Ravi kumar

Work place: Department of Electronics and Communication Engineering, Jaypee University of Engineering and Technology, Guna, India

E-mail: ravi.kumar6@gmail.com


Research Interests: Engineering


Ravi Kumar completed his B.E. in Electronics & Communication Engineering from RGPV, Bhopal in 2001. After Graduation, he served as Centre Manager in Pentasoft Technologies Ltd., Bhopal. In 2004, he completed his M.Tech. in Electronics & Communication with specialization in Microwave Engineering from MITS, Gwalior. After  completing  his post-graduation, he joined MITS as a Lecturer and worked there for one year. At present he has been working as Sr.Lecturer in Jaypee University of Engineering & Technology since 2005 and pursuing his Ph.D. from same university in Adaptive Smart antenna array systems. He is member of IEEE & IETE and published several research papers in Journals and conferences at International and national level.

Author Articles
MIMO Capacity Analysis Using Adaptive Semi Blind Channel Estimation with Modified Precoder and Decoder for Time Varying Spatial Channel

By Ravi kumar Rajiv Saxena

DOI: https://doi.org/10.5815/ijitcs.2012.10.01, Pub. Date: 8 Sep. 2012

Multiple Input Multiple Output(MIMO) has been in much importance in recent past because of high capacity gain over a single antenna system. In this article, analysis over the capacity of the MIMO channel systems with spatial channel with modified precoder and decoder has been considered when the channel state information (CSI) is considered partial. Due to delay in acquiring transmitted information at the receiver end, the time selective fading wireless channel often induces incomplete or partial CSI. The dynamic CSI model has also been implemented consisting channel mean and covariance which leads to extracting of channel estimates and error covariance which then further applied with the modified precoder and decoder utilizing both the parameters indicating the CSI quality since these are the functions of temporal correlation factor, and based on this, the model covers data from perfect to statistical CSI, either partially or fully blind. It is found that in case of partial and imperfect CSI, the capacity depends on the statistical properties of the error in the CSI which has been manipulated according to the precoder and decoder conditions.
Based on the knowledge of statistical distribution of the deviations in CSI knowledge, a new approach which maximizes the capacity of spatial channel model with modified precoder and decoder has been tried. The interference then interactively reduced by employing the iterative channel estimation and data detection approach, where by utilizing the detected symbols from the previous iteration, multiuser/MIMO channel estimation and symbol detection is improved.

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