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Estimation for Wireless Communications: MIMO/OFDM Cellular and Sensor Networks

Estimation for Wireless Communications: MIMO/OFDM Cellular and Sensor Networks. Instructor: Prof. Aditya K. Jagannatham, Department of Electrical Engineering, IIT Kanpur. Estimation theory provides a wide variety of tools and techniques which form the basis for several key applications in modern wireless communications and signal processing. Various signal processing procedures in communication systems such as channel estimation, equalization, synchronization etc., which are also employed in MIMO-OFDM based 3G/4G wireless systems, are based on fundamental concepts in estimation theory. Further, recent research developments in areas such as wireless sensor networks also employ several tools from estimation theory towards distributed parameter estimation etc. Therefore, principles of estimation are naturally of a significant interest in research and industry. A clear grasp of the basic principles of estimation can significantly enhance understanding by providing deeper insights into various techniques in signal processing and communication. Beginning with a brief overview of the basic concepts of maximum likelihood (ML) and Least Squares Estimation (LS), this course will comprehensively cover several applications of estimation theory in wireless communications such as channel estimation, equalization, MIMO, OFDM. Further, we will also cover Bayesian Estimation, MMSE, LMMSE and illustrate applications in wireless sensor networks and other allied applications such as Radar. (from nptel.ac.in)

This lecture covers the following topics: 1. Derivation of covariance of noise vector in the wireless system model. 2. Discussion on properties (i.e. mean and variance) of the ML estimate of the channel. 3. Establishment of unbiasedness of the channel estimate and relation between channel variance and pilot energy.

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