Abstracts Communications and the Arts

Efficient compressed sensing for wireless communication systems

by Theofanis Xifilidis

The currently deployed wireless communication systems have been inextricably linked to the Big Data deluge conveying an explosive growth of transmitted and processed heterogeneous data that demand a low complexity and resource efficient information extraction. The above necessity constitutes the main motivation for a thorough understanding of advantages and limitations that govern the communication system performance analysis and design. As with other scientific areas, the performance evaluation of modern communication systems implies the careful formulation of an optimization problem with relevant objective and constraints that best model the practical requirements of the specific problem at hand. To that end, a priori information for the specific problem is proven to contribute to the acquiring of an optimal solution. CS comprises a set of optimization tools that effectively convert a problem of high intractability i.e. combinatorial nature to a reduced dimensionality problem with low computational and implementation complexity. Thus, CS has already emigrated to wireless communication system performance evaluation due to the essential fact that the convenient property of structure as additional information is also verified in the wireless communication field. Efficient algorithms that jointly consider physical limitations of the wireless channel, in terms of the distortion it induces to the transmitted signal, are already present and rapidly evolving. This thesis constitutes the integration of CS and information theory in statistical modeling of the wireless channel from the essential statistical independence assumption point of view. The random distorting mechanisms of the wireless channel are accounted for thus additive noise and diverse fading. Moreover, the concept of resource efficiency adapts to this thesis in terms of information accessibility in a large scale deployed network. The above statistical assumption provides useful performance insights which extent in terms of comparison to the more practical correlation case with respect to additive noise and fading distributions. Finally, the merit of the results derived in this thesis is verified by stating feasible application of these results in terms of CS theory and principles to the current Fifth Generation communication systems. Through this relation, limitations of the current communication system generation can further boost performance and provide guidelines in terms of practical application specific considerations serving as motive to designing improved future communication systems.The currently deployed wireless communication systems have been inextricably linked to the Big Data deluge conveying an explosive growth of transmitted and processed heterogeneous data that demand a low complexity and resource efficient information extraction. The above necessity constitutes the main motivation for a thorough understanding of advantages and limitations that govern the communication system performance analysis and design. As with other scientific areas, the…