2017 № 3(36)

Kazancev G.Y., Omarova G.A. CONSTRUCTION AND RESEARCH OF MICROSCOPIC MODELS FOR TRAFFIC FLOW
Bredikhin S.V., Lyapunov V.M., Shcherbakova N.G. CLUSTER ANALYSIS OF THE CITATION NETWORK OF SCIENTIFIC JOURNALS
Kudaykulov A.K., Tashev A.A. CREATING SOFTWARE FOR ANALYSIS OF THE UNSTEADY THERMAL STATE OF A ROD WHICH IS EXPOSED TO THE SIMULTANEOUS PRESENCE OF A LOCAL INSULATION, THERMAL TRANSFER, AND HEAT FLUX
Zybareva O.Y. ENERGY SUPPLY OF SENSORS IN WIRELESS SENSOR NETWORKS AND THEIR APPLICATIONS
Magzom M.M., Nyssanbayeva S.E., Kalimoldayev M.N. COMPUTERR SIMULATION OF DECENTRALIZED NETWORK
Akhpashev R.V. SOFTWARE DEVELOPMENT FOR LTE COVERAGE OPTIMIZATION

Novosibirsk State University, 630090, Novosibirsk, Russia
*Institute of Computational Mathematics and Mathematical Geophysics SB RAS, 630090, Novosibirsk, Russia

CONSTRUCTION AND RESEARCH OF MICROSCOPIC MODELS FOR TRAFFIC FLOW

UDC 519.179.2—512.23

Simulation of transport systems is the demanded task in control of road networks helping to make decisions on further development and extension of transport system. In particular, simulation allows defining need for extension of a road network or adding of means of regulation. In this paper, traffic is simulated according to two different models: the cellular automaton based on cellular automaton of the Nagel-Scheckenberg model and Intelligence Driver model and existed cellular automata model was modified for simulations of multiline roads and multiline intersections.

The Intelligence Driver model was proposed by Treiber. It is continuous deterministic one-dimensional model, which defines acceleration of vehicle i as function from its own velocity , gap and velocity difference to the vehicle in front i-1. For experiments, integration with simple Euler scheme was used, with time discretization of Dt=0.4 s and translation of vehicles in each step according to equation of motion with constant acceleration for period of time Dt.

The Nagel-Scheckenberg model is a one-dimensional stochastic machine designed to simulate traffic. The model dimensional grid used in each cell is placed exactly one machine, the cell is either empty or contains a car. Time is discrete, the machine moves to forward an integral number of cells for each step of iteration. At each step of the iteration for each car in turn all the rules are applied. The first rule is responsible for aspiration of drivers to go as soon as possible, without violating the rule, the second rule doesn’t allow collisions, and the third rule introduces an element of randomness in the motion of each driver. This rule set is the minimum set necessary for reproduction of basic properties of a transport flow. The main advantage of this model is its simplicity compared with other approaches; it is important in the transition to more complex structures, such as multi-row model or models including intersections or implementation of modification, which allow more accurate imitation of driver’s behavior, such as slow-to-start and slow- to-stop models. In slow-to-start model for third rule used velocity-dependent random value with higher chance of slow if velocity on previous step is zero. In slow-to-stop model in addition was modified second rule, so vehicle begins to slow not in the last moment before collision but in several steps before according to velocity difference and expectations about gap between vehicles according to their velocities on previous step.

Experiments with both models with equivalent parameters and same initial conditions results in obtaining similar fundamental diagrams of traffic flow for one line traffic. In both cases traffic flow increasing with increase of its density at first, but after near same density value it begins decreasing to near zero in situations where density is equal to one. Max value of traffic flow is also similar in both cases.

To allow cellular automata, based on Nagel-Scheckenberg model, to simulate multiline road, rule for changing lines is needed. In this paper symmetrical change-line rule was used, there are no differences in changing line to left or to right. With this rule if vehicle found way forward blocked but still can move in this step according to its velocity and line near current have greater gap, vehicle change lines.

Simulation of multiline intersection is more complex, because according to traffic regulations on intersections with more than one line not all directions of turn available for vehicles on different lines. So although the only difference on intersection is different trajectories for vehicles on different lines, on road before intersection vehicles should change lines to come on intersection on right position according to traffic regulations. According to that, in close vicinity of intersection, priority of choosing line changes from line where vehicle can move faster to line, where vehicle can move to correct road to its course according to traffic regulations.
A cellular automaton for traffic simulation of multiline intersections was designed. The program of generation of the cellular automaton for different intersections was realized.

