimization of Sign Regressor FLANN Model for Channel Equalization. In: Xhafa, F., Patnaik, S., Yu, Z. (eds) Recent Developments in Intelligent Systems and Interactive Applications. IISA 2016. Advances in Intelligent Systems and Computing, vol 541. Springer, Cham. https://doi.org/10.1007/978-3-319-49568-2_18
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DOI: https://doi.org/10.1007/978-3-319-49568-2_18
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