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A novel handover scheme using torch nodes and adaptive measurement aggregation mechanism to improve QoS in high-speed railway communication

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Abstract

Technological advancement in the field of transportation and communication is happening at a faster pace in the past few decades. As the demand for high-speed transportation increases, the need for an improved seamless communication system to handle higher data traffic in a highly mobile environment becomes imperative. This paper proposes a novel scheme to enhance the quality of service in high-speed railway (HSR) communication environment using the concept of torch nodes (TNs) and adaptive measurement aggregation (AMA). The system was modeled using an object-oriented discrete event simulator, and the performance was analyzed against the existing single-antenna scheme. The simulation results show that the proposed scheme with its minimal implementation overhead can efficiently perform seamless handover with reduced handover failure and communication interruption probability.
A novel handover scheme using torch nodes and adaptive
measurement aggregation mechanism to improve QoS in
high-speed railway communication
P. J. Pramod
1
B. C. Jinaga
2
Received: 24 April 2017 / Revised: 9 November 2017 / Accepted: 15 November 2017
The Author(s) 2017. This article is an open access publication
Abstract Technological advancement in the field of
transportation and communication is happening at a faster
pace in the past few decades. As the demand for high-speed
transportation increases, the need for an improved seamless
communication system to handle higher data traffic in a
highly mobile environment becomes imperative. This
paper proposes a novel scheme to enhance the quality of
service in high-speed railway (HSR) communication
environment using the concept of torch nodes (TNs) and
adaptive measurement aggregation (AMA). The system
was modeled using an object-oriented discrete event sim-
ulator, and the performance was analyzed against the
existing single-antenna scheme. The simulation results
show that the proposed scheme with its minimal imple-
mentation overhead can efficiently perform seamless han-
dover with reduced handover failure and communication
interruption probability.
Keywords High-speed railway Cellular wireless
technology Long-term evolution Mobile relays
Handover scheme Quality of services
1 Introduction
The twenty-first century is experiencing tremendous
growth of data and Internet services [1] to meet the sig-
nificant rise in socioeconomic developmental needs [2] and
user demand. Smart devices demanding cellular wireless
connectivity are increasing exponentially and have crossed
the current world population [3]. Wireless networks are
also enhancing its capability to handle more devices, users
and larger data traffic.
Advancement in high-speed railway (HSR) transporta-
tion has resulted in more passengers transiting through
railway networks [4]. HSR is currently becoming more and
more popular, and this mode of public transportation is
preferred in several countries due to its speed, safety,
energy efficiency and larger passenger handling capacity
[59]. The demand for high-quality video, voice and data
over broadband wireless communication in an HSR envi-
ronment has thrown open various limitations of cellular
wireless technology.
The LTE-Advanced standardization was through 3GPP
release 10 version of specification has introduced long-
term evolution-advanced (LTE-Advanced) [10,11] which
provides better bandwidth, higher efficiency and enhanced
intercell interference coordination (eICIC). The data rates
were enhanced to 1 Gbps (downlink, DL)/500 Mbps
(uplink, UL) for low mobility application and 100 Mbps
(DL)/50 Mbps (UL) for high mobility application [12]
along with an increase in requirements of peak spectral
efficiency to 30 bps/Hz (DL)/15 bps/Hz(UL). This
enhancement has put forward significant implementation
challenges to HSR system designers [13].
Figure 1shows the architecture of LTE-Advanced with
two distinct components: (1) evolved universal terrestrial
radio access network (E-UTRAN) and (2) evolved packet
&P. J. Pramod
pramodpj@cdac.in
B. C. Jinaga
jinagabc@gmail.com
1
Electronic System Design and Manufacturing (ESDM)
Group, Centre for Development of Advanced Computing (C-
DAC), Plot No. 6 and 7, Hardware Park, Hyderabad,
Telangana 500005, India
2
Electronics and Communication Engineering Department,
Jawaharlal Nehru Technological University Hyderabad,
Kukatpally, Hyderabad, Telangana 500085, India
123
J. Mod. Transport.
https://doi.org/10.1007/s40534-017-0152-8
core (EPC) [14]. The EPC consists of mobility manage-
ment entity (MME), serving gateways (S-GW) and packet
data network gateway (P-GW) which provide services like
signaling, handover, security, whereas the E-UTRAN
incorporates multiple interconnected evolved NodeBs
(eNBs) [15]. These eNBs are interconnected using X2
interface, whereas they are connected to EPC through S1
interface.