The models can be used to understand, predict and optimize different traffic situations and as examples for the various possible extensions and fields of applications.

Key words: model, cellular automaton, Triber model, slow-start and slow-stop models, distance, speed, acceleration.

References

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Bibliographic reference: Kazancev G.Y., Omarova G.A. Construction and research of microscopic models for traffic flow //journal “Problems of informatics”. 2017, № 3. P. 4-15.

Article

Bredikhin S. V., Lyapunov V. M., Shcherbakova N. G.

Institute of Computational Mathematics and Mathematical Geophysics SB RAS, 630090, Novosibirsk, Russia

CLUSTER ANALYSIS OF THE CITATION NETWORK OF SCIENTIFIC JOURNALS

UDC 001.12—303.2

In this work we analyze the structure of the journal citation network built on the basis of the bibliographic information extracted from the database RePEc. The network is represented as the weighted directed graph (digraph), the main component G has 1729 vertices (journals) and 135702 arcs (citations). In accordance with M. Kessler (1963) the network of bibliographic coupling was constructed that is represented as weighted undirected graph and in accordance with G. Small (1973), I. V. Marshakova (1973) - co-citation network was constructed that is represented as weighted undirected graph . The weights of edges are assigned accordingly vector space model G. Salton, M. MacGill (1983). The graphs G, è are the objects of studying.

In the first part of the work we examine the problem of network connectivity via the adjacency relations between neighbors. The answer comes in two main flavors. One approach assesses the overall level of clustering in a network, and is called transitivity, see S. Wasserman, K. Faust, (1994). The global clustering coefficient is the fraction of closed triplets (subgraphs with three nodes and three edges) to all triplets (subgraphs with three nodes and two edges), see M. Newman (2002). A generalization to weighted networks was proposed by T. Opsahl, P. Panzarasa (2009). An alternative approach to connectivity was introduced in the work D. Watts, S. Strogatz (1998). A node clustering coefficient is defined as the fraction of number of actual ties among the neighbor nodes over possible ties between them. The network local clustering coefficient is defined as an average of clustering coefficients of nodes and is considered as one of the small-world parameters. For the weighted networks we use the generalization proposed in the work A. Barrat (2004). The results of local clustering measurements for G, è are presented.

In the second part of the work we analyze the community structure of the weighted digraph G and weighted undirected graphs è . It will be remarked that the majority of clustering algorithms are designed for weighted undirected graphs. We examine applicability of algorithms BTW M. Girvan, M. Newman (2002), WTR P. Pons, M. Latapy (2005), IMP M. Rosvall, C. Bergstrom (2008), MLO V. Blondel (2008). For digraph G clustering we used algorithms BTW è IMP, and for undirected version of G we used the whole kit. In both cases IMP obtained the community structure that largely corresponds to the economic disciplines. For clustering and the algorithms IMP, WTR è MLO were applied. Measures for the similarity of partitions delivered by the algorithms were analyzed (NMI, RAND). The results of applying community detection algorithms to graphs and are presented in the tables (3.1-3.4).

The conclusion contains comments to the results of the research. The approved tools give the basic insight about the structure of the bibliometric networks on study.

Key words: journal citation network, co-citation network, bibliographic coupling network, weighted directed graph, transitivity, weighted local clustering coefficient, community finding.

References

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13. Barrat A., Barthelemy M., Pastor-Satorras R., Vespignani A. The architecture of complex weighted networks // Proc. of the National Academy of Sciences. 2004. V. 101, iss. 11. P. 3747–3752.
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Bibliographic reference: Bredikhin S.V., Lyapunov V.M., Shcherbakova N.G. Cluster analysis of the citation network of scientific journals //journal “Problems of informatics”. 2017, № 3. P. 16-34.

Article

Kudaykulov A.K., A. A. Tashev A.A.

