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ЦИФРОВАЯ ТРАНСФОРМАЦИЯ ТРАНСПОРТА / DIGITAL TRANSFORMATION OF TRANSPORT
УДК 004.7
DOI: 10.25559/SITITO.15.201902.516-527
Mesh Network for Railways
D. M. Shneps-Shneppe*, E. O. Tikhonov
AbavaNet, Moscow, Russia
34 Narodnogo Opolcheniya St., Moscow 123423, Russia * [email protected]
Abstract
The possibilities provided by the mesh telecommunication network on the railways are examined in the article. Mobile terminal radio stations located on trains are considered as repeaters and moving base radio stations for trains outside the coverage area of base stations of the network. Such a mesh network is represented both as the main communication network on railway lines equipped with an insufficient number of radio base stations and as a backup option in the event of a base station failure on one hand or a decrease in the signal-to-noise ratio at the terminal station due to a breakdown on the train on the other hand. The results of a theoretical mathematical calculation of the increase in the effective coverage area of a radio network gained from the use of mesh technology are presented. The results of modeling of the mesh network on the railroad are also presented together with the dependencies of the probability of communication from such factors as: the number of trains on the railway line, the number and range of the base stations, the range of terminal stations, the capacity of the network and the limitation on the number of retransmissions. For the case of using a mesh network as a backup option when a railway line is fully covered with base stations, the results of simulating the time of establishing a connection via a retransmission in the area of a base station failure are presented. Comparison of the possibilities provided by first-order mesh networks (with one repeater between the terminal and base stations) and more capacious (second and higher orders by the number of allowable repeaters) is presented. As a radio communication standard for mesh network modeling, the application of DMR (Digital Mobile Radio) is considered as a promising one for railway communications, requiring a small number of base stations.
Keywords: Moscow railway network, Moscow diameters; GSM-R, DMR, TETRA, railway mesh network, DMR mesh network.
For citation: Shneps-Shneppe D.M., Tikhonov E.O. Mesh Network for Railways. Sovremennye infor-macionnye tehnologii i IT-obrazovanie = Modern Information Technologies and IT-Education. 2019; 15(2):516-527. DOI: 10.25559/SITITO.15.201902.516-527
Контент доступен под лицензией Creative Commons Attribution 4.0 License. The content is available under Creative Commons Attribution 4.0 License.
Современные информационные технологии и ИТ-образование
Mesh сеть для железных дорог
Д. М. Шнепс-Шнеппе*, Е. О. Тихонов
AbavaNet, г. Москва, Россия
123423, Россия, г. Москва, ул. Народного Ополчения, д. 34 * [email protected]
Аннотация
В статье рассматриваются возможности, предоставляемые применением mesh-сети, для организации связи на железнодорожной сети. Анализируется использование комплекса терминальных станций радиосвязи, расположенных на поездах, в качестве ретрансляторов для поездов, находящихся вне зоны действия базовых станций сети связи. В статье такая mesh-сеть представлена как в качестве основной сети связи на железнодорожных линиях, оборудованных недостаточным количеством базовых станций радиосвязи, так и в качестве бэкап-опции на случай выхода из строя базовой станции на пути следования поезда либо понижения уровня сигнал/шум на терминальной станции вследствие поломки на поезде. Представлены результаты теоретического математического расчета увеличения эффективной площади покрытия радиосети от использования mesh-технологии. Также приводятся результаты моделирования mesh-сети на железной дороге и представлены зависимости вероятности установления связи от таких факторов, как: количество поездов на железнодорожной линии, количество и радиус действия базовых станций, радиус действия терминальных станций, емкость сети и ограничение по количеству ретрансляций, и др. Для случая использования mesh-сети в качестве бэкап-опции при полном покрытии базовыми станциями железнодорожной линии приведены результаты моделирования времени установления связи через ретрансляторы в зоне выхода из строя базовой станции. Приводится сравнение возможностей, предоставляемых mesh-сетями первого порядка (с одной ретрансляцией между терминальной и базовой станциями) и более емких (второго и более высоких порядков по количеству допустимых ретрансляций). В качестве стандарта радиосвязи для моделирования mesh-сети рассмотрено применение DMR (Digital Mobile Radio), как перспективного для железнодорожной связи, требующего небольшого количества базовых станций.
Ключевые слова: Московская железнодорожная сеть, Московские диаметры, GSM-R, DMR, TETRA, железнодорожная mesh сеть, DMR mesh сеть.
