Capacity Approximations for a Deterministic MIMO Channel

In this paper, we derive closed form approximations for the capacity of a point-to-point, deterministic Gaussian MIMO communication channel. We focus on the behavior of the inverse eigenvalues of the Gram matrix associated with the gain matrix of the MIMO channel, by considering small variance and large power assumptions. We revisit the concept of deterministic MIMO capacity by pointing out that, under transmitter power constraint, the optimal transmit covariance matrix is not necessarily diagonal. We discuss the water filling algorithm for obtaining the optimal eigenvalues of the transmitter covariance matrix, and the water fill level in conjunction with the Karush-Kuhn-Tucker optimality conditions. We revise the Telatar conjecture for the capacity of a non-ergodic channel. We also provide deterministic examples and numerical simulations of the capacity, which are discussed in terms of our mathematical framework

Nanoparticles as Smart Treatment-delivery Systems in Plants: Assessment of Different Techniques of Microscopy for their Visualization in Plant Tissues

9 pages, 5 figures.-- PMID: 17998213 [PubMed].-- Online version available on Nov 11, 2007.[Background and Aims] The great potential of using nanodevices as delivery systems to specific targets in living organisms was first explored for medical uses. In plants, the same principles can be applied for a broad range of uses, in particular to tackle infections. Nanoparticles tagged to agrochemicals or other substances could reduce the damage to other plant tissues and the amount of chemicals released into the environment. To explore the benefits of applying nanotechnology to agriculture, the first stage is to work out the correct penetration and transport of the nanoparticles into plants. This research is aimed (a) to put forward a number of tools for the detection and analysis of core-shell magnetic nanoparticles introduced into plants and (b) to assess the use of such magnetic nanoparticles for their concentration in selected plant tissues by magnetic field gradients.[Methods] Cucurbita pepo: plants were cultivated in vitro and treated with carbon-coated Fe nanoparticles. Different microscopy techniques were used for the detection and analysis of these magnetic nanoparticles, ranging from conventional light microscopy to confocal and electron microscopy.[Key Results] Penetration and translocation of magnetic nanoparticles in whole living plants and into plant cells were determined. The magnetic character allowed nanoparticles to be positioned in the desired plant tissue by applying a magnetic field gradient there; also the graphitic shell made good visualization possible using different microscopy techniques.[Conclusions] The results open a wide range of possibilities for using magnetic nanoparticles in general plant research and agronomy. The nanoparticles can be charged with different substances, introduced within the plants and, if necessary, concentrated into localized areas by using magnets. Also simple or more complex microscopical techniques can be used in localization studies.A. Pérez de Luque acknowledges a post-doctoral contract at the IAS-CSIC funded by the programme ‘Ramón y Cajal’ of the Spanish Ministry of Education and Science. M. J. Coronado is funded by the programme ‘Juan de la Cierva’ of the Spanish Ministry of Education and Science. P. González-Melendi is funded by the programme ‘Ramón y Cajal’ of the Spanish Ministry of Education and Science. This research was supported by the project NanoAgro-200540F0041 funded by CSIC (Proyectos Intramurales de Frontera) and by the project NAN2004-09270-C03-03 funded by the Spanish Strategic Action on Nanoscience and Nanotechnology of the Spanish Ministry of Education and Science.Peer reviewe

Optimal measurement locations for parameter estimation of non linear distributed parameter systems

A sensor placement approach for the purpose of accurately estimating unknown parameters of a distributed parameter system is discussed. The idea is to convert the sensor location problem to a classical experimental design. The technique consists of analysing the extrema values of the sensitivity coefficients derived from the system and their corresponding spatial positions. This information is used to formulate an efficient computational optimum experiment design on discrete domains. The scheme studied is verified by a numerical example regarding the chemical reaction in a tubular reactor for two possible scenarios; stable and unstable operation conditions. The resulting approach is easy to implement and good estimates for the parameters of the system are obtained. This study shows that the measurement location plays an essential role in the parameter estimation procedure