Institute of information and computing technology, 050010, Almaty, Republic of Kazakhstan

CREATING SOFTWARE FOR ANALYSIS OF THE UNSTEADY THERMAL STATE OF A ROD WHICH IS EXPOSED TO THE SIMULTANEOUS PRESENCE OF A LOCAL INSULATION, THERMAL TRANSFER, AND HEAT FLUX

UDC 539.3

The bearing element of a strategic equipment is a rod of limited length and variable cross-section. Most of them are exposed to certain types of heat sources. To ensure reliable operation of this equipment, it is necessary to know the change of the thermal physical characteristics of the rod along the length and time.

Defining the distribution law of the thermal characteristics of the rod with limited length, which is exposed to heterogeneous types of heat, is the basis for the study of the thermo-strained deformed state of structural rod elements of power plants, internal combustion engines, and hydrogen engines. To determine the temperature distribution law along the length of the rod with limited length and constant cross section, many scientists use a finite element method. In particular, they consider the established problem to determine the temperature field along the length of the horizontal rod with the insulated side surface, limited length and a constant cross-section. The heat transfer coefficient and ambient temperature are considered constant.

Some of the work investigates the process of heat conduction in the core elements of nuclear power plants based on the finite element method.

Many authors also consider the effect of temperature on the deformation of the investigated element, during which they can also analytically calculate the temperature distribution law along the length of the rod with insulated lateral surface, and the left end is exposed to the heat flux and the right end is exposed to the heat exchange with the environment. In addition, in this work, we determine the temperature field along the length of the horizontal rod with constant cross section. At the same time, the left end is exposed to the constant temperature, and the remaining surface of the core is exposed to the heat exchange with the environment. The results obtained agree well with practical results. Most of the authors use the energy conservation law in combination with variation methods to study the process of heat exchange between the deformable shell and the surrounding liquid. And here we developed application packages that use modern tools of programming to solve this problem. We can say that these packages, in a certain sense, are universal and user-friendly. Also, in this work, we study the different ways to define the non-stationary fields of temperature distribution in cylindrical rods which are exposed to laser heat sources. The obtained results can be used in the study of no stationary thermal processes in the rod with the laser heat source. Also, in this work, we are dealing with computational methods, algorithms and software package for the study of steady-state thermal stress — strain state of a rod with limited length and constant cross section, which is exposed to the local heat flow, temperature, thermal exchange, and the availability of local insulation is considered as well. In addition, for each of the considered problem, we successfully identified regularities. For some problems, we determined the steady-state temperature fields, the components of strain and stress and the displacement field. We obtained equations to calculate the elongation and axial compressive force. Also, investigated the convergence of the studied method and the accuracy of the numerical results. In contrast to the above works, in this paper, we consider the development of methods, computational algorithms, and programs based on the energy conservation law to study the steady thermal stress and strain state of the horizontal rod with constant cross section. For this task, we first defined the distribution law of temperature along the length of the rod. Further, if one end of the rod is firmly fixed and the other end is free, we can calculate the elongation depending on existing heat sources, physical and geometric characteristics of the rod, taking into account the presence of insulation. In the case of pinching both ends of the studied core, we can calculate the axial compressive force, taking into account the real factors. It also determines the distribution law of all the components of deformations and stresses. The study revealed some patterns of the process. It should be noted that programs developed in Delphi and Python proved to be effective and user-friendly.

The paper proposes a computational algorithm and method to determine thermo physical characteristics of the rod with limited length and variable cross- section in time. They are based on fundamental laws of energy conservation. The numerical solutions of the problem have been successfully achieved.

Key words: heat flow, the radius of the cross section, a heat source, the length of the rod, thermal conductivity, heat transfer.

References

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Bibliographic reference: Kudaykulov A.K., Tashev A.A. Creating software for analysis of the unsteady thermal state of a rod which is exposed to the simultaneous presence of a local insulation, thermal transfer, and heat flux //journal “Problems of informatics”. 2017, № 3. P. 35-46.

Article

Zybareva O.Y.

Novosibirsk State Unuversity, 630090, Novosibirsk, Russia

ENERGY SUPPLY OF SENSORS IN WIRELESS SENSOR NETWORKS AND THEIR APPLICATIONS

UDC 004.72

A sensor network, a network of integrated embedded devices (sensor nodes) with capabilities of sensing, computation and communication, is used to sense and collect data. A typical and widely deployed category of applications is one that uses sensor nodes with battery power. A major limitation of untethered nodes is finite battery capacity — nodes will work for a finite period, as long as the battery lasts. Finite node lifetime implies finite lifetime of the applications or additional cost and complexity to regularly change batteries. Nodes could use large batteries for longer lifetimes, but will have to deal with increased size, weight and cost.
Some solution techniques have been proposed to maximize the lifetime of battery-powered sensor nodes. These techniques include accumulator battery, routing, energy-aware MAC protocols and redundant location of nodes. The above techniques help extend the life of the application or/and the time interval between battery replacements but do not exclude the obstacles associated with energy.