A highly mobile HSR scenario involves long narrow
strips, bridges, viaducts and directional antennas with
reduced cell coverage. The deployment of wireless net-
works for such a scenario is challenging due to increased
handover (HO) frequency resulting in significant perfor-
mance degradation [16]. To make the condition worse, the
implementation of HO in LTE-Advanced is a hard HO
which requires breaking the radio link with source before
connecting with target eNB. Frequent HOs in such tradi-
tional networks would increase the network load and power
consumption of user equipment (UE), thereby affecting the
overall quality of services (QoS) [17]. Group HO, frequent
HO at short time intervals, Doppler frequency shift, pen-
etration path loss and fading in propagation characteristics
due to shielded carriage of trains, viaduct, hilly terrain and
tunnel [18,19] are major concern for system designers in a
high-speed scenario.
In order to improve communication in a long-distance
HSR scenario, leaky coaxial cable (LCX)-based radio
communication system [20] was introduced to provide
better bandwidth and efficient frequency reuse. The need
for repeaters to compensate for transmission losses, high
maintenance cost and large deployment cost limits the
acceptance of LCX system for high-speed train-ground
information transmission. Radio-over-fiber (RoF)-based
system [21,22] with remote antennal units (RAU)
deployed along railway lines to transmit data wirelessly to
the onboard unit is another promising technology for HSR
communication. Support for higher bandwidth, cost-effec-
tiveness, reduced power consumption due to linear radiated
antenna, and reduced HO are the major features of RoF
technology [23,24].
Introduction of wireless local area networks (WLAN) to
complement satellite communication in HSR scenario by
M. Han et al. [25] was another significant work to over-
come the limitation of HO and coverage. However, the
bandwidth limitation, inherent delay in satellite-based
system, blind spots, initial investment cost and requirement
of line of sight have confined the scalability of this model
in HSR.
A seamless HO scheme based on dual-link architecture
was proposed by Lin Tian et al. [26]. The system with two
antennas in the front and rear takes advantage of bi-casting
and dual antennas to implement soft HO with reduced
overhead and latency.
3GPP TR-36.836 has introduced mobile relays as base
station [27] to circumvent the connectivity issues in HSR.
These multi-RAT relays would provide wireless connec-
tivity and services to onboard UE. Such a shift in con-
nectivity maintenance from portable mobile devices to
relays has significantly reduced the UE power consumption
[28], signal storming or group HO [29], Doppler frequency
shift and penetration path loss [30]. Though mobile relays
have improved the performance between UE and eNB, the
HO issues limiting the performance and reliability persist.
Introducing relays as an intermediate node has only shifted
the HO issues from UE to relay nodes. Increased load on
these nodes has further deteriorated the packet latency,
QoS, frequent HO and resilience capability of the overall
system.
An effective two-link architecture based on distributed
antenna system (DAS) and mobile relay was introduced by
Liu et al. [31]. Onboard devices in this system are con-
nected to train relay nodes which are further interfaced to
remote central station using multiple RAUs based on RoF
technology. However, the proposed system has neglected
the period of HO, which significantly affects the perfor-
mance in real networks [32]. An enhanced HO scheme [33]
was proposed using special control mobile relays (cMRs)
equipped in front of a train and several mobile relays were
distributed across the train. This scheme also proposed an
enhanced measurement procedure to reduce the duration of
cMR signal measurement based on the direction of
movement. The cMR-based scheme is effective in reducing
the signaling overhead and HO interruption time, whereas
MME/S-GW MME/S-GW
S1 S1
S1
S1
X2
X2 X2
eNB
eNB
eNB
EPC
E-UTRAN
Fig. 1 LTE-Advanced network architecture
P. J. Pramod, B. C. Jinaga
123 J. Mod. Transport.
failure of HO at cMR would inherently affect the overall
connectivity of the system.
