optimization of handover algorithms in lte high-speed railway

Optimization of Handover Algorithms in LTE High-speed Railway networks

Linlin Luan, Muqing Wu, Jing Shen, Junjun Ye, Xian He

Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications, Beijing,100876, China

Email: [email protected], [email protected], [email protected]

Abstract

This paper introduces two kinds of handover algorithms that adjust the handover (HO) parameters of LTE (Long-Term Evolution) eNodeB (evolved NodeB) to improve the overall network performance and diminish negative effects. The focus is on the impact that two kinds of handover algorithms compare to A3 event based on the optimization of hysteresis and time-to-trigger in the different velocity environment and the different SINR. Both parameters have been designed and implemented in a dynamic system level simulator and have been investigated for different parameter sets in a high-speed railway) simulation scenario. Reference Signal Received Power (RSRP) and Reference Signal Received Quality (RSRQ) parameters have been simulated in a dynamic link level simulation and studied the influence factors via the simulation. The results suggest that optimized handover algorithms have higher handover success rate than the classical A3 event in the different velocity environment.

Keywords: LTE, Handover (HO), hysteresis, Time-to-Trigger (TTT), High-speed Railway

1. Introduction

Universal Terrestrial Radio Access Network Long-Term Evolution (UTRAN LTE), also known as Evolved UTRAN (E-UTRAN), is the 4th generation cellular mobile system that is being developed and specified in 3GPP[1][2][3]. There are two different radio access mechanisms used in LTE. OFDMA (Orthogonal Frequency-Division Multiple Access) is being used for the downlink and SC-FDMA (Single Carrier-Frequency-Division Multiple Access) is used for the uplink. OFDMA provides high spectral efficiency which is very immune to interference and reduces computation complexity in the terminal within larger bandwidths [4]. LTE is designed to increase the capacity, coverage, and the speed of mobile wireless networks over the earlier wireless systems [5]. Requirements for 3GPP LTE include the provision of peak cell data rates up to 100Mbps in downlink (DL) and up to 50Mbps in uplink (UL) under various mobility and network deployment scenarios. As one of the crucial aspects in radio resource management functionality, the handover performance becomes more important, especially for real-time service, since the handover failure rate will increase with the higher moving velocity. An additional requirement is the uninterrupted provision of high data rates and call services.

LTE has a very simplified network architecture compared to UMTS. The LTE network architecture consists of three elements: evolved-NodeB (eNodeB), Mobile Management Entity (MME), and Serving Gateway (S-GW)/ Packet Data Network Gateway (P-GW). eNodeB performs all radio interface related functions such as packet scheduling and handover mechanism. MME manages mobility, user equipment (UE) identity, and security parameters. S-GW and P-GW are a node that terminates the interface towards E-UTRAN and Packet Data Network, respectively [6]. This paper is focus on high-speed railway scenario, which deploys eNodeB consisting of Base Band Unit (BBU) and Radio Remote Unit (RRU) along railway line as demonstrated in Fig.1.

Handover is one mechanism that transfers an ongoing call or data session from one base station to another base station or one sector to another sector within same base station. There are 2 types of handover mechanisms, namely Connect (Entry)-Before-Break (CBB) and Break-Before-Connect (BBC). CBB refers to soft handover mechanism in which it is possible for a UE to simultaneously connect to two or more cells (or cell sectors) during an ongoing session whereas BBC is a hard handover that requires disconnecting from source eNodeB before establishing connection to a target cell [6].

Optimization of Handover Algorithms in LTE High-speed Railway networks Linlin Luan, Muqing Wu, Jing Shen, Junjun Ye, Xian He

International Journal of Digital Content Technology and its Applications(JDCTA) Volume6,Number5,March 2012 doi:10.4156/jdcta.vol6.issue5.10

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Figure 1. eNodeB deployment along railway line

In LTE only hard handover is supported. The use of break-before-connect handover reduces the complexity of the LTE network architecture. However, the hard-handover type may result in data being lost. Therefore, a mechanism to avoid loss of data is needed for hard handovers. To provide high data rate services in different velocity environment within LTE, an efficient, self-adaptive and robust handover algorithm is required. Hence handover technique becomes an important area of research since the proposition of LTE by 3GPP in 2004 [5]. Generally handover process within LTE system is divided into the following steps: measurement, judgment and execution. Measurement, which is fundamental

and crucial for handover performance，is made in the downlink between the serving cell and the neighboring cell and processed in the user equipment (UE). Based on the measurement of either reference signal received power (RSRP) or reference signal received quality (RSRQ) or both, a measurement report is done in order to make a reselection or handover decision. Then by radio resource control (RRC) signaling in the uplink, the report is delivered to the serving cell. If certain decision handover criterion is met, the reasonable handover is estimated. At last, handover is executed by handing in UE control power to the target cell from the serving cell [8].

Several papers have been published to optimize the LTE HO performance recently. A radio detection based rescue handover for 3G LTE has been studied. The radio problem detection based handover algorithm takes advantage of already existing radio link failure (RLF) detection mechanism specified in 3GPP for LTE [9]. Three well known handover algorithms have been optimized in the LTE system [10]. And the simulation results show that this optimization outperforms non-optimized algorithms by minimizing the average number of handover. In [11], the author proposes a new handover strategy between the femtocell and the macrocell for LTE-based networks in hybrid access mode, which consider some parameters for handovers, including interference, velocity, RSS and quality of service (QoS) level. The paper [12] shows that an efficiency of target base station prediction for several scenarios is investigated. Moreover, this paper analyzes an impact of a number of neighbor stations on the ratio of successfully predicted target base stations.

The propagation path between the eNodeB and UE transfer from simple line-of-sight (LOS) to one that is severely blocked by buildings, mountains, and tunnel [13]. Therefore, different channel environment, velocity or measurement bandwidth may have great influence on the measurement of RSRP and RSRQ. In this paper, 3GPP Spatial Channel Model (SCM), its extension (SCME) is used to analyze the impact on the measurement of RSRP and RSRQ under different parameters. In this paper two kinds of LTE handover algorithms will be introduced detailedly in high-speed railway scenario: One is the rapid handover algorithm based on different UE velocity, the other is the rapid handover algorithm based on optimized time-to-trigger (TTT) value.

The paper is organized as follows: In section II, downlink simulation platform is set up. The definitions of RSRP, RSSI and RSRQ are explained in it. In section III, both rapid handover algorithms will be shown. Then in section IV simulation results are analyzed and finally conclusions are drawn in section V.


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2. LTE System Simulation Metrics

UE related measurements for the handovers are defined in 3GPP specification in [14]. 1) Reference Signal Received Power (RSRP): is measured for a considered cell as the linear

average over the power contribution of the resource elements that carry cell-specific reference signals within the considered measurement frequency bandwidth. The cell-specific reference signals according to [15] can be used for RSRP determination. RSRP is calculated from the source eNodeB transmit power ( sP ), the pathloss values from UE to the source eNodeB (

ueL )

and additional shadow fading with a log-normal distribution and a standard deviation of 3dB (

fadL ) [14]. RSRP values which UE receives is as follows:

faduesues LLPRSRP ,

(1)

2) Signal to Interference and noist ratio (SINR): is calcualted from the RSRP of the source

eNodeB (uesRSRP ,

) and the RSRP of the target eNodeB (interfering cell) plus the thermal

noise. The RSRP values of the interferers and the thermal noise are added up to (noiseRSRPint,

).

The SINR values is as follows:

noiseuesue RSRPRSRPSINR