An alternative technique that applied to solve the problem of finite node lifetime is the use of energy harvesting. Energy harvesting is the use energy from the environment or other energy sources and converting it to electrical energy. The collected electrical energy supplies the sensor nodes. Energy from external sources can increase lifetime and capability of the sensor nodes. Since a node is limited to energy only until the next harvesting opportunity (recharge cycle), it can optimize energy consumption to maximize productivity during this time interval.

There are realizations of energy harvesting nodes using energy sources like human power, wind, and radio frequency energy. The most common and popular technique of energy harvesting is converting solar energy to electrical energy. Although there are many sources of energy harvesting, solar energy is the cheapest, most affordable and convenient source for energy collection. Solar energy is predictable, but it is unregulated energy source — the intensity of the sunlight cannot be controlled. Other methods of energy harvesting convert wind energy or mechanical energy to electrical energy. Since the amount of energy used for conversion can vary, such methods can be considered as controlled sources of energy. No energy source is ideal for all applications. The choice depends on the requirements and limitations of each application.

This paper surveys applications that use the capabilities of sensor networks to receive energy from the environment, its architecture, energy sources and storage technologies. Energy harvesting system consists of three components, the Energy source (performs the function of energy generator), the Harvesting architecture (mechanisms for using and converting external energy into electrical energy) and the Load (consumption of collected energy).

The application of energy harvesting tools can help to receive the tradeoff between the quality of service and lifetime of sensors. For this purposes it needs to solve the following problem. It is required to estimate the periodicity and magnitude of the source of energy harvest and determine the strategy for tuning. At the same time it is required to prevent unreasonable fast depletion of sensor batteries until the next recharge cycle. The corresponding mathematical tools have to be made.

In this paper the mathematical models and methods for node throughput estimation in energy harvesting wireless sensor networks have been discussed. The sensor behavior is modeled by Markov processes with discrete states and continuous time. There are different types of models. The probabilities of sensor states can be used for network performance optimizing.

It can be conclude that the solar energy is the preferable source of energy for wireless sensor networks. This type of energy is easily available and utilized. The survey of some solutions for energy harvesting sensor nodes architectures is provided. Generally, there are two following architectures. Energy is harvested just-in-time for use and energy is harvested, if it is possible, and stored in some energy buffer for application requirements in future. The alternative energy sources (wind, radio frequency energy harvesting, piezo-electric etc.) are also considered.

Key words: wireless sensor network, energy harvesting, the lifetime of the sensor network node, the probability of the sensor availability, solar energy.

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23. SHahov V. V., YUrgenson A. N., Sokolova O. D. EHffektivnyj metod generacii sluchajnyh geometricheskih grafov dlya modelirovaniya besprovodnyh setej // Prikladnaya diskretna matematika, 2016. N 4 (34). C. 99–109.
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25. Stanley-Marbell P. and Marculescu D. An , Low Power, Energy-harvesting System with Custom Multi-channel Communication Interface // Proc. Conference on Design, automation and test in Europe. EDA Consortium, 2007, P. 15–20.
26. Polastre J., Szewczyk R., and Culler D. Telos: Enabling Ultra-low Power Wireless Research // Fourth International Symposium on Information Processing in Sensor Networks, April 2005, P. 364–369.
27. Corke P., Valencia P., Sikka P., Wark T., and Overs L. Long-duration Solar-powered Wireless Sensor Networks // Proc. 4th Workshop on Embedded Networked Sensors. ACM, 2007, P. 33–37.
28. Minami M., Morito T., Morikawa H., and Aoyama T. Solar biscuit: A Battery-less Wireless Sensor Network System for Environmental Monitoring Applications // The 2nd International Workshop on Networked Sensing Systems, 2005, 2007.
29. Mica, Mica2, Mica2Dot, MicaZ, Telos, [El. Res.]. http://www.xbow.com/products.
30. TinyOS, [El. Res.]. http://www.tinyos.net/.
31. Zhang P., Sadler C. M., Lyon S. A., and Martonosi M. Hardware Design Experiences in ZebraNet // Proc. Second International Conference on Embedded Networked Sensor Systems. ACM, 2004, P. 227–238.
32. TurtleNet, [El. Res.]. http://prisms.cs.umass.edu/dome/turtlenet.
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34. Musiani D., Lin K., and Rosing T. S. Active Sensing Platform for Wireless Structural Health Monitoring // Proc. Sixth International Conference on Information Processing in Sensor Networks. ACM, 2007, P. 390–399.
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Bibliographic reference: Zybareva O.Y. Energy supply of sensors in wireless sensor networks and their applications //journal “Problems of informatics”. 2017, № 3. P. 47-67.