In this paper, in order to overcome the limitations of
existing systems, we introduce a novel HO scheme to
enhance the QoS in an HSR communication environment
by proposing the concept of torch nodes (TNs) and
mobility-based adaptive measurement aggregation (AMA)
to improve the existing HO mechanism. By introducing
this approach through a distributed mobile relay (DMR)-
based architecture, we also address the resilience capability
in HSR systems.
The rest of the paper is organized as follows. In the next
section, we present our proposed solution, describing the
system architecture and operational procedures. Various
stages of the proposed HO scheme are elaborated in
Sect. 3. Section 4details the AMA mechanism. Imple-
mentation of simulation model and performance analysis
will be carried out in Sect. 5. Finally, in Sect. 6we sum-
marize our results and present our conclusions.
2 Proposed system
Considering the rapid proliferation of smart devices among
travelers and passenger accommodation capacity in high-
speed trains, an onboard distributed relay mechanism is
proposed for HSR as shown in Fig. 2. The DMR nodes
mounted on trains will act as relay nodes and equip the
system to be resilient toward single-point failures. DMRs
are further interfaced to the backhaul using WLAN Link
(LTE-LAA) or LTE-Advanced.
Torch nodes (TNs) equipped in the front (TN-1) and rear
(TN-2) of the train act as measurement nodes to provide
prior information of donor eNBs (DeNBs) in a highly
mobile environment. TNs report the measurement values to
the onboard processing unit (OPU), which further uses this
information for HO decision of respective DMRs. A global
positioning system (GPS) integrated inertial measurement
unit (IMU) is used to determine the speed of train. This unit
is interfaced to OPU.
The OPU carries out two independent functionalities.
The load balancer module of OPU effectively distributes
the signaling load across multiple DMRs, whereas the
measurement engine processes measurement details from
TNs and DMRs based on speed of train and generate DMR-
specific measurement report to be forwarded to respective
DeNBs. OPU is connected with nodes using optical med-
ium for faster data transfer and incorporates interface
modules for TNs, DMRs, APs and IMU. Based on load
sharing and network topology requirements, the OPU can
be specific for each DMR node or a group of DMRs can
share an OPU along with IMU. The block diagram of OPU
is depicted in Fig. 3.
Based on the load being handled by respective DMRs,
the OPU will dynamically link UEs to respective DMRs,
thereby curbing the issue of overload. The onboard UEs are
interfaced to DMRs via OPU through WLAN access points
(APs) deployed across carriages.
When the train is at a higher speed, the measurement
details of TNs will provide prior information of upcoming
DeNBs to which HO needs to be initiated. Leveraging this
information will provide sufficient lead time for DMRs in
DeNB 1 DeNB 2 De NB3
DMR-1
AP1 AP2 AP3 APm
TN - Tor c h node
DMR - Dis t r ib u ted mob ile rel ay
AP - Access point
TN-1 TN- 2DMR-n
DeNB - LTE-Advanced base station
OPU - On boar d pr oc es s ing u nit
OPUIMU
Fig. 2 System architecture
A novel handover scheme using torch nodes and adaptive measurement aggregation mechanism to
123
J. Mod. Transport.
initiating and executing HO in a highly mobile HSR
environment. At lower speeds or when the train is sta-
tionary, the signal strength information from respective
DMR will be given preference while estimating measure-
ment reports.
Based on velocity readings from IMU, the OPU pro-
vides a mobility-based adaptive measurement aggregation
mechanism of values collected by TNs and DMRs to
generate periodic- or event-based measurement report. This
adaptive reporting strategy based on speed of train will
facilitate DMRs to effectively speculate the upcoming
DeNBs and initiate the HO early.
