Implementazione su fpga di un pre-distorsore digitale a banda larga per sistemi a microonde di backhaul

The development of next generation microwave technology for backhauling systems is driven by an increasing capacity demand. In order to provide higher data rates and throughputs over a point-to-point link, a cost-effective performance improvement is enabled by an enhanced energy-efficiency of the transmit power amplification stage, whereas a combination of spectrally efficient modulation formats and wider bandwidths is supported by amplifiers that fulfil strict constraints in terms of linearity. An optimal trade-off between these conflicting requirements can be achieved by resorting to flexible digital signal processing techniques at baseband. In such a scenario, the adaptive digital pre-distortion is a well-known linearization method, that comes up to be a potentially widely-used solution since it can be easily integrated into base stations. Its operation can effectively compensate for the inter-modulation distortion introduced by the power amplifier, keeping up with the frequency-dependent time-varying behaviour of the relative nonlinear characteristic. In particular, the impact of the memory effects become more relevant and their equalisation become more challenging as the input discrete signal feature a wider bandwidth and a faster envelope to pre-distort. This thesis project involves the research, design and simulation a pre-distorter implementation at RTL based on a novel polyphase architecture, which makes it capable of operating over very wideband signals at a sampling rate that complies with the actual available clock speed of current digital devices. The motivation behind this structure is to carry out a feasible pre-distortion for the multi-band spectrally efficient complex signals carrying multiple channels that are going to be transmitted in near future high capacity and reliability microwave backhaul links.

A Reliable Downscaling of ECG Signals for the Detection of T wave Heterogeneity Features

In cardiovascular disease the definition and the detection of the ECG parameters related to repolarization dynamics in post MI patients is still a crucial unmet need. In addition, the use of a 3D sensor in the implantable medical devices would be a crucial mean in the assessment or prediction of Heart Failure status, but the inclusion of such feature is limited by hardware and firmware constraints. The aim of this thesis is the definition of a reliable surrogate of the 500 Hz ECG signal to reach the aforementioned objective. To evaluate the worsening of reliability due to sampling frequency reduction on delineation performance, the signals have been consecutively down sampled by a factor 2, 4, 8 thus obtaining the ECG signals sampled at 250, 125 and 62.5 Hz, respectively. The final goal is the feasibility assessment of the detection of the fiducial points in order to translate those parameters into meaningful clinical parameter for Heart Failure prediction, such as T waves intervals heterogeneity and variability of areas under T waves. An experimental setting for data collection on healthy volunteers has been set up at the Bakken Research Center in Maastricht. A 16 – channel ambulatory system, provided by TMSI, has recorded the standard 12 – Leads ECG, two 3D accelerometers and a respiration sensor. The collection platform has been set up by the TMSI property software Polybench, the data analysis of such signals has been performed with Matlab. The main results of this study show that the 125 Hz sampling rate has demonstrated to be a good candidate for a reliable detection of fiducial points. T wave intervals proved to be consistently stable, even at 62.5 Hz. Further studies would be needed to provide a better comparison between sampling at 250 Hz and 125 Hz for areas under the T waves.