Article

Magzom M.M., Nyssanbayeva S.E., Kalimoldayev M.N.

The Institute of Information and Computational Technologies, 050010, Almaty, Republic of Kazakhstan

COMPUTER SIMULATION DECENTRALIZED NETWORK

UDC 004.056.5

This paperis dedicated to the development of a software system for computer modeling (simulation) of a decentralized network with the ability to perform calculations on distributed nodes.The results of the creation of a such simulation system for decentralized computer networks arc discussed. This system is used during research and implementation of different cryptographic algorithms based on modular arithmetic.

In decentralized networks, there arc no dedicated servers, and each node (peer ) acts like a client and a server. Unlike the client-server architecture, such an organization allows to keep the working capacity of network at any number and any combination of available nodes. Considering the steady growth in the number of applications, users and devices in these networks, issues of ensuring information security in such networks arc particularly relevant.

Cryptographic means of information protection can be used to solve the problems of confidentiality and authentication during the interaction in the network. Encryption of the data flow between decentralized network nodes allows not only to protect the data itself, but also to hide the fact that network connection has taken place.

The main tasks of cryptographic protection of information in decentralized networks arc the following: data encryption to ensure confidentiality during storage and transmission over the network between nodes; the usage of hash functions to control the integrity of data; usage of message authentication codes and electronic digital signatures for message authentication. An important task for this type of networks is to provide cryptographic protection of information during data transmission through communication channels and during storage.

During the research and development of cryptographic systems based on modular arithmetic in the Laboratory of Information Security of the Institute of Information and Computational Technologies, it was important to investigate possibility and efficiency of usage of the developed symmetric and asymmetric cryptographic algorithms in network data transmission. For this reason, the work on the development and implementation of a simulation system of decentralized networks is carried out.

The analysis of existing programs for simulating peer-to-peer networks is performed. The typical requirements for these systems such as workflow architecture, usability, scalability, statistics, portabilitywcrc evaluated. It was shown, that the most of the simulation systems, which arc available from the open sources, arc obsolete and do not allow to run network simulation on distributed nodes. According to it, a new simulation system has been developed.

The developed system includes the following components: topologvdesign and monitoring system; node process manager; computing process instance. First the component of topology design creates a network topology based on the specified parameters. Based the created topology process managers create instances of processes that simulate the operation of individual nodes. Building a node manager in a separate component allows to distribute the process of creating and managing nodes to different computers. Each process performs calculations and acts like a separate network node. A process is
assigned a unique identifier and a lambda function that will be executed by the process and simulate the calculation process. Processes can exchange data through this protocol by using an arbitrary form of messages, the content of which depends on specifications in the processes of the lambda functions. The system uses an event-based workflow, that is, a state change causes corresponding events in related objects. The network monitoring component receives every status message from nodes in the network.

The system is implemented in the JavaScript language using the Node.js and AngularJS web platforms. Processes are interconnected by passing a message through the HTTP protocol by using WebSocket technology.
The structural and protocol design of the system is discussed. The proposed structure of the system allows users to apply their own encryption algorithms and security protocols to the simulation process. The developed system of decentralized network simulation has a feature of working on distributed nodes, for example on different computers, either physical or virtual. This feature makes the developed simulation system a useful tool during research and implementation of different cryptographic algorithms based on modular arithmetic. This gives an opportunity to evaluate efficiency of different cryptographic schemes in a network flow.