3 Stages of proposed HO scheme
The handover scheme proposed has the following three
stages: (1) HO preparation, (2) HO execution and (3) HO
completion.
3.1 HO preparation stage
LTE-Advanced adopts a UE assistance-based network-
controlled hard HO procedure. In the context of HSR, the
relay nodes deployed in train will take over the connec-
tivity aspect from UEs, by acting as enablers between UE
and DeNB as shown in Fig. 4. The DMRs will start its
measurement procedure after receiving a measurement
control command from the serving DeNB (S-DeNB). The
DMRs will forward this measurement control command to
OPU for configuring the TNs and IMU for initiating
measurement in those nodes.
The measurement of DMRs, TNs and IMU will be
forwarded as per pre-configured interval to the measure-
ment engine module of OPU. This module implements an
AMA mechanism based on the speed of train. Priority
toward DMR measurement will be given at a time wherein
the train is stationary or at lower speed. When the train
attains moderate or higher speeds, AMA mechanism will
give preference to readings from TNs, thereby facilitating
an early reporting mechanism. This will provide
TN int er f ac e DMR inter f ac e
AP interface
IMU interface
Measurement
engine
Load
balancer
Fig. 3 Onboard processing unit
SGW/PGW (DMR) UE1 TNs IMU OPU DMR S-DeNB T-DeNB MME
Mst. c ontrol
Packet data Packet data
Speed
TN details DMR details
Mst. v alues
Mst. report
HO request
HO ACK
RRC Reconf ig.
Mst. engine
HO decision
Adm. c ontrol
SGW/PGW (UE2)
Fig. 4 Handover preparation stage
P. J. Pramod, B. C. Jinaga
123 J. Mod. Transport.
E-UTRAN and EPC with sufficient lead time in completing
the HO procedures.
The OPU/DMR can be configured for periodic- or
event-based reporting as per the measurement control
command provided. Periodic configuration ensures that the
OPU/DMR will report the measured signal strength values
of target DeNB (T-DeNB) to S-DeNB in a fixed report
interval (RI). S-DeNB performs HO when the signal
quality of T-DeNB is above a threshold for continuous
kreports, where the value of kis defined by cellular
operator. During event-based reporting, the measurement
control command will carry the appropriate event types and
time-to-trigger (TTT) values.
Based on the LTE-Advanced radio resource control
(RRC) specification, A3, A4 and A5 are the three event
types defined to trigger the measurement reports.
3.2 Handover execution stage
As soon as the DMR receives the RRC reconfiguration
message, the device detaches from S-DeNB. Further, it
uses the configuration details to synchronize with the
T-DeNB by sending contention-free-based random access
preamble message. At the same time, the S-DeNB forwards
the buffered data and status transfer command to T-DeNB.
Once successfully synchronized, the DMR sends a tracking
area update to MME along with RRC connection config-
uration complete message. This will establish the uplink
communication between DMR and T-DeNB.
3.3 Handover completion stage
Based on the tracking update message from DMR, the
MME updates the DMR location and replies with a
tracking area update accept command to the DMR. The
T-DeNB will also send a path switch request message to
inform the MME that the S-DeNB of the DMR has chan-
ged and the routing path needs to be modified. Then, the
MME issues a user plane update request command to
S-GW to switch the routing path. A successful update will
result in S-GW replying with a user plane update response
command to the MME and MME further notifying
T-DeNB using a path switch request acknowledgement
(ACK). This would enable the T-DeNB and S-GW to
forward data to DMR along the new path. Further, T-DeNB
sends a context release message to request S-DeNB in
releasing the context of DMR. This will complete the HO
process. HO execution and completion stages are depicted
in Fig. 5.
As observed, the proposed methodology will only
modify the HO preparation stage of LTE-Advanced for
reducing latency and improving the HO failure rates. Due
to this strategy, the proposed mechanism can be easily
adopted in the existing implementation with little or no
modification in the mobile relay-based infrastructure setup.
By adopting an AMA-based HO foreseeing approach, the
system adapts itself to the dynamic nature of HSR
environment.
