The ubiquitous signal processing : Applications to communications, spectral analysis and array processing
Abstract: This dissertation is concerned with statistical signal processing and its applications. The thesis consists of three parts: I) applications to wireless communications, II) applications to spectral analysis and III) applications to array processing.In part I, an iterative receiver for interference suppression in a system using orthogonal space-time block codes (STBC) is derived. An extension of STBC to frequency-selective fading is developed and receiver structures are devised. Furthermore, the orthogonal frequency division multiplexing (OFDM) technique is discussed. New algorithms for synchronization and channel estimation in an OFDM system are proposed and the optimal design of training sequences in an OFDM system with transmit diversity is discussed.In part II, computationally efficient implementations of nonparametric spectral estimators are derived. A new high-resolution nonparametric spectral estimation method is devised and analyzed. Furthermore, a novel spectral analysis method for both one and two-dimensional discontinuously sampled data is developed.In part III, a new high-resolution finding technique is developed for the case when the observed data contain missing samples. Furthermore, Cramer-Rao bounds for direction estimation are examined under deterministic and stochastic data models, respectively. Finally, an algorithm for blind source separation is discussed and analyzed.
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