Impact of antenna choices on the reliability of mobile broadband transmission at millimetre - wave frequencies

This paper deals with the impact of several antenna chices on the radio transmission performance within a cellular Mobile Broaband System (MBS) currently under research in Europe. Several antenna types are considered, namely switchable-beam antennas and adaptive antennas employing a phased array approach.

Adaptive transceiver - antenna techniques for mobile broadband communications at millimetre - wave frequencies

This paper is concerned with the implementation of a Mobile Broadband System, currently under research in Europe. We present a low-complexity, adaptive transceiver/antenna approach where simple, linear, phased arrays are adjusted under a transmission quality measurement provided by a decision-feedback equalizer. Several simulation results are presented and discussed.

Impact of antenna choices on the reliability of mobile broadband transmission at mm-wave frequencies

This paper deals with the impact of several antenna choices on the radio transmission performance within a cellular Mobile Broaband System (MBS) currently under research in Europe. Several antenna types are considered, namely switchble-beam antennas and adaptive antennas employing a phased array approach.

Training multilayer perceptrons - an optimization perspective

Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large field of applications. In control and signal processing applications, MLPs are mainly used as nonlinear mapping approximators. The most common training algorithm used with MLPs is the error back-propagation (BP) alg. (1).

Training multilayer perceptrons for control systems applications - a comparison of different approaches

Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large field of applications. In control and signal processing applications, MLPs are mainly used as nonlinear mapping approximators. The most common training algorithm used with MLPs is the error back-propagation (BP) alg. (1).

Parallel implementation of a learning algorithm for multilayer perceptrons using transputers

In this paper the parallelization of a new learning algorithm for multilayer perceptrons, specifically targeted for nonlinear function approximation purposes, is discussed. Each major step of the algorithm is parallelized, a special emphasis being put in the most computationally intensive task, a least-squares solution of linear systems of equations.