More rain compensation results

To reduce the impact of rain-induced attenuation in the 20/30 GHz band, the attenuation at a specified signal frequency must be estimated and extrapolated forward in time on the basis of a noisy beacon measurement. Several studies have used model based procedures for solving this problem in statistical inference. Perhaps the most widely used model-based paradigm leads to the Kalman filter and its lineal variants. In this formulation, the dynamic features of the attenuation are represented by a state process (x(sub t)). The observation process (y(sub t)) is derived from beacon measurements. Some ideas relating to the signal processing problems related to uplink power control are presented. It is shown that some easily implemented algorithms hold promise for use in estimating rain induced fades. The algorithms were applied to actual data generated at the Virginia Polytechnic Institute and State University (VPI) test facility. Because only one such event was studied, it is not clear that the algorithms will have the same effectiveness when a wide range of events are studied

A non-autonomous stochastic discrete time system with uniform disturbances

The main objective of this article is to present Bayesian optimal control over a class of non-autonomous linear stochastic discrete time systems with disturbances belonging to a family of the one parameter uniform distributions. It is proved that the Bayes control for the Pareto priors is the solution of a linear system of algebraic equations. For the case that this linear system is singular, we apply optimization techniques to gain the Bayesian optimal control. These results are extended to generalized linear stochastic systems of difference equations and provide the Bayesian optimal control for the case where the coefficients of these type of systems are non-square matrices. The paper extends the results of the authors developed for system with disturbances belonging to the exponential family

Control of Systems Subject to Small Measurement Disturbances

When a controlled system is subject to external disturbances of large magnitude, the regulator often uses a mixed strategy, combining a feedforward link to neutralize the primary impact of the disturbance, and a feedback link to reduce the effect of any residual. If there is a possibility of error in measuring the disturbance, the problem becomes more complex. A sophisticated regulator might even try to “learn” the true value of the disturbance. Attempts to design such an intelligent regulator usually lead to intractable synthesis equations. This paper provides a simple alternative for the case in which the measurement of the disturbance is close to the true value. A study of a simple model of a solar-powered boiler shows that the performance of the proposed regulator is near that attainable by much more complicated controllers.</jats:p