Abstract

Our research program is concerned with the development of an information theory of classical electromagnetic fields with applications to wireless communications, remote sensing, and radar. In the present work, emphasis is given to the derivation of upper bounds for the Shannon information capacity of a wireless communication channel formed by a rather general receiving antenna and a transmitting antenna whose support is assumed to be contained within a mathematical spherical volume of a given radius. Due to reciprocity the results also apply as fundamental bounds for the information capacity of a wave sensor of a given size, be it an antenna, the eye, or any wave field-measuring device. This work includes numerical results illustrating the derived theory. A discussion of applications of the derived theory and numerical results to wavefield imaging, e.g., number of degrees of freedom of the data, and classes of recorverable objects profiles, using near or far electromagnetic fields, is also given. Specifically, this work has applications to MIMO wireless communications systems, MIMO radars, in determining resolution limits of sensing systems such as synthetic aperture radar and other imaging systems and it also clarifies the possibility of super-resolution [1] in certain situations. More generally, the developments are derived from the first principles' point of view provided by the classical electromagnetic theoretic framework, and are therefore fundamental for both analysis and design of a variety of wireless communications, remote sensing and radar systems.

Notes

Poster presented at the 2006 Thrust R2A Multi-View Tomographic Methods Conference

Keywords

Electromagnetic Information Theory, information theory, wireless communications, MIMO

Subject Categories

Wireless communication systems

Disciplines

Engineering

Publisher

Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS)

Publication Date

2006

Rights Holder

Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS)

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