Modify bearer resp.
Uplink delay
End marker
Path switc h req.
Sy nchronization
Data f orwarding
SN st atus trans f er
UL allocat ion
RRC Conn.
Handover ex ecut ion
Packet data
Modify bearer req.
End marker
Packet data
Path switch ACK
Contex t releas e
Packet data
Packet data
Handover completion
Downlink delay
Detac h f rom old
cell &sy nc to new
cell
Deliv er buff ered
in transit packets
to T-DeNB
Buf fer pac kets f rom S-D eNB
Release res ources
Switch DL pat h
UE1 DMR S-D eNB T-DeNB MME SGW/ PGW (D MR) SGW/PGW (UE2)
Fig. 5 Handover execution and completion stage
A novel handover scheme using torch nodes and adaptive measurement aggregation mechanism to
123
J. Mod. Transport.
4 AMA mechanism
The adaptive measurement aggregation is a mechanism
with which the DMR decides the measurement parameters
to be reported to the S-DeNB. The decision in this regard
will give due consideration to the mobility aspects of train
and implements a predictive approach at higher speeds by
correlating the measurement values of TNs along with
DMR measurements.
4.1 Measurement parameters
According to 3GPP, reference signal received power
(RSRP) and reference signal received quality (RSRQ) are
the major DMR-related values which need to be considered
as measurement parameters in LTE-Advanced.
The RSRP measurement, R
P
, is the linear average of the
power contributions by cell-specific resource elements that
carry reference signals within the measurement frequency
bandwidth as shown in Eq. (1). For absolute RSRP, the
requirement would vary from ±6to±11 dB, whereas a
relative measurement requirement varies from ±2
to ±3 dB for intra-frequency and widens to ±6 dB for
interfrequency measurement. The RSRP measurements are
further mapped to integer numbers, whose value ranges
from 0 to 97 before they are included in the RRC messages.
RP¼PTX TLS fðl;rÞ;ð1Þ
where P
TX
is the transmission power of DeNB, T
LS
is the
path loss of the signal between DeNB and DMR and f(l,r)
is the shadow fading which usually follows Gaussian
distribution with mean lbeing zero and variance r
2
. For
illustration, the path loss in dB [34] for a line of sight
DeNB-DMR to model the propagation environment is as
follows:
TLS ¼22 lg dþ28:0þ20 lg FR;10 m\d\dBP;
ð2Þ
where F
R
is the frequency (Hz); d
BP
is the breakpoint
distance; the distance dbetween DMR and DeNB is
estimated as
d¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
ðytyiÞ2þðxtxiÞ2
q;ð3Þ
where (x
t
,y
t
) describes the position of DMR at time tand
(x
i
,y
i
) defines the location of DeNB
i
.
RSRQ is a cell-specific signal quality metric, expressed
in dB, which is defined as N
RB
R
P
/R
S
, where N
RB
is the
number of resource blocks over which the measurement is
conducted, and R
S
is the RSSI
E-UTRA
parameter which
represents the entire received power from all interference
and thermal noise source. In LTE-Advanced, the RSRQ
measurement is also mapped from dBm to an integer
number ranging from 0 to 34.
Since RSRQ measurement combines signal strength and
interference levels, this parameter is significant in assisting
the mobility management in E-UTRAN. Mathematically,
as the RSRQ measurement is proportional to the RSRP and
signal strength, the current implementation considers
RSRQ as the key measurement parameter along with
mobility to implement the AMA mechanism. This opti-
mizes and provides a fast, simplified and efficient aggre-
gation and reporting mechanism.
In order to implement an effective HO mechanism for
HSR, parameters with regard to mobility and service
quality should also be considered while generating mea-
surement reports. Such multi-criteria approach will provide
an effective solution to enhance HO efficiency and increase
resource utilization. In the current effort, the implementa-
tion consideration with regard to service quality is beyond
the scope and will be addressed through a separate paper.