Для цитирования: Шнепс-Шнеппе Д. М., Тихонов Е. О. Mesh сеть для железных дорог // Современные информационные технологии и ИТ-образование. 2019. Т. 15, № 2. С. 516-527. DOI: 10.25559/SITITO.15.201902.516-527
Modern Information Technologies and IT-Education
Introduction
Nowadays modern railway systems require special communication and signaling network along the train path. The onboard equipment collects data from train automation and telemechanics (GAT) and exchanges information with the central processing complex (CSC) [16]. Existing railway radio communication systems require migration to digital standards. The currently used GSM-R mobile communication standard is out-of-date and is expected to be discontinued by 20301 [17]. The promising modern digital radio standard DMR (Digital Mobile Radio)2 has advantages in comparison with GSM-R, LTE and 5G3, and is equals or exceeds the TETRA digital radio standard (depending on the frequencies used) in the base stations coverage area4. The DMR Level 3 specifications (Tier III - professional / industrial equipment) satisfy the requirements for maintaining the voice communication between the operator and the central complex, and have sufficient bandwidth for the transmission of GAT data. A feature of the DMR standard is the economic availability of equipment. In practice, DMR is considered as communications standard in the association of urban and suburban railway communications of the Moscow agglomeration, in the so-called Moscow diameters5 (see Figure 1).
For communication in less densely populated regions of Russia, long-range (in comparison with GSM 2-5 generations) digital radio connections could be used, for example satellite connections6.
Further in this article, usage of the digital DMR radio standard or analog with a station coverage area of 10 km or more capable of supporting the terminal (on-board) radio station speed up to 500 km/h will be proposed. The communication distance between the terminal stations is assumed to be several times lower than the communication distance between the base and the terminal stations.
These parameters of digital radio system for voice and data transmission allow implementing mesh network based on fixed base stations with a large coverage area, and a set of moving terminal stations act as repeater for each other. Mesh network provides online connection out of the base stations coverage with a certain probability. This probability is a benefit in functional area of the radio system due to the mesh networks usage. On the other hand, if the railway line has 100% connection coverage directly to the base stations, then using the mesh network will restore the signal in case of base station problems (Figure 2):
• One base station failure. In this area there will be trains connecting to neighboring base stations via mesh network repeaters.
• The drop in radio power of the terminal station on a train or the occasional stop/deceleration of the train far from the base station. Trains moving in the same and opposite directions (with the normal terminal station power) will provide the communication of the broken train with the CSC.
F i g. 2. Goals of using mesh network
If the railway radio communication and signaling network is built on the basis of the DMR standard, the mesh network implementation will require a small costs increase. First of all, it is based on usage of already installed terminal stations as the repeaters. Compared with the additional base stations installations, the use of terminal repeaters is economically reasonable because of the following reasons:
• Terminal stations are easier in support, since does not require the technician's visit on a place. The train itself arrives at the
1 EIRENE Functional Requirements Specification, Version 8.0.0. GSM-R Functional Group. UIC CODE 950. Version: 0.0.2. International Union of Railways, Paris, France, 2015. [Electronic recourse]. Available at: https://uic.org/IMG/pdf/frs-8.0.0_uic_950_0.0.2_final.pdf (accessed 12.01.2019). (In Eng.)
2 DMR - New Radio Standard. Radioprofessional [Electronic recourse]. Available at: http://www.radioprofessional.info/dmr_new.php (accessed 12.01.2019). (In Russ.)
3 Mottier D. How 5G technologies could benefit to the railway sector: challenges and opportunities. Mitsubishi Electric R&D Centre Europe - France. 2016. [Electronic recourse]. Available at: https://docbox.etsi.org/Workshop/2016/201611_managing_rail_mobile_comms/s03_attractiveness_future_other_techno/benefits_5g_techno_ railway_sector_mottier_merce.pdf (accessed 12.01.2019). (In Eng.)
4 Marengon R. A TETRA and DMR Comparison. MissionCritical Communications, RadioResource International. April 01, 2010. [Electronic recourse]. Available
at: https://www.rrmediagroup.com/Features/FeaturesDetails/FID/174 (accessed 12.01.2019). (In Eng.); A comparison of TETRA and GSM-R for
railway communications. Sepura, 2017. [Electronic recourse]. Available at: http://fplreflib.findlay.co.uk/images/pdf/tetratoday/A-comparison-
of-TETRA.pdf (accessed 12.01.2019). (In Eng.); Teltronic Tetra Solutions for railway signaling applications. White papers. Teltronic, Zaragoza Spain. [Electronic recourse]. Available at: https://www.teltronic.es/wp-content/uploads/2017/06/BD170317_eng_ed2.0_White-Paper_TETRA-for-Railway-Signaling. pdf (accessed 12.01.2019). (In Eng.)
5 All Moscow Metro lines now feature MT_FREE Wi-Fi network. Moscow Mayor official website. 30 April 2017. [Electronic recourse]. Available at: https://www.mos.ru/ en/news/item/23445073 (accessed 12.01.2019). (In Eng.)
6 Morris I. Russia's MTS: There Is No 5G Business Case. Light Reading. 3 Dec. 2017. [Electronic recourse]. Available at: http://www.lightreading.com/mobile/5g/russias-mts-there-is-no-5g-business-case/d/d-id/731347 (accessed 12.01.2019). (In Eng.)
Современные информационные технологии и ИТ-образование
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depot - the service can be produced there serially.
