Single-carrier frequency domain equalisation for hammerstein communication systems using complex-valued neural networks

Single-carrier (SC) block transmission with frequency-domain equalisation (FDE) offers a viable transmission technology for combating the adverse effects of long dispersive channels encountered in high-rate broadband wireless communication systems. However, for high bandwidthefficiency and high power-efficiency systems, the channel can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. For such nonlinear Hammerstein channels, the standard SC-FDE scheme no longer works. This paper advocates a complex-valued (CV) B-spline neural network based nonlinear SC-FDE scheme for Hammerstein channels. Specifically, We model the nonlinear HPA, which represents the CV static nonlinearity of the Hammerstein channel, by a CV B-spline neural network, and we develop two efficient alternating least squares schemes for estimating the parameters of the Hammerstein channel, including both the channel impulse response coefficients and the parameters of the CV B-spline model. We also use another CV B-spline neural network to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard least squares algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Equalisation of the SC Hammerstein channel can then be accomplished by the usual one-tap linear equalisation in frequency domain as well as the inverse B-spline neural network model obtained in time domain. Extensive simulation results are included to demonstrate the effectiveness of our nonlinear SC-FDE scheme for Hammerstein channels.

The science case for an orbital mission to Uranus: Exploring the origins and evolution of ice giant planets

Giant planets helped to shape the conditions we see in the Solar System today and they account for more than 99% of the mass of the Sun’s planetary system. They can be subdivided into the Ice Giants (Uranus and Neptune) and the Gas Giants (Jupiter and Saturn), which differ from each other in a number of fundamental ways. Uranus, in particular is the most challenging to our understanding of planetary formation and evolution, with its large obliquity, low self-luminosity, highly asymmetrical internal field, and puzzling internal structure. Uranus also has a rich planetary system consisting of a system of inner natural satellites and complex ring system, five major natural icy satellites, a system of irregular moons with varied dynamical histories, and a highly asymmetrical magnetosphere. Voyager 2 is the only spacecraft to have explored Uranus, with a flyby in 1986, and no mission is currently planned to this enigmatic system. However, a mission to the uranian system would open a new window on the origin and evolution of the Solar System and would provide crucial information on a wide variety of physicochemical processes in our Solar System. These have clear implications for understanding exoplanetary systems. In this paper we describe the science case for an orbital mission to Uranus with an atmospheric entry probe to sample the composition and atmospheric physics in Uranus’ atmosphere. The characteristics of such an orbiter and a strawman scientific payload are described and we discuss the technical challenges for such a mission. This paper is based on a white paper submitted to the European Space Agency’s call for science themes for its large-class mission programme in 2013.

Regulation of early steps of GPVI signal transduction by phosphatases: a systems biology approach

We present a data-driven mathematical model of a key initiating step in platelet activation, a central process in the prevention of bleeding following Injury. In vascular disease, this process is activated inappropriately and causes thrombosis, heart attacks and stroke. The collagen receptor GPVI is the primary trigger for platelet activation at sites of injury. Understanding the complex molecular mechanisms initiated by this receptor is important for development of more effective antithrombotic medicines. In this work we developed a series of nonlinear ordinary differential equation models that are direct representations of biological hypotheses surrounding the initial steps in GPVI-stimulated signal transduction. At each stage model simulations were compared to our own quantitative, high-temporal experimental data that guides further experimental design, data collection and model refinement. Much is known about the linear forward reactions within platelet signalling pathways but knowledge of the roles of putative reverse reactions are poorly understood. An initial model, that includes a simple constitutively active phosphatase, was unable to explain experimental data. Model revisions, incorporating a complex pathway of interactions (and specifically the phosphatase TULA-2), provided a good description of the experimental data both based on observations of phosphorylation in samples from one donor and in those of a wider population. Our model was used to investigate the levels of proteins involved in regulating the pathway and the effect of low GPVI levels that have been associated with disease. Results indicate a clear separation in healthy and GPVI deficient states in respect of the signalling cascade dynamics associated with Syk tyrosine phosphorylation and activation. Our approach reveals the central importance of this negative feedback pathway that results in the temporal regulation of a specific class of protein tyrosine phosphatases in controlling the rate, and therefore extent, of GPVI-stimulated platelet activation.