In the past it was usual to exert a huge effort in the design, simulation, and the real time implementation of the complicated electronic and communication systems, like GNSS receivers. The complexity of the system algorithms combined with the complexity of the available tools created a system that is difficult to track down for debugging or for redesign. So, the simulation and educational tools was different from the prototyping tools. In this paper the parallel search acquisition phase of a GPS receiver was simulated and implemented on FPGA using the same platform and through a graphical programming language. So this paper introduces the fruit of integrating the prototyping tools with the simulation tools as a single platform through which the complicated electronic systems can be simulated and prototyped.
This paper presents a baseband model and an enhanced implementation of the wireless full duplex analog method introduced by .Unlike usual methods based on hardware and software self- interference cancelation, the proposed design relies on FSK modulation. The principle is when the transmitter of a local end is sending data by modulating the carrier with the appropriate frequency deviation, its own receiver is checking if the remote transmitter is using the opposite deviation. Instead of architectures often used by both non-coherent and coherent receivers that require one filter (matched filter for coherent detection) for each frequency deviation, our design uses one mixer and one single integrator-decimator filter. We test our design using Universal Software Radio Peripheral as radio frequency front end and computer that implements the signal processing methods under free and open source software. We validate our solution experimentally and we show that in-band full duplex is feasible and synthesizable for wireless communications.
One of the basic parameters which describes road traffic is Annual Average Daily Traffic (AADT). Its accurate determination is possible only on the basis of data from the continuous measurement of traffic. However, such data for most road sections is unavailable, so AADT must be determined on the basis of short periods of random measurements. This article presents different methods of estimating AADT on the basis of daily traffic (VOL), and includes the traditional Factor Approach, developed Regression Models and Artificial Neural Network models. As explanatory variables, quantitative variables (VOL and the share of heavy vehicles) as well as qualitative variables (day of the week, month, level of AADT, the cross-section, road class, nature of the area, spatial linking, region of Poland and the nature of traffic patterns) were used. Based on comparisons of the presented methods, the Factor Approach was identified as the most useful.