• Terminal stations are installed on trains and do not require engineering and protective structures (towers, etc.]
• According to the requirements of the railway system, a 100%-coverage by the radio signal of the entire train path can be provided. In this case, the mesh network has a high economic potential as a backup technology compared to base stations duplication. In the case of an occasional train stop or the signal-to-noise ratio fall at the terminal station, mesh network will allow the most rapid receipt of a signal from the broken train away from the base stations of ign syfOsm ane the en-sence of other means of communication.
First and second level mesh neiwork
Mobile terminal radio station located on train could connect with either base radio station directly (if located inside the coverage area of network base station] or with usage of mobile repeater (mobile terminal radio station that has connection to base directly or also using repeaters]; it's a basement of considered mesh network. In case of possibility of only one repeater in the network route because of some limits or network structure features, terminal radio station with actual network connection has to be located inside base station coverage area or inside the coverage area of the mobile station placed there. This mesh network could be named “first-level mesh network”. The coverage are of mobile radio station is lesser then area of base station, so mobile station used as repeater should be located near the edge of base coverage area virtually extending that. Main parameters:
B - base station coverage distance, km. Connection probability inside that assumed to be 100%.
b - mobile terminal (on-board] repeater station coverage distance, km (b<B]. If repeater is inside the base station coverage area inside this distance connection probability assumed to be 100%. If not, connection possibility is assumed to be 0%.
L - length of the model railway, km
N - number of trains that could be used as repeaters in mesh network, pc.
Acceptable values for x>0 for conditions (A] are x є (0 b):
B + x - b < B ^ x < b
Probability of random i є(0,Z). to be under (A] demands:
Pl ]=Ljcii=i|b +b _ b=L [B-(B+x - b )]=L (b - x)
Probability for rand om i to be hi contra diction ■with (A]: ogabilisy for all N random repeaters to be in contradiction with (A]:
P(x) = {Pi (x)f =(!-b/f)
ogobility forat lessi ono of At takdnro kepeaters to be under (A] de-mokSs: _ N h o,n
P W = 1 -TW = 1 -[1 --
Figure 5 shows the theoretical dependence for the probability of establishing a connection using a 1 repeater on position relative to base station edge and computer simulation of this parameter.
Probability for 1 possible forwarding
-----P1(x) ------Simulation
Distance from base station edge, x/b
F i g. 4. Dependence for the connection probability with 1 repeater Pfc) on x (for b=10, L=500, N=100]: theoretical and computer simulation
If the train trying to connect the network, is guteide thee dgeof base coverage area B in distance x, following cknOitiens k0 oriO Sir correct to connect through repeater located In distaeee ifrom the -see (see Figure 3]:
Location of firs t-level
b b nesh network entities
1_ X _1_^
5 ^ В 1 1 '
V -J L
Base station coverage area First repeater coverage area
Distance from he base station
F i g. 3. The location of the base station edge B, repeater i, train x
f i < в (1] - repeater i is inside B area
і . (2] - train x is inssde і area
[ B + x < i + b
or:
B + x - b < i < B. (A]
Figure 5 shows virtual bas e stnhion area coverage extension because of usage first-level mesh network. Connection probability at She rdges (ootsi de base station areo] is lossrr 100% and depends on potential repeaters positions.
Virtual base coverage area extension
Distance from base area edge, x/b
F i g. 5. Virtual base station coverage extension. Computer simulation for b=10 km,L=500km,N=100pc, B=40km (M=5000 cycles]
Modern Information Technologies and IT-Education
Summary probability with conditions (A) at least one of N random i with random x є(0, ö). (if x>b connection probability is 0, because of impossibility of achievement (A)):
Defining an additional parameter Л:
L L
dx
L jyN dy =
N + Г
.Summary connection probability on the path L using 1 repeater:
( / , \N+1X
P =
B+b-X B+b
L
L N +1
i-'i-J
For the second-level mesh networ- (where up to 2 repe-ters in network route could be esed) 0, 1 or 2 repeaters could exist between the trai ns that want to connect the base station.In tins case forthe train in distance x from the base coverage area cdfe В Єі.е. gIrect connection to the base statio- is impessiblee fei'O.or 2 retransmio-sions alkewed cornection probability can lee calculated similarloto first-level mesh network:
P,2 (X)
b - x
•l(jV-l)
e--
(2b - x 2L?
2Lt
N (N-l)
,/огхє (0; f)
, forx e(b; 2b)
0, e
ure 6 shows connection probability dependence on x pocition cf ai train for parameters b=10 km, L=500 km, N=100 pc. Blue line shows theoretical result and red line shows computer simulation. Probability for 1 or 2 possible forwardings
-----P1,2(x) -----Simulation
Distance from base station edge, x/b
F і g. 6. Connection probability dependence for 2 and lesser retransmissions /■“. jxj on train position x from base coverage area for b=10 km, 1=500 km, N=100 pc
Figure 6 shows that possibility to realize second retransmission increases the probability of establishing a connection in comparison with limiting to only one retransmission. Also second-level mesh network provide high connection probability (0-60%) on the distance more than one terminal station coverage area f from Case edge (with example parameter values). Increasing number of^ocsh ble retransmissions (3 and more) also increases virtual Cage coveto age area extension; or decreases offline tune in sasg oebast rtaeion failure time for fully covered railway (that mean that mesh network will act as a backup option for the railway communication system).
