MIMO channel modeling using temporal artificial neural network (ANN) architectures

  • Authors:

  • Kandarpa Kumar Sarma;Abhijit Mitra

  • Affiliations:

  • Indian Institute of Technology Guwahati, Guwahati, Assam, India;Indian Institute of Technology Guwahati, Guwahati, Assam, India

  • Venue:
  • Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia
  • Year:
  • 2010

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Abstract

Stochastic nature of wireless channels has continued to make channel estimation a challenging issue. The statistical nature of wireless channels can be tackled using an Artificial Neural Network (ANN) like a multi layer perceptron (MLP) which can be used to provide channel estimation and symbol recovery to minimize the deficiencies of multi-user transmission under multipath fading. MLP based MIMO modeling, however, doesn't consider time varying nature of the wireless channel. This work describes two MLP architectures with temporal characteristics which are found to be better suited for time varying channel conditions especially for slow fading conditions for applications with indoor networks with Multiple-Input Multiple-Output (MIMO) systems using Orthogonal Frequency Division Multiplexing (OFDM) together called MIMO-OFDM.