Martin Mudroch

Mitigation of time-spatial influence in free-space optical networks utilizing route diversity

New communication systems are emerging with growing demand on the data traffic. Fiber optics allow us to transfer data of rates higher than hundreds gigabits per second. These systems are usually used for backbone networks, although using of these systems is appearing in last mile connections. Wireless communication systems are still more and more popular owing to fast and cheaper deployment contrary to wire or fiber communication systems. On the other hand, wireless communication systems including free-space optics (FSO) are affected by weather conditions. In order to mitigate these effects, several mitigation techniques were investigated. For instance spatial diversity using more than one transmitter or receiver, auto-tracking of an optical beam, wavelength diversity utilizing radio band links as a backup etc. FSO links may be used in FSO networks to connect several building of a corporation, hospital or university campus. In case of proper network topology, route diversity can contribute to availability enhancement. In this paper, mitigation technique based on the route diversity is presented. Results are compared with hybrid FSO link.

Multipath fading measurement and prediction on 10 GHz fixed terrestrial link

Multipath propagation events are observed on the 50 km long fixed terrestrial link operating in 10 GHz band. Several receivers are located in different heights. Two year statistics of attenuation and enhancement due to multipath are obtained from measured signal fluctuations in different heights. The results are compared with cumulative distributions predicted by the two methods — the ITU-R method and the VUS method which is currently used for the planning of radio-relay links in the Czech Republic. The predicted distributions of attenuation provide slightly higher exceedance probabilities than measured.

Classification and prediction of lower troposphere layers influence on RF propagation using artificial neural networks

This paper describes the basic steps of a novel approach to weather classification by remote and local atmosphere sensing. Atmospheric data on the troposphere are gathered by 10 GHz radio links and a number of meteorological sensors. Classification is performed by artificial neural networks (ANN) and is crucial for further processing, because of the different RF propagation influences under a variety of weather conditions. Reasons for using ANN compared to other means of classification are discussed. Differences in the size and number of hidden layers of back-propagation networks used are discussed. Different learning sets of measured data and their construction are also evaluated.

An Experimental Study of the Lowest Troposphere Layers at 10 GHz - First Results

In this paper an extensive innovative experiment for combined, both local and remote sensing of the troposphere is introduced. The experiment is based on a unique set of mutually linked, time-space dependent, synchronized radio-electrical and radio-meteorological measurements. The first results for first two months of operation are presented and discussed as well.

Atmosphere analysis and measurements via free-space optical network

Free-space optical link is an alternative instrument to transmission of information in data rates up to tenths of gigabits per second. Although evolution of this technology has been proceeded for several years, many factors affecting propagation of optical beam still have not been suitable minimized. Therefore several mitigation techniques are tested nowadays. In this paper, influences of atmosphere and rain are discussed with respect to particular diversity techniques. First results from a measurement campaign are introduced.