Application of basis selection algorithms to wireless communications systems

点击翻译按钮获取中文摘要

Efficient signal representations require efficient signal decomposition algorithms. The problem of basis selection for signal decomposition consists of determining a small subset of vectors chosen from a large redundant set of vectors to match a given data. The basis selection algorithms are generally treated as a part of the specific application for which they are used. These applications include time/frequency representations of speech coding, spectral estimation, video coding and channel estimation. Finding an optimal solution using an exhaustive search is infeasible, suboptimal methods that require lower computational complexity have been proposed. Among these suboptimum techniques we have focused on sequential basis selection (SBS) in particular matching pursuit algorithms which have lower levels of computational complexity than the conventional least squares methods and work well especially in applications with sparsity properties.   The objective of our proposed research is to improve the performance of these SBS algorithms and extent their applications to more complex wireless applications. We are working on optimizing the associated dictionary structures. This corresponds to a training sequence design for channel estimation, array structure design for angle of arrival detection and code structure design for multi-user detection. By optimizing the dictionary, the requirement of a combinatorial search in the SBS algorithm is eliminated and the  complexity can be further reduced. Extending the wireless applications which utilize SBS algorithms will be done for multiple input multiple output (MIMO) systems, and for radiolocalization systems. MIMO systems are of interest due to their ability to provide substantial gains in capacity and quality. Similarly, accurately radiolocating a terminal is essential for efficient network operation of modern wireless systems. Many important results can be obtained by applying the overcomplete signal expansions to such systems due to the low complexities of the SBS algorithms. In addition to estimation of MIMO channels and geolocation, other potential applications we will investigate are higher dimensional angle of arrival estimation, and decoder design in channel coding systems.