Seyman, M. NuriTaspinar, Necmi2020-06-252020-06-252013closedAccess2193-567X2191-4281https://doi.org/10.1007/s13369-013-0586-1https://hdl.handle.net/20.500.12587/5483Orthogonal frequency division multiplexing (OFDM) combined with multiple input multiple output (MIMO) antennas is one of the promising schemes for high rate data transmission and capacity improvement. However, in these systems, channel estimation task is critical for coherent detection and demodulation. In this study, we have proposed a channel estimator based on radial basis function neural network trained by gradient descent method for MIMO-OFDM systems. Simulation results show that the proposed estimator performs better than other considered channel estimation techniques.eninfo:eu-repo/semantics/closedAccessMIMO-OFDMChannel estimationRadial basis function neural networkArticle3882173217810.1007/s13369-013-0586-12-s2.0-84880731413Q1WOS:000322114200022Q3