Key words: decentralized networks, network simulation, information security, computer modeling.

References

1. Nakamoto S. Bitcoin: A peer-to-peer electronic cash system. 2009; 2017. [El. Res.]. http://www.bitcoin.org/bitcoin.pdf
2. Bocek T., Peric D., Hecht F., Hausheer D., Stiller B. PeerVote: A Decentralized Voting Mechanism for P2P Collaboration Systems. In: Sadre R., Pras A. (eds) Scalability of Networks and Services. AIMS 2009. Lecture Notes in Computer Science. Springer; Berlin; Heidelberg, 2009. Vol. 5637.
3. Risson J., Moors T. Survey of Research Towards Robust Peer-to-Peer Networks: Search Methods. Technical Report, University of New South Wales. Sydney; Australia, 2004.
4. Kurose J., Ross K. Computer Networking: A Top-Down Approach Featuring the Internet. Addison-Wesley, 2005.
5. Status of the UC-Berkeley SETI Efforts, Korpela, et al. // Instruments, Methods, and Missions for Astrobiology XIV. Proc. SPIE 8152. 2011. Vol. 14. P. 1–8.
6. Ethereum: a platform for smart contracts. [El. Res.]. https://www.ethereum.org/
7. Biyashev R. G., Nyssanbayeva S. E., Begimbayeva Ye. Ye., Magzom M. M. Modification of the Cryptographic Algorithms, Developed on the Basis of Nonpositional Polynomial Notations // Proceedings of the International Conference on Circuits, Systems, Signal Processing, Communications and Computers (CSSCC 2015). Vienna, 2015. P. 170–176.
8. Biyashev R. G., Nyssanbayeva S. E., Begimbayeva Ye. Ye., Magzom M. M. Building modified modular cryptographic systems // International Journal of Applied Mathematics and Informatics. 2015. Vol. 9. P. 103–109.
9. Biyashev R., Kalimoldayev M., Nyssanbayeva S., Magzom M. Development of an encryption algorithm based on nonpositional polynomial notations // Proceedings of the International Conference on Advanced Materials Science and Environmental Engineering (AMSEE 2016). Chiang Mai; Thailand, 2016. P. 243–245.
10. Bailes J., Templeton G. Managing P2P security // Communications of the ACM 47. 2004. Vol. 47, N 9. P. 95–98.
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12. Naoumov N., Ross K. Exploiting P2P Systems for DDoS Attacks. International Workshop on Peer-to-Peer Information Management. 2006. [El. Res.]. http://cis.poly.edu/~ross/papers/p2pddos.pdf

Bibliographic reference: Magzom M.M., Nyssanbayeva S.E., Kalimoldayev M.N. Computerr simulation of decentralized network //journal “Problems of informatics”. 2017, № 3. P. 16-34.

Article

Akhpashev R.V.

Siberian State University of Telecommunication and Information Sciences, 630102, Novosibirsk, Russia

SOFTWARE DEVELOPMENT FOR LTE COVERAGE OPTIMIZATION

UDC 004.7

The LTE is a reality today and is growing fast in the global mobile technology. The members which using mobile internet must be having broadband access wherever they go, and not just at home or in the office. The users are enhanced further for more demanding applications like interactive TV, mobile video streaming, advanced games or professional services.

For the LTE deployment and modelling of cell coverage using the most common propagation model is very important. The radio propagation models are very significant while planning for any wireless communication system. The propagation models calculating for some area (e.g. Japan). The problem of this models is a low level of accuracy for another place [3]. The propagation model tuning is one of the most important issues in efficient network planning. Obviously, we need to correct these models and find the correction factor because the calculating parameters of original COST 231 Hata are not true.

A mobile network operators design LTE networks with help of a radio propagation models (Okumura-Hata, Walfisch-Ikegami, etc.). One of the most common model used in determining the radio coverage in LTE networks is COST 231 Hata. Tuning of the model is carried out using large number of measurement records to increase the accuracy of the path loss prediction. The path loss predictions of tuned model are compared with the COST 231 Hata model. In this paper, tuning of COST 231 Hata prediction method has been carried out based on experiments using LTE technology. Authors are carried out the link budget calculation for path losses in urban area using theoretical parameters for LTE.