4.2 AMA based on HSR mobility
In a realistic LTE-Advanced scenario, the network will
combine multiple radio access technologies (RATs), fre-
quencies and cell sizes for efficient deployment [35] and
the UEs carry out parameter measurement for multi-RAT
intra-/interfrequency mobility. For elaboration simplicity,
we consider interfrequency E-UTRAN HO process in the
current context, whereas the proposed system with minimal
enhancement can also be employed for inter-RAT HO
mechanism.
Measurement reporting in LTE-Advanced can be con-
figured as periodic, event triggered or event-triggered
periodic. Triggering events as defined by 3GPP for moni-
toring the quality of serving cell and target cell are given in
Table 1and are calculated based on the entering conditions
as elaborated in TS 36.331.
The triggering events as defined for LTE-Advanced are
more suitable for low mobility scenarios, whereas their
applicability in a highly mobility environment like HSR
requires considerable modification. Along with the mea-
surement parameters as observed from target and serving
cells, it is indispensable that the system should also con-
sider the velocity of high-speed train (HST) to dynamically
adapt the triggering events in a highly mobile environment.
Considering various mobility scenarios in HSR, the varia-
tion in event triggering based on HST speed, S, is identified
as follows:
(1) Movement of HST at lower speed (S
Low
)
When stationary or at a lower speed than a threshold level
(for example 200 km/h), the event triggering is considered
P. J. Pramod, B. C. Jinaga
123 J. Mod. Transport.
based on the standard LTE-Advanced mechanism as
detailed in Table 1.
(2) Movement of HST at higher speed (S
High
)
At an increased mobility scenario wherein the value of
S
High
increases beyond a threshold level (for example,
200 km/h), it is essential for relay nodes to foresee the
parameters of upcoming DeNB’s and correlate the data
with the measurements of DeNB’s which are left behind to
have an effective HO decision. Considering the assumption
that the DeNBs deployed in an HSR is directional and
continuous, the TNs deployed in the front and back of the
train provide sufficient visibility to the futuristic and past
parametric information.
In order to exemplify the above, we denote by R
Q1-FTN
,
R
Q1-RTN
and R
Q1-DMR
the RSRQ measurements as observed
by front TN, rear TN and DMR for S-DeNB, respectively,
and by R
Q2-FTN
,R
Q2-RTN
and R
Q2-DMR
the counterparts as
reported for T-DeNB. A parameter pattern, R
Q1-RTN
C
R
Q1-DMR
CR
Q1-FTN
, being reported for S-DeNB node
observed for TTT duration, can be inferred to be a condi-
tion wherein the train is leaving the vicinity of a cell.
Meanwhile, R
Q2-FTN
CR
Q2-DMR
for the T-DeNB node
indicates that the train is entering the cell.
Considering this aspect, the HO event generated at HO
initiate time for DMR-TN, T
HS-initiate
, as shown in Eq. (4)
provides a realistic and accurate HO decision-making
scenario, in comparison with HO initiate time, T
HO-initiate
,
as recommended by 3GPP standard where event triggering
occurs whenever the T-DeNB is better than the S-DeNB.
RQ1-RTN [RQ1-DMR RQ1-FTN
ðÞAND RQ2-FTN [RQ2-DMR
ðÞ:
ð4Þ
In such a scenario, it is ideal to have the HO initiated at
time T
HS-initiate
, which is DTduration prior to the time
T
HO-initiate
as defined by the 3GPP specification. This would
provide sufficient lead time in initiating the HO procedure
in a high mobility HSR scenario. Moreover, the proposed
method envisages significant reduction in the time for
DMR to reenter (T
Reentry
) and the time to re-establish the
corresponding DMR connection during call drop
(T
Reconnect
)
THS-initiate ¼THO-initiate DT:ð5Þ
In contrast to the conventional approach of taking
measurement parameters from a single MRN, it is essential
to adapt to the varied mobility conditions and estimate the
parameter values dynamically. Though various approaches
can be applied to generate events as mentioned in Eq. (4), a
weighted average mechanism to aggregate the S-DeNB and
T-DeNB measurements across front TN (TN-1), rear TN
(TN-2) and DMR is adopted here as shown in Eq. (6). The
weights are determined on the basis of mobility conditions
of HST.
