Analysis of distortion in pulse modulation converters for switching radio frequency power amplifiers

High-efficiency linear radio frequency (RF) power amplifiers are needed for today’s wireless communication systems. Switch mode techniques have the potential for high efficiency but require a pulse drive signal. The generation of pulse width modulated signals and pulse position modulated signals by sigma delta modulators can introduce unwanted spectral components. Third order and image components are the dominant distortions generated in the pulse position modulation circuit. The authors identify the cause of distortion and mathematically quantify its amplitude and frequency. In a single carrier environment, an increase in offset frequency increases the unwanted spectral components. Calculations, simulations and measurements show that offsets less than 1% of the carrier frequency are required to keep unwanted components 40 dB below the signal level. Simulations and measurements show that the effect on a multichannel orthogonal frequency division multiplexing (OFDM) system is less detrimental. Nonetheless, unacceptable noise increases of up to 20 dB are observed in odd harmonic channels when the transmission is not centred on the nominal carrier frequency

A framework for safer driving in Mauritius

According to the National Transport Authority (NTA), there were 493,081 registered vehicles in Mauritius in April 2016, which represents a 1.4% annual increase compared to 2015. Despite the sensitization campaigns and the series of measures setup by the Minister of Public Infrastructure and Land Transport, the number of road accidents continues to rise. The three main elements that contribute to accidents are: road infrastructure, vehicle and driver. The driver has the highest contribution in collisions. If the driver is given the right information (e.g. driving behaviour, accident-prone areas and vehicle status) at the right time, he/she can make better driving decisions and react promptly to critical situations. This paper proposes a framework for safer driving in Mauritius that uses an on-board car diagnostic module (OBDII) to collect data such as vehicle average speed, engine revolution and acceleration. This module relays the data to a cloud environment where an adaptive algorithm analyses the data and predicts driver behaviour in real-time. Based on driving behaviour, mobile alerts can be sent to the driver in the form of messages, voice commands or beeps. A survey was also carried out to evaluate the acceptance rate of such a framework by people of different age groups in Mauritius

Applicability of Federated Learning for Securing Critical Energy Infrastructures

Energy grids are becoming more intelligent due to the use of a vast array of technologies, including the Internet of Things and Intelligent Systems. These Critical Energy Infrastructures, which are essentially cyber-physical systems, are particularly vulnerable to cyber threats. Machine Learning (ML) techniques have been increasingly used in security applications, and the energy domain is no exception. One approach, in particular, Federated Learning (FL), employs a distributed architecture and has potential in security applications, as it counters the issue of having a centralized data warehouse. In this work, a review of FL and its applications in security and privacy are presented. Moreover, a demonstration case involving a simulated model of FL for enhancing the security of systems is implemented and discussed. This demonstration case has provided added insight into potential issues and challenges as well as mitigation strategies