Abstract: Indoor positioning on a Wi-Fi network belongs to a class of tasks in which the dependence of output characteristics on input variables is influenced by many parameters and external factors. When solving such problems, it is necessary to take into account that in determining the location, it is of significant interest not only to determine the static coordinates of an object, but also to predict the vector of its movements. In the case where the location of an object is determined only by the level of signal power received from several access points on a Wi-Fi network, the use of signal attenuation models that take into account the conditions of propagation of radio waves indoors is difficult due to the need for reliable information about the material of ceilings, floors and ceilings, the presence of fixed and mobile shading objects, etc. Since the electromagnetic environment inside the room varies depending on many factors, the above-mentioned models have to be adjusted to these changes. Since finding patterns in a large amount of data requires non-standard algorithms, artificial neural networks can be used to solve the positioning problem. It is important to choose a neural network architecture that can take into account changes in the signal strength received by a mobile device from Wi-Fi access points. Before training a neural network, statistical data is preprocessed. For example, abnormal cases are excluded from the machine learning dataset when the device detects a signal from less than three access points at one measuring point.
As a result of the analysis of statistical data, it was found that the same distance between the measuring points leads to the fact that the neural network incorrectly determines the location of the object. The paper shows that in order to increase the accuracy of positioning the location in conditions of complex radio placement, when compiling radio maps, it is necessary to determine the optimal varying distances between measuring points. The conducted experimental studies, taking into account the proposed approach to optimizing the distances between measuring points, prove that the accuracy of location determination in the vast majority of measuring points reaches 100%.

Abstract: One of the topical areas of the digital economy is the development of services based on the use of systems for local positioning of objects. The article presents the results of analytical modeling of a positioning system built on the equipment of the IEEE 802.15.4 standard. The purpose of this study is to evaluate the efficiency of data transmission in a ZigBee network. As a modeling tool, the mathematical apparatus of queuing networks (CeMO) was selected, which has proven its effectiveness for calculating the characteristics of various infocommunication systems. The method of analysis of average values was chosen by the authors to assess the quality of service indicators due to its computational simplicity and the adequacy of the results obtained. The authors have developed a structural diagram of the investigated positioning system. On the basis of the network architecture, a conceptual, algorithmic and software model in the form of a closed homogeneous queuing network has been developed and its characteristics have been calculated. The parameters obtained as a result of modeling make it possible to evaluate and analyze the quality of service indicators in the telecommunications segment of the local positioning system under study, such as latency, performance, network load factor and the probability of losses, which can be used for efficient traffic management in the telecommunications segment of the geolocation system based on IEEE 802.15.4 standard.

Abstract: The article presents the results of analytical modeling of mobile communication systems 4G. The purpose of this study is to evaluate QoS performance in an LTE network channel. As a simulation tool, the mathematical apparatus of queuing networks (SEMO) was chosen, which proved its effectiveness for calculating the characteristics of infocommunication systems of various purposes and of any dimension. The author examined various research methods, further on the basis of the evolutionary system architecture of LTE, a conceptual, algorithmic and programming model was developed in the form of a closed homogeneous SemOI and its characteristics were calculated. The mean value analysis method was adapted to obtain network quality parameters with LTE technology. During the simulation, the probabilistic-temporal characteristics of the service process in the fourth-generation mobile communication systems were obtained: the transmission delay and the network capacity for a different number of active users, represented in the form of dependency curves from the input load. The results can be used both for designing new ones and for efficient traffic management in existing mobile networks.