RQ-MN ¼W1RQ-DMR þW2RQ-FTN þW3RQ-RTN;ð6Þ
where R
Q-MN
is the aggregate RSRQ measurement to be
reported for event triggering, and W
i
(i=1, 2, 3) is the
significance parameter.
5 Simulation and performance analysis
5.1 Implementation of simulation model
The proposed model was designed and implemented on an
object-oriented discrete event simulator [36] extended with
an LTE-Advanced package [37]. A representative illus-
tration of the simulation environment on Omnet??
involving a train traveling in an HSR environment between
two stations is presented in Fig. 6a. The simulated infras-
tructure consists of DeNBs, Routers, P-GW and Server.
The DeNBs uses omnidirectional anisotropic antennas and
are interconnected through X2 interface.
Table 1 Event triggers for measurement report
Event Description
Inter-LTE mobility
A1 S-DeNB better than absolute threshold
A2 S-DeNB worse than absolute threshold
A3 T-DeNB better than offset relative to S-DeNB
A4 T-DeNB better than absolute threshold
A5 S-DeNB worse than one absolute threshold (AT1) and T-DeNB better than another absolute threshold (AT2)
A6 T-DeNB better than offset relative to secondary DeNB
Inter-RAT mobility
B1 T-DeNB better than absolute threshold
B2 S-DeNB worse than one absolute threshold AT
R1
and T-DeNB better than other absolute threshold AT
R2
A novel handover scheme using torch nodes and adaptive measurement aggregation mechanism to
123
J. Mod. Transport.
As shown in Fig. 6b, the implementation of onboard
train network involves front torch nodes (TN-1), rear torch
nodes (TN-2), two distributed mobile relay nodes (DMR-1
and DMR-2), onboard processing units (OPU1 and OPU2)
and train networks (TNET1 and TNET2). Figure 6c shows
the implementation of TNET which establishes LAN
connectivity across multiple coaches. TNETs are further
interfaced to the UEs through wireless APs as shown in
Fig. 6d. IMU unit was implemented as a module in OPU,
and implementation of load balancer was simplified to
handle individual DMR. Table 2summarizes the simula-
tion parameters. The simulation uses ITU Urban Macro
[38] for path loss and Jakes fading model [39].
5.2 Simulation results
We validated the model and carried out simulations to
assess the performance of the proposed system in
improving the HO latency and HO failure probability.
Performance of the proposed model is compared with that
of the single link mobile wireless relay node (MRN). The
MRN uses only single wireless link to connect to DeNB, in
comparison with the proposed DMR-TN system, which
involves TNs for efficient estimation of measurements in a
mobile environment, multiple antenna scheme to enhance
the load distribution, enhanced monitoring using AMA and
efficient message handling capabilities.
Fig. 6 Omnet?? simulation screenshot. aHSR simulation between two stations. bSimulated onboard train network. cLAN network across
coaches. dWireless LAN connectivity at coaches
P. J. Pramod, B. C. Jinaga
123 J. Mod. Transport.
(1) HO latency
The HO latency is computed from the time when the S-
DeNB begins its HO to the time when the connection is
established for data transmission to T-DeNB. The HO
latency THO-latency is estimated as follows:
THO-latency ¼PSHO THO
þ1PSHO ðTReentry þTReconnect

;ð7Þ
where the T
HO
is the time taken to handover; P
SHO
is the
probability estimate value for calculating the average HO
latency, and is considered based on [26,40]. The proba-
bility estimate of successful handover for MRN scheme,
P
SHO-MRN
, is derived as 0.97, and the probability estimate
of successful handover for DMR-TN, P
SHO-DMR-TN
,is
0.999. The HO in the proposed approach significantly
reduces the T
Reentry
and T
Reconnect
and increases the prob-
ability of success at each stage. The onboard measurement
analyzer and multi-antenna with load balancer have
reduced the HO latency in comparison with the existing
systems.
