KALMAN FILTER BASED CHANNEL ESTIMATION METHOD FOR MIMO-OFDM SYSTEM WITH LOW COMPLEXITY
Published In: INTERNATIONAL CONFERENCE ON RECENT TRENDS IN COMPUTING AND COMMUNICATION ENGINEERING
Author(s): PRAVEEN KUMAR , G RAVINDAR REDDY , GANESH MIRIYALA , VINDHYA KANIGIRI
Abstract: In multi input multi output orthogonal frequency division multiplexing (MIMO-OFDM) systems, a low complexity subspace based time domain channel estimation method is studied. This method works based on parametric channel model, where the response of the time varying channel is considered as a collection of sparse propagation paths. Translate the estimation of channel parameters into an unconstrained minimized problem by considering the channel correlation matrix. To solve this problem, Kalman filter based method which tracks the subspace is proposed, which provides the constant subspace to construct state equation and measurement equation. This method represents a low complexity subspace schemes. The approach can be extended to MC-CDMA systems. The simulation results prove that the Kalman filter method can track faster fading channel, and is more accurate with low complexity
- Publication Date: 21-Apr-2013
- DOI: 10.15224/978-981-07-6184-4-5
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HYBRID STRUCTURE OF LORENZ AND CHEN’S ATTRACTOR
Published In: INTERNATIONAL CONFERENCE ON RECENT TRENDS IN COMPUTING AND COMMUNICATION ENGINEERING
Author(s): CHILAKA RANGA , GANESH MIRIYALA , NEELAM SRINIVASULU
Abstract: n this paper, the results finding out the hybrid structure of a new chaotic attractor. This new chaotic attractor is combination of Lorenz chaotic attractor and Chen’s attractor. This new chaotic attractor obtained by merging Lorenz and Chen’s attractors. This will give the applications of both Lorenz chaotic attractor and Chen’s attractor.
- Publication Date: 21-Apr-2013
- DOI: 10.15224/978-981-07-6184-4-54
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- Downloads: 0