This study deals with the problem of fiber-free optical communication systems—known as free space optics—using received signal strength identifier (RSSI) prediction analysis for hard switching of optical fiber-free link to base radio-frequency (RF) link and back. Adverse influences affecting the atmospheric transmission channel significantly impair optical communications, therefore attention was paid to the practical design, as well as to the implementation of the monitoring device that is used to record and process weather information along a transmission path. The article contains an analysis and methodology of the solution of the high availability of the optical link. Attention was paid to the technique of hard free space optics (FSO)/RF-switching with regard to the amount of received optical power detected and its relation to the quantities influencing the optical communication line. For this purpose, selected methods of machine learning were used, which serve to predict the received optical power. The process of analysis of prediction of received optical power is realized by regression models. The study presents the design of the optimal data input matrix model, which forms the basis for the training of the prediction models for estimating the received optical power.

One of the biggest challenges of communication networks is the video transmission in real time. It requires high demands on the available network capacity and transport mechanisms. Availability of smart mobile devices with batteries, which keep the terminal working for several hours, caused an increased interest in the research of the deployment of video transmission in wireless transmission systems. The presented paper deals with the transmission of video encoded with H.264/AVC (Advanced Video Coding) video coding standard through wireless local area network (WLAN) using the programming environment OPNET Modeller (OM). The test network studied in this work was prepared by combining real and simulated networks, which allows interesting possibilities when working with the OM tools. Such an approach to working with OM allows a detailed video streaming analysis, because the video output was noticeably not only in the form of statistics, but we can see the real impact of transmission failures. Using the OM simulation environment allows to design the transmission systems, which would be difficult to establish in laboratory conditions.

In this paper, we describe a problem of mitigating a multiple-access interference (MAI) and a channel disturbance in DS-CDMA technology. The receiver is based on a blind algorithm, which does not need any training sequence, or any information about the channel. Our simulations are oriented on a land mobile communications, where the channel is changing through the time. Proposed channel consists of three states. The comparison of effectiveness between the blind MOE algorithm and conventional detection using computer simulations is demonstrated and the experimental results of image transmission over 3-states channel using blind detection are presented.

In this paper we describe 2-stage blind detector, of which the second stage is based on the constant modulus algorithm (CMA). Simulations are oriented on MC-CDMA signals and the image transmission over 3-states channel enlarged with a complex AWGN noise. The channel model is assigned for Land mobile satellite communications.