A New Taxonomy for Symbiotic EM Sensors

It is clear that the EM spectrum is now rapidly reaching saturation, especially for frequencies below 10~GHz. Governments, who influence the regulatory authorities around the world, have resorted to auctioning the use of spectrum, in a sense to gauge the importance of a particular user. Billions of USD are being paid for modest bandwidths. The earth observation, astronomy and similar science driven communities cannot compete financially with such a pressure system, so this is where governments have to step in and assess /regulate the situation. It has been a pleasure to see a situation where the communications and broadcast communities have come together to formulate sharing of an important part of the spectrum (roughly, 50 MHz to 800 MHz) in an IEEE standard, IEEE802.22. This standard (known as the "TV White Space Network" (built on lower level standards) shows a way that fixed and mobile users can collaborate in geographically widespread regions, using cognitive radio and geographic databases of users. This White Space (WS) standard is well described in the literature and is not the major topic of this short paper. We wish to extend the idea of the WS concept to include the idea of EM sensors (such as Radar) adopting this approach to spectrum sharing, providing a quantum leap in access to spectrum. We postulate that networks of sensors, using the tools developed by the WS community, can replace and enhance our present set of EM sensors. We first define what Networks of Sensors entail (with some history), and then go on to define, based on a Taxonomy of Symbiosis defined by de Bary\cite{symb}, how these sensors and other users (especially communications) can co-exist. This new taxonomy is important for understanding, and should replace somewhat outdated terminologies from the radar world.Comment: 4 pages, 1 Figur

A Survey of Brain Inspired Technologies for Engineering

Cognitive engineering is a multi-disciplinary field and hence it is difficult to find a review article consolidating the leading developments in the field. The in-credible pace at which technology is advancing pushes the boundaries of what is achievable in cognitive engineering. There are also differing approaches to cognitive engineering brought about from the multi-disciplinary nature of the field and the vastness of possible applications. Thus research communities require more frequent reviews to keep up to date with the latest trends. In this paper we shall dis-cuss some of the approaches to cognitive engineering holistically to clarify the reasoning behind the different approaches and to highlight their strengths and weaknesses. We shall then show how developments from seemingly disjointed views could be integrated to achieve the same goal of creating cognitive machines. By reviewing the major contributions in the different fields and showing the potential for a combined approach, this work intends to assist the research community in devising more unified methods and techniques for developing cognitive machines