Computer simulation
The estimation of the change in quality of network communication due to some mesh network methods can be performed by numerical computing for models with varying degrees of proximity to the real situation. Basic model.
Similar to the theoretical approach, the basic model estimate the connection probability at each point of path with random positions of the repeater trains. For this purpose, the presence of a network connection at each point with a random distribution of repeaters is checked certain number of times, forming a statistical distribution. Initial parameters for the model: the route length (L, km), number of trains with terminal stations on the route (N, pc), base station coverage distance (B, km), repeater coverage distance (b, km), the array of base positions ({bases}) and indirect: dimensioned analysis step (Лх) and number of cycles (M).
Triac commuoigafion jfrchatolityon Cge radway ys defineni as gh n ratio of thennmbhr of points with coneectrnn Oothe base (throcac ly as ueing eepraters) tolOetoghl топЛег of ooesible rosrdinate valuee (L)fer ranPemlyoenrrateTtram tcpeaCers positions. Tde 'onocedure is peofocmtd a pcadcgormmed numbtr of timos for sta-tittical ronules: overawe connecTion pnrsibihry on eha oaola h anel probadilety depgndence on oocrtinaVe (РПх)}.
Bcpic modd fa Two baoe statfons
Mcdd demenstrated basic possibilities for extending the influence of7 Oes^^^ rtatieos distpnre.
tnitcal bhnsmcCoa vgiueo: the ecesine ienpth L = 50b 0ml bane ttpiinn eoveaage aistance B = XOkm, reppoCorcoveragedietaпи t = id Xm, nsimc)es cf Oramrapeaters b =120 °c, base positfons: S5770™, 3yn km}, cycles number M=5000, analysis step Ax = 1 km.
Visualization of the simulation objects locations
0 167 333 L=500
Position, X
Fig.7.Oneofmodel generatedrandom train allocations. Graycirclesare bases, blue - trains inside the base coverage (direct connections), green - with network access thtouoi rexnnOrrs, red circle Sc elflino trains Analysis results:
Average connection probability with relevant increase
Connection probability, P
+0.39%
+0.3«
+0.25%
+0.15%
+0.04%
+0.01%
Fig.8.Modelanalysisresultvisualization:totalconnectionprobability(P) dependingonallowednumber ofretransmissions(K pc).Foreach K (black bold) communicationprobability(black)andincrease(gray)relevantto K-1 retransmissionsareindicated.
Figure 8 demonstrates that for determined parameter values even first-level mesh network gives relevant connection probability in-
Современные информационные технологии и ИТ-образование
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crease 16%. The biggest win is achieved by 18-level mesh network Thus, for parameter values specified in the model (a relatively large
and is more than 25%.
Connection probability at points of path
F і g. 9. Model analysis result visualization: total probability of connection established (P %) depending on allowed number of retransmissions (1C pc). The intensity of the color corresponds to the probability of connection. For each К (black), the connection probability is shown (gray).
The contribution to the efficiency of communication decreases with the growth of the required number of retransmissions (the main contribution is made by 1 and 2 retransmiss ions), however this contribution still remains significant.
number of repeater trains on the line, not too close and not too far base stations), the initial low probability of establishing communication is greatly enhanced by using the mesh network.
Parameter values variations
The effectiveness of the mesh network strongly depends on the initial parameters: the base station coverage distance B, the density of the location of the base stations on the path, the repeaters coverage distance b and the number of repeaters N on the railway.
The analysis of the model allows to explore and to evaluate some rules of such dependences (performed for the above parameters, except for the variable).
Connection probability for the different number of repeaters
• 100% • 90% ; 80% 70% 60% . 50% 40% 30% 20% 10% 0%
0 2 4 6 8 10 12 14
Position from the edge of base, x/b
-----N=10
N=30
-----N=50
-----N=70
N=90
F і g. 11. Model parameter values variation analysis visualization: connection probability at each points [P(x], %) for a different number of evenly distributed repeatess N,pc
Connertion probability at various points of the path
p(x) p(x)
Without retransmissions, P=32,4% f ^ retransmissions allowed, P-45,9%
F ig. 10.Modelanalysisresultvisualization:connectionprobabilityfor eachpointofpath(P(xj)depending onallowedretransmissionsnumber(tf).Height correspondstoconnection probability;light green shows contributiontoresult by K-level meshabove(K-1)-levelmeshnetwork.
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Efficiency of mesh network features rapidly increases with the increase in the nu mber of repeaters^ (but the growth rate slows down with this increase), especially at small distances frem the base station. Therefore, the more the number of trains, the higher the expediency of usingthem as repeaters.
