Перегляд Кафедра інфокомунікаційної інженерії (ІКІ) за Автор "Ageyev, D."
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Результатів на сторінку
- ДокументLTE EPS Network with Self-Similar Traffic Modeling for Performance Analysis(KHARKIV NATIONAL UNIVERSITY OF RADIO ELECTRONICS, 2015) Ageyev, D.; Nameer, Q.An important task in parametric synthesis of telecommunications network such as EPS network is to de- termine QoS parameters when traffic processed on EPS net- work nodes. In this conference paper, presented mathemati- cal models for the calculation of QoS parameters such as delay and loss probability taking into account properties of self-similar traffic. This modeling based on model P/P/1 with Pareto distribution function for between packet intervals and processing time for case then intervals between packets and the duration of processing on servers are limited. Proposed model compared with model with log-normal and Weibull distribution of packet processing time and M/M/1 model.
- ДокументLTE RAN and Services Multi-Period Planning(KHARKIV NATIONAL UNIVERSITY OF RADIO ELECTRONICS, 2015) Ageyev, D.; Ali Al-AnsariThis paper proposes an optimization model for the LTE RAN network planning that aimed to accounting of ser-vices multi-period planning. The analysis of experiments results showed that formulation of the problem, which is shown in paper and presented as a problem of MILP, allows to obtain the correct solutions from the practical point of view. Comparison of the result showed that usage of multi- period network and services planning increase the profit margin to 10% more than the proposed by us previously method.
- ДокументRealization of Resource Blocks Allocation in LTE Downlink in the Form of Nonlinear Optimization(2016) Aymen Al-Dulaimi; Mohammed Al-Dulaimi; Ageyev, D.In this paper proposed realization of resource blocks allocation in LTE downlink in the form of nonlinear optimization. In using improved model it is possible to avoid the control variables Boolean nature, which has a positive impact on the computational complexity of final technological solutions for resource allocation. Problem of RAT 1 was reduced to the problem solution of nonlinear optimization. In solving this problem minimized both the number of resource blocks used, and downlink bandwidth.