Miroslav Vozňák

Exploiting hybrid time switching-based and power splitting-based relaying protocol in wireless powered communication networks with outdated channel state information

ABSTRACT Wireless powered communication networks (WPCNs) have attracted much research interest in fifth generation (5G) wireless networks. With the help of WPCN, the reliability and battery life of wireless low-power devices can be enhanced. In this paper, we investigate throughput and ergodic capacity in WPCN-assisted amplify-and-forward relaying systems considering two transmission modes, including delay-tolerant and delay-limited. More importantly, we propose energy harvesting protocol so-called hybrid time switching-based and power splitting-based relaying (HTPSR) protocol in order to achieve optimal throughput. In particular, both time switching-based and power splitting-based coefficients in this scheme are considered. Unlike most previous works, we further focus on the impact of outdated channel state information (CSI) in WPCN. In order to evaluate information processing efficiency, the performance can be substantially improved by optimizing harvesting time and power coefficients of the received signal at the relay node for energy and information extraction. Thanks to Monte Carlo simulations, it is confirmed that the system performance is more sensitive to CSI estimation error, noise variance and signal-to-noise ratio which enable us in reasonable computations of HTPSR to obtain QoS requirement.

Energy harvesting over Rician fading channel: A performance analysis for half-duplex bidirectional sensor networks under hardware impairments

In this paper, a rigorous analysis of the performance of time-switching energy harvesting strategy that is applied for a half-duplex bidirectional wireless sensor network with intermediate relay over a Rician fading channel is presented to provide the exact-form expressions of the outage probability, achievable throughput and the symbol-error-rate (SER) of the system under the hardware impairment condition. Using the proposed probabilistic models for wireless channels between mobile nodes as well as for the hardware noises, we derive the outage probability of the system, and then the throughput and SER can be obtained as a result. Both exact analysis and asymptotic analysis at high signal-power-to-noise-ratio regime are provided. Monte Carlo simulation is also conducted to verify the analysis. This work confirms the effectiveness of energy harvesting applied in wireless sensor networks over a Rician fading channel, and can provide an insightful understanding about the effect of various parameters on the system performance.

Bi-layers Red-emitting Sr 2 Si 5 N 8 :Eu 2+ Phosphor and Yellow-emitting YAG:Ce Phosphor: A New Approach for Improving the Color Rendering Index of the Remote Phosphor Packaging WLEDs

Due to optimal advances such as chromatic performance, durability, low power consumption, high efficiency, long-lifetime, and excellent environmental friendliness, white LEDs (WLEDs) are widely used in vehicle front lighting, backlighting, decorative lighting, street lighting, and even general lighting. In this paper, the remote packaging WLEDs (RP-WLEDs) with bi-layer red-emitting Sr2Si5N8: Eu2+ and yellow-emitting YAG:Ce phosphor was proposed and investigated. The simulation results based on the MATLAB software and the commercial software Light Tools indicated that the color rendering index (CRI) of bi-layer phosphor RP-WLEDs had a significant increase. The CRI had a considerable increase from 72 to 94. In conclusion, the results showed that bi-layer red-emitting Sr2Si5N8:Eu2+ and yellow-emitting YAG:Ce phosphor could be a prospective approach for manufacturing RP-WLEDs with enhanced optical properties.

Investigation of Sonar Stabilisation Method for Improved Seafloor Image Quality

Constant monitoring of sea floor in harbours is an essential part of economy development of every sea country. Exact estimation of the sea floor relief parameters is very important not only for port development but also for scientists. Sonar image corrections are constantly made with a high margin of error, using GIS. New correction methods are developed. They include: mechanical correction of the cables of the side-scan sonar, programmable correction of the ship navigation and steering system, other software tolls with developed correction and control algorithms. Most commonly sea floor images are made using side scan sonar. It is used for rapid seafloor imaging. The quality of the captured images is strongly influenced by the sonar towing consistency. Even small sonar disturbances caused by the vessels’ towing motion can affect the quality of the images. Therefore, to reduce the influence of the ship motion new methods are being developed. In some cases heave motion compensation can prove to be effective. In this paper an efficient heave motion detecting system was proposed and briefly analysed. Sonar and the ship motion were taken into account during the development and testing of the heave motion compensation system prototype.

Searching for Dependences within the System of Measuring Stations by Using Symbolic Regression

This article deals with searching for dependences within the System of Measuring Stations.Weather measuring stations represent one of the most important data sources. The same could be said about stations that measure the composition of air and the level of pollutants. Knowledge of the current state of air quality resulting from the measured values is essential for citizens, especially in areas affected by heavy industry or dense traffic. Computation of such air quality indicators depends on values obtained from measuring stations which are more or less reliable. They can have failures or they can measure just a part of the required values. In general, searching for dependences represents a complex and non-linear problem that can be effectively solved by some class of evolutionary algorithms. This article describes a method that helps us to predict the levels of air quality in the case of station failure or data loss. The model is constructed by the symbolic regression with usage of the principles of genetic algorithms. The level of air quality of a given station is predicted with respect to a set of surrounding stations. All experiments were focused on real data obtained from the system of stations located in the Czech republic.