But even witha smal Inumber of repeaters, mes h network gives an increasein tfficsency. The quantity characte ristic aS this canbe an "уігШпі incrraea" of the tiese rtatioaeovrreee distsnte n tte differ. ence betwern "he real diameter of the base station and the one that wnubd be necensayy to eecovkin tftfs protability of eommamcation witl the tame laveC es retrantmieoiun syrtem:
Virtual increase of of thc bast station coverage distance
F i g. 12. Virtual the base station coverage distance increase (the coefficient of increase in the coverage distance of the base station, leading to the same change inthetotalprobabilityofcommunicationalongtheentirepath)
Even with the moderate number of repeaters (less than 30) retransmission system leads to the same result of the final probability of communication along the entire path, as if the range of base stations increased by 4-10% (or the number of base stations increased by the corresponding number).
Relative increase of connection probability using the repeaters decreases with base stations number increase. Each base station acts as a reference for the retransmission chain, but simultaneously increases the iniiitl oelue for Sisyct crnnecteen to tie itse station, eerasiog a higher ties'; io r nstim atnig ttureletieu inctemint. In nt ditior, ifihe brses are lycaCed eless to seci other, oniy part of the oracepeteteialle reproved tn retesnsmisciano wiil bf ineluCed in thhireffsetiveneeo: the rest positions will be in direct connection with the base station. Basic model 2. Missing base/failure of the base station.
Themod eldemonstrates main possibilities of establishing connection when one btsestation faile.
Initial paeameyec va lues:theroutelengih nc °ns fey, iraee eicor n c övmeğe aiutaneu e = 40 hn, eepeeier coouragech etunces = 10 km, number of train repeaters N = 120 pc, base positions: {40, 120, 200, 360, 440,520, 600 km}, cycles number M=5000, analysis step Ax = 1 km. Visualization of the simulation objects locations
Fig. 13.Oneofmodelgeneratedrandomtrainallocations.Gray circlesarebases, blue-trainsinsidethebasecoverage(directconnections),green-withnetwork access through repeaters, red circles - offline trains.
Analysis results:
Connection probability for different retranslations numbers, P(x)
p(x)
t No retranslations allowed = lack of communication (on 12% of a path)
p(x)
♦ 12 retranslations = connection probability 35-85% on the problem area
F i g. 14. Model analysis result visualization: connection probability at each path point (P(x)): without retransmissions, with 1 retransmission allowed and with an unlimited number of allowable retransmissions
In defined model conditions retransmission system on the "problem” area provides at least 35% of the probability of establishing a connection (on average - in 51.6% cases). That means that the connection is partially restored on site: on average half the time the trainin thezoneof the missed base station network will be online. Surely, this does not replace the guaranteed availability of connection (since it relies on random positions of trains), but the mesh network system can act as a backup communication system in the event of a failure of the base station.
More realistic model
The simulation model with trains moving along the railway between stations provides an analysis of their radio communication with the base stations (directly or via repeaters) at various times. These trains move according to a timetable based on a real one (making stops of different duration at intermediate stations), and all types of trains are taken into account: long-distance trains that pass way in whole or in part, as well as suburban electric trains. The analysis is performed in 24 hours.
The basic analysis of realistic model is carried out similarly to the basic model, but the distribution of repeaters is no longer randomly, but corresponds to the schedule embedded in the simulation for each time point of the considered interval. Additionally, for each train, the time it was online using mesh network system and direct connectionwiththe basestation time is compared.
This model based on the main Oktyabrskaya railway system route (Moscow-St. Petersburg) with a length of 650 km as an example.
h t,tt% , 6t,tt% ■ 5t,tt%
et,tt%
3t,tt%
ut,tt%
1t,tt%
t,tt%
1t ut 3t et 5t 6t ht at 9t 1tt
Number of potential repeaters, N
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The coordinates of the base stations (their distance from the end points) aee selsetidin accordance with the rsally existing large rail-waystaZmns.
The Initial aatametors: the wnalyzea irng^l^ isA =s 650 km, the batg ctation ceveeage dtetance ss B = n0 km, the coatrage dittancc i)l tae repeates it f = 10 km, thr соordintCec op the Ifat<s slationf ai'e {0, :lciil, 209, 331, 532r n50 Asr), th e numbes oh smulation M =
5000, distance computation step: 1 km, time step is: 1 min.
Time=08:21
Щ Time - 501
[0. .1439] ■ So
Fig.15.Model visualization ехатрю. Theblackbordercorrespondsto the
railway (0.. L=650 km). Gray хігсіхр are bases, blue - trains inside the base
coverage (direct connections), gxeen - with network access through repeaters,
redcircles-offlinetrains
Trainschedule.
The actual schedule for onx x. the days (01/09/2018) was chosen as the initial data of train dispositions. From.x blic souixxs, model schedule was created for all passenger trains passing at least part of the way. The control points are station arrival and departure times for each train. Between the stations trains assumed to move uni-
formly within the model, that is, at a constant speed (including the passage of intermediate stations withoutstop).