Figure 7illustrates the HO latency of the simulation run
wherein the proposed DMR-TN scheme outperforms the
single-antenna-based MRN scheme. Although users with
high mobility are expected to experience an increase in HO
latency, the HO latency in the proposed solution is com-
paratively smaller and increases gradually as the speed
increases.
(2) HO failure probability
Once HO is triggered, any subsequent degradation of
T-DeNB signal strength below a threshold level will result
in connection losses and an HO failure will occur if this
interruption exceeds the predefined delay limit. In the
proposed scheme, the measurement report from TNs
provides a further assurance in estimating the T-DeNB,
resulting in significant reduction in HO failures. Figure 8
shows that the HO failure probability of the simulated
model is on an average of 0.01, whereas the value is near to
0.05 for MRN scheme.
(3) Communication interruption probability
The probability of communication interruption (CI) during
an HO procedure provides a detailed overview of the
efficacy of a model. For a system to provide improved QoS
and seamless user experience, the communication inter-
ruption probability needs to be smaller. In the simulation
model, we plotted the CI probability as a function of HO
locations within a range of 1100–1500-m region in the
overlap area. In comparison with the single-antenna MRN
model, the interruption probability for the proposed DMR-
TN scheme is less than 0.1 for the majority of overlap area,
as shown in the simulation results given in Fig. 9. The
involvement of torch nodes and adaptive measurement
aggregation mechanism module has significantly
Table 2 Simulation parameters
Parameters Values
DeNB Single cell base station
User equipment (UE) 120 Nos.
Macrocell radius 1500 m
Macrooverlapped area 400 m
Railway distance 7000 m
Speed of train 200–400 km/h
Length of train 200 m
Application VOIP
Carrier frequency 2 GHz
Bandwidth 5 MHz (25 RBs)
Path loss model ITU Urban Macro
DeNBTx power 46 dB
Mobility model Linear mobility
Simulation time 75 s
0
20
40
60
80
100
120
140
160
50 100 150 200 250 300 350 400
HO latency (ms)
Speed of train (km/h)
MRN DMR-TN
Fig. 7 HO latency
A novel handover scheme using torch nodes and adaptive measurement aggregation mechanism to
123
J. Mod. Transport.
contributed in decreasing the failure probability as the
distance increases.
6 Conclusion and future work
This paper presents the details of a novel scheme to
improve QoS in a high-speed railway communication
system. The proposed scheme involves the following key
features: (1) torch nodes to effectively forecast target
DeNBs, (2) adaptive measurement aggregation based on
mobility and (3) distributed mobile relays with load bal-
ancer for efficient resource utilization. The proposed
scheme was simulated using Omnet?? tool, and the per-
formance is analyzed in terms of handover latency, han-
dover failure probability and communication interruption
probability. The preliminary analysis shows that the DMR-
TN scheme outperforms the single-antenna scheme and
provides better performance with reduced handover failure
and communication interruption probability. The proposed
scheme can be easily implemented in high-speed railways
with reduced implementation overhead. In the future work,
we plan to carryout further optimization by considering
service-based parameters (e.g., voice, video, and data) to
enhance handover efficiency and resource optimization.
Acknowledgements The authors would like to thank Centre for
Development of Advanced Computing (C-DAC), Hyderabad, and
Jawaharlal Nehru Technological University, Hyderabad, in facilitat-
ing this research work.
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted
use, distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
made.
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
1000 1050 1100 1150 1200 1250 1300 1350 1400 1450 1500
Failure pro babilit y
HO lo c a ti on (m)
MRN DMR-TN
Fig. 8 HO failure probability
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
1000 1050 1100 1150 1200 1250 1300 1350 1400 1450 1500
CI pr obability
HO lo c a ti on (m)
Fig. 9 Communication interruption probability for the proposed DMR-TN scheme
P. J. Pramod, B. C. Jinaga
123 J. Mod. Transport.
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