Matlab Deep learning-based vehicular channel estimator in high mobility environments

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Abstract communication performance in wireless networks are greatly affected by the fidelity of the channel estimator, revisiting old methods of the estimation of LS and MMSE channels by revealing their shortcomings, a new method based on deep-learning is proposed, demonstrating significant improvements in communications reliability as well as the reduction of the computational complexity of vehicular networks, under different high mobility environments ( high doppler frequency) with very short reflection times are tested by the new model Dl estimator

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