Moscow Tver V.Volochek Bologoe M Uglovka
Train 0 km 967 km 286 km 331 km 381 km
dep. arr. dep. arr. dep. arr. dep. arr. dep.
116C 0:10 2:05 2:07 3:20 3:22 3:54 3:55
020U Megapolis 0:20 0:1- 2:15
016A «Arctic» 0:41 2:29 2:31 3:43 3:45 4:15 4:40
060*G «Volga» 0:44 2:37 2:39 4:23 4:25
030A 1:15 X:Xt 3:03 4:14 4:16 4:47 4:48 5:26 5:27
128A 1:25
062A 1:53 3:42 3:44 5:20 5:30
Fig. 16. Examplxpartof modxlusxd train schedule with the stations (and their positions), arrival and departure time for each train, that acts as a repeater
Several types of trains on the railway, acting as repeaters were considered (only a part of them are on the way at the same time):
• long-distance trains running the full path from start to finish - 94 pc (average amount on the railway is about 28 pieces at the same time);
• long-distance trains passing only part of the way - 41 pc (average amount on the railway is about 10 pieces at a time);
• electric trains (local trains) - 312 pc (average amount on the railway is about 18 pieces at a time).
• Further by default results for all types of trains ai'e given.
The tosieiots of some traits example
Long-distance X49A Long-distance 293S Long-distance 135S Long-distance 763A Long-distance [5[M Long-distance 116S Local 6631 Local 6630 Local 6533 Local 65x7 Local 6719 Local 6714
F ig.17.Model positionsintime visualizationforsome typceol trains:full-path long-distancetrains, part-pathlong-distancetrains andregional local trains (in different directions; some of themwith long-term staying on intermediate stations)
The tosieiots of some traits example
Time, О
Long-distance 049A Long-distance 293S Long-distance 135S Long-distance 763A Long-distance 151M Long-distance 116S
------Local 6631
------Local 6630
------Local 6533
------Local 6507
Local 6719 ------Local 6714
Fvll-taOh lotg-disOatce traits disOriOvOiot
Part-path lotg-disOatce traits disOriOvOiot
PosiOiot, x
Lets! tns'oa distribution
1,2%
1,0%
0,8%
0,6%
0,4%
0,2%
0,0%
0 100 200 300 400 500 600
і
'
5 A 1
JW
POf't'OOi t
A!! tns'os distribution
F i g. 18. Trains distribution: probabilitytofind a train of a certain type at random time at all positions
Modem Intormatiop eecEnolo-ieE and IT-Education
The Figure 19 shows that realistic di strib utions contain peaks of probability (corresponding to the stationb on which the trains are stayingttr attng ttme;that fact reducesbhe efficiency of retransmissions). But also their distribution diffebs from the uniform: only lott-disttnce trains runmng all the way from thnmitial to rlit fin^0 point are relatively close to a equable distribution.
So, the conclusions of the basic models are limited and atplicable to reality only qualitatively. Obviously further refinement of rhe motion modete (forexomple, mtleding to train schedule maermediate stations on wfich Phe trains do not snoe, auci therefote tda eotce-ednodmh data aaenotavaileMe foa pubhc acteesS wdl allow a moee сішИС^0.: unaiysie fos the atosedrnn ^losste t;o -ho reel Analyiio ctsu Its:
Fig.19.Probabilityoftheconnectionestablishment(averagedovertime)for each peint el Gcay indleatte diaect communicsSionwith Ше baoe section;
gseee - thooufh She retiansmisoionsohein.
Percent of trains online
45,00%
40,00%
35,00%
ooooooooooo
»нгчт^-ілюг-'оостіо
I I I I I I I I I V—I
ooooooooov
гІГМГП^іЛ'ІІГ^ООО
CD
Percent outinne online
Co nnitOoe pro baiiiUts oi poiiP of railway
Fig.20.Probabilityoftheconnectionestablishment(averagedovertime)for each point of the way. Gray indicates direct communication with the base station; green-throughlretransmission
Realistic model results comparable with basic models: the increase in the conMction probability on the path due to retransmission system is approximately 10% (of which about half is provided by 1 retra петлею n).
The presence of defined moving trains and the timetable for their moveme5t m the model makes possible to estimate an important parameter: the additional time that the train is on (potential) com-municaticmwith base stations due to retransmissions and compare it with such time without them.
Within the model, the average online time increase for all trains is 14.8% due to mesh network, while:
• for 30% trains there is no increase;
• for 30% trains online time intrefsen by 10-20%;
• for 20% more trains - 20-30%;
• for 10% more trains - by 10%.