The radio propagation models are very important while planning for any wireless communication system. The model describes the behavior of the signal while it is transmitted from the transmitter towards the receiver, and the path loss. The Path loss models are important for predicting coverage area, interference analysis and cell parameters which are basic elements for network planning process in cellular systems.
In this paper, tuning of COST 231 Hata prediction method has been carried out based on experiments using LTE technology. Authors are carried out the link budget calculation for path losses in urban area using theoretical parameters for LTE. The information of path losses provides defining the coverage area of the LTE networks. The main parameters of link budget are transmitter power, antenna gain, antenna direction, height of base station and subscriber antenna height. The LTE standard uses the Orthogonal Frequency Division Multiplexing (OFDM) technology on physical layer. OFDM subdivides the bandwidth available for signal transmission into a multitude of narrowband subcarriers. The basic LTE downlink physical resource can be seen as a time-frequency grid. The OFDM symbols are grouped into resource blocks. The resource blocks have a total size of 180k Hz in the frequency domain and 0.5 ms in the time domain. The important parameters of cell quality are measurements. In LTE network user equipment (UE) need to measure signal strength of its own and neighbor cell constantly, during idle, connected mode or handovers in order to keep the signal quality constant. UE measures RSRP and RSRQ in LTE. RSRP is the linear average of the downlink reference signals across the channel bandwidth.

The information of path losses provides defining the coverage area of the LTE networks. The main parameters of link budget are transmitter power, antenna gain, antenna direction, height of base station and subscriber antenna height.

The main task in this paper is to develop a mobile application (Android) that will receive the LTE measurements (RSRP, RSRQ) from the service base station. All of this data could be tagged with geographic information. Also, we need to develop the server software for data analysis, finding the weak LTE coverage areas and making the recommendations of parameter correction.

Authors have developed the hardware and software system that allows to calculate the correction factors for the empirical propagation model based on LTE measurements getting from mobile devices. The software helps to get measurements from LTE base station. The predicted coverage area calculated with the theoretical model is 857 m. The black circle shows the cell radius after the correction factor adding. The cell range based on the correction factor is equal to 368 m. If we compare two coverages, we can see that the empirical model does not accurately indicate the coverage area.

Key words: LTE, optimization, COST 231 Hata, Android.

References

1. Moray Rumney. LTE and the Evolution to 4G Wireless: Design and Measurement Challenges, 2nd Edition, JohnWiley, 2013.
2. Farooq Khan. LTE for 4G Mobile Broadband: Air Interface Technologies and Performance. Cambridge University Press, 2009.
3. Harri Holma, Antti Toskala. LTE for UMTS — OFDMA and SC-FDMABasedRadio Access. John Wiley, 2009.
4. Tihvinskij V. O. Seti mobil’noj svjazi LTE, tehnologii i arhitektura. Jeko-Trendz, 2010.
5. Triantafyllopoulou D.; Kollias K.; Moessner K. QoS and Energy Efficient Resource Allocation in Uplink SC-FDMA Systems, IEEE Transactions on Wireless Communications, 2015. V. 14, Iss. 6, P. 3033–3045.
6. Chien-Hua Chen, Kai-Ten Feng. Statistical Distance Estimation Algorithms With RSS Measurements for Indoor LTE-A Networks, IEEE Transactions on Vehicular Technology. 2017. V. 66, Iss. 2, P. 1709–1722.
7. Shakhov V. Experiment Design for Parameter Estimation in Sensing Models // Springer Lecture Notes in Computer Science. 2013. V. 8072, P. 151–158.
8. Hata, M. Empirical Formula for Propagation Loss in Land Mobile Radio Services // IEEE Transactions on Vehicular Technology. 1980. V. 29 (3), P. 317–25.
9. Shahov V. V., Jurgenson A. N., Sokolova O. D. Jeffektivnyj metod generacii sluchajnyh geometricheskih grafov dlja modelirovanija besprovodnyh setej // Prikladnaja diskretnaja matematika. 2016. N 4 (34). S. 99–109.
10. Kiran P.; Jibukumar M. G.; Premkumar C. V. Resource allocation optimization in LTE-A/5G networks using big data analytics // International Conference on Information Networking (ICOIN), 2016, P. 254–259.

Bibliographic reference: Akhpashev R.V. Software development for lte coverage optimization journal “Problems of informatics”. 2017, № 3. P. 78-98.

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