Wireless Communication

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Basis Expansion Models Analysis for MIMO/OFDM Systems


Affiliations
1 School of Electronics Engineering, VIT University, Vellore, Tamil Nadu, India
2 School of Electronics Engineering, VIT University, Vellore, Tamil Nadu, India
     

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We consider Channel estimation for multiple-input multiple-output/orthogonal frequency-division multiplexing (MIMO/ OFDM) systems in time-varying wireless channels using superimposed training (ST). By using a discrete prolate spheroidal basis expansion model (DPSS) and truncated discrete fourier bases expansion models (Fourier-BEM) for representing the time varying channel. Based on these models, a weighted average approach is adopted for estimating linear time varying (LTV) channels for OFDM symbols. The performance analysis between two BEM models based on Mean square error (MSE) is present in this paper. Simulation results show that the DPSS-BEM model outperforms the Fourier Bases expansion model.

Keywords

Basis Expansion Models (BEMS), MIMO/OFDM, Slepian Sequences, Superimposed Training.
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  • Basis Expansion Models Analysis for MIMO/OFDM Systems

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Authors

K. V. N. Kavitha
School of Electronics Engineering, VIT University, Vellore, Tamil Nadu, India
Sibaram Khara
School of Electronics Engineering, VIT University, Vellore, Tamil Nadu, India
J. V. Rama Krishna Reddy
School of Electronics Engineering, VIT University, Vellore, Tamil Nadu, India

Abstract


We consider Channel estimation for multiple-input multiple-output/orthogonal frequency-division multiplexing (MIMO/ OFDM) systems in time-varying wireless channels using superimposed training (ST). By using a discrete prolate spheroidal basis expansion model (DPSS) and truncated discrete fourier bases expansion models (Fourier-BEM) for representing the time varying channel. Based on these models, a weighted average approach is adopted for estimating linear time varying (LTV) channels for OFDM symbols. The performance analysis between two BEM models based on Mean square error (MSE) is present in this paper. Simulation results show that the DPSS-BEM model outperforms the Fourier Bases expansion model.

Keywords


Basis Expansion Models (BEMS), MIMO/OFDM, Slepian Sequences, Superimposed Training.