Thus, mesh network features can give a significant increase in the time at which many trains on the railway are online in the network.
ro retransmission-
retransmission-
■ 30-40% uptime
40-50%
uptime
irceoaao
more 50% uptime
Fig. 21. Efficiency ofretransmissions:increasingthe proportion of time online
Современные
инФормєциєнньіє
тєхнрюгир
иИТ-сбрюзосание
Том 15, № 2. 2019 ISSN 2411-1473 sitito.cs.msu.ru
Model limitations:
• One-dimensional linear motion.
The model considers the only one variable coordinate of the repeater on a straight line path, and also considers linear changing of it (the reference railway is really quite straightforward on a large scale, but generally speaking, the railways are two-dimensional at least and could have even three dimensions when passing a terrain with a large difference in altitude). In some cases, taking into account the nonlinearity of the path could force to increase/decrease results, since the movement along the straight line corresponds to the maximum rapid removal and earlier exit from the base station coverage, but also does not take into account the additional different disturbances.
• Simplified trajectories of the trains: even movement (no change in speed except stations) and deterministic (without occasional deviations from the schedule).
• Not taken into account obstacles and interference, as well as the direction diagram of the signal source (that leads to indeterminate actual boundaries of the coverage area of the stations, determined by an acceptable signal-to-noise ratio).
• The really used equipment of base stations and repeaters and their practical coverage distance and other characteristics are not discussed.
• The location of the base stations is largely arbitrary (even in realistic model), since the purpose is to demonstrate the principal opportunities for improving communication by retransmitting mesh networks. In particular, it is possible to provide a complete network connection on the railway, when only the reserve channel function remains for retransmissions.
Possible further modifications.
For a deeper exploring of the mesh network capabilities for railways, or to analyze the practical possibilities for certain cases, further model changes are possible in order to improve accuracy:
• More detailed train schedule (intermediate stations without stay, other control points).
• Accounting for irregularities in the movement (random deviations from the schedule).
• Random deviations of the coverage distances of base stations and repeaters (or probability distribution depending on remoteness).
Also important possibility is to transfer packages offline: via repeaters, which are not currently in communication, but are waiting for it in the near future. This may be relevant for the transmission of GAT data, for example, in the areas of failure of the network infrastructure.
Conclusions.
The presented theoretical and simulation-based results allow predicting efficiency increase for railway radio communication network due to the implementation of the mesh network features. Mesh network allow restoring communication in the areas of the base station failure or in the case when a train suddenly stops out of direct connection with the base station for any reason. In this case, the neighboring repeater-train will help to establish the connection of the train with the CSC.
Also mesh network significantly increases the functional coverage of base stations (from 10% and higher), wherein the additional costs of implementing a mesh network features may be minimal
(depending on the digital radio standard used).
Mesh network could become a way to solve some typical problems
of data transmission of GAT related to linear or ring circuits.
References
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Modern Information Technologies and IT-Education
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Submitted 12.01.2019; revised 24.04.2019; published online 25.07.2019.
bout the authors:
Donat M. Schneps-Schneppe, Senior Manager, AbavaNet (34 Narodnogo Opolcheniya St., Moscow 123423, Russia), ORCID: http://orcid.org/0000-0001-9775-3292, donat.shneps-shneppe@ abava.net
Eugene O. Tikhonov, Technical Director, AbavaNet (34 Narodnogo Opolcheniya St., Moscow 123423, Russia), ORCID: http://orcid. org/0000-0002-2115-6528, [email protected]
All authors have read and approved the final manuscript.
Список использованных источников
[1] Smith K. Beyond GSM-R: the future of railway radio // International Railway Journal. March 01, 2017. URL: https://
www.railjournal.com/in_depth/beyond-gsm-r-the-future-of-railway-radio (дата обращения: 12.01.2019). Sneps-Sneppe M., Namiot D. On 5G Projects for Urban Railways // 2018 22nd Conference of Open Innovations Association (FRUCT). Jyvaskyla, 2018. Pp. 244-249. DOI: 10.23919/FRUCT.2018.8468290
Розенберг Е. Н, Дзюба Ю. В., Батраев В. В. О направлениях развития цифровой железной дороги // Автоматика, связь, информатика. 2018. № 1. С. 9-13. URL: https:// elibrary.ru/item.asp?id=32245249 (дата обращения:
12.01.2019).
Memorandum: Soren Degnegaard // ERTM Level 2 for large stations and junction areas, Banedanmark, 2008.
Wu H, Gu Y., Zhong Z. Research on the Fast Algorithm for GSM-R Switching for High-speed Railway // Journal of Railway Engineering Society. 2009. No. 1. Pp. 92-98.
Zhong Z.-D. et al. Chapter 2. Key Issues for GSM-R and LTE-R. // Dedicated Mobile Communications for High-speed Railway, Advances in High-speed Rail Technology. Beijing Ji-aotong University Press and Springer-Verlag GmbH Germany, 2018. Pp. 19-55. DOI: 10.1007/978-3-662-54860-8_2 Sun T., Zhou K, Luo X., Huang Y Research on the Fast Handover Algorithms of GSM-R for High-Speed Railway // 2015 International Conference on Network and Information Systems for Computers. Wuhan, 2015. Pp. 213-218. DOI: 10.1109/ICNISC.2015.68
[8] Ding Lu, Wei Wen Jun. Research on optimal method for GSM-R double-layer handover for railway // Railway Computer Application. 2010. Vol. 19, Issue 12. Pp. 9-11.
[9] Sniady A., Soler J. An overview of GSM-R technology and its shortcomings // 2012 12th International Conference on ITS Telecommunications. Taipei, 2012. Pp. 626-629. DOI: 10.1109/ITST.2012.6425256
[10] Banerjee S., Hempel N., Sharif H. A Survey of Wireless Communication Technologies & Their Performance for High Speed Railways // Journal of Transportation Technologies. 2016. Vol. 06, No. 1. Article ID: 62604. DOI: 10.4236/ jtts.2016.61003
Вишневский В. М., Кришнамурти А., Козырев Д. В., Ларионов А. А., Иванов Р Е. Методы исследования и проектирования широкополосных беспроводных сетей вдоль протяженных транспортных магистралей // T-Comm: Телекоммуникации и транспорт. 2015. Т. 9, № 5. С. 9-15. URL: https://elibrary.ru/item.asp?id=23734337 (дата обращения: 12.01.2019).
[12] Tingting G., Bin S. A high-speed railway mobile communication system based on LTE // 2010 International Conference on Electronics and Information Engineering. Kyoto, 2010. Pp. V1-414-V1-417. DOI: 10.1109/ICEIE.2010.5559665
[13] Han J., Zhou K. Interference research and analysis of LTE-R // 2013 5th IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications. Chengdu, 2013. Pp. 732-734. DOI: 10.1109/MAPE.2013.6689858
[14] Намиот Д. Е., Кутузманов З. М., Федоров Е. А., Покусаев
О. Н. Об оценке социально-экономических эффектов городской железной дороги // International Journal of Open Information Technologies. 2018. Т. 6, № 1. С. 92-103. URL: https://elibrary.ru/item.asp?id=32314918 (дата
обращения: 12.01.2019).
Современные информационные технологии и ИТ-образование
Том 15, № 2. 2019 ISSN 2411-1473 sitito.cs.msu.ru
[15] Мишарин А. С., Покусаев О. Н., Намиот Д. Е., Катцын Д. В. О моделировании пассажирского потока для высокоскоростных железных дорог // International Journal of Open Information Technologies. 2018. Т. 6, № 5. С. 15-20. URL: https://elibrary.ru/item.asp?id=34865313 (дата обращения: 12.01.2019).
[16] Ефанов Д. В. Функциональный контроль и мониторинг устройств железнодорожной автоматики и телемеханики. СПб.: ФГБОУ ВО ПГУПС, 2016. 171 с.
[17] Shneps-ShneppeD. On Digital Signaling for Moscow City Railways // International Journal of Open Information Technologies. 2018. Т. 6, № 6. С. 28-37. URL: https://elibrary.ru/ item.asp?id=35050445& (дата обращения: 12.01.2019).
[18] Qaddus A. Real Time Performance Analysis of Digital Mobile Radio (DMR) and APCO Project 25 (P-25) Radio Systems in Land Mobile Radio (LMR) Systems // International Journal of Computer Engineering and Information Technology. 2016. Т. 8, № 3. С. 49-55. URL: http://www.ijceit.org/pub-lished/volume8/issue3/3Vol8No3.pdf (дата обращения:
12.01.2019) .
[19] Zhu Q., Jiang Xin-hua, Zou Fu-min Experimental Research on the Influence Factors in the Multi-hop Multi-radio Mesh Network // Science Technology and Engineering. 2008. Vol. 21. URL: http://en.cnki.com.cn/Article_en/CJFDTotal-KX-JS200821017.htm (дата обращения: 12.01.2019).
[20] Matsumoto M., Nishimura T., Hagita M., Saito M. Cryptographic Mersenne Twister and Fubuki Stream/Block Cipher // Cryptology ePrint Archive, Report 2005/165. 2005. URL: https://pdfs.semanticscholar.org/60c7/518d60b6b-53f8344c4bff116240a88132fa4.pdf (дата обращения:
12.01.2019) .
Поступила 12.01.2019; принята к публикации 24.04.2019; опубликована онлайн 25.07.2019.
|0б авторах:|
Шнепс-Шнеппе Донат Манфредович, старший менеджер, AbavaNet (34 Narodnogo Opolcheniya St., Moscow 123423, Russia), ORCID: http://orcid.org/0000-0001-9775-3292, donat.
Тихонов Евгений Олегович, технический директор, AbavaNet (34 Narodnogo Opolcheniya St., Moscow 123423, Russia), ORCID: http://orcid.org/0000-0002-2115-6528, eugene.tikhonov@abava. net
Все авторы прочитали и одобрили окончательный вариант рукописи.
Modern Information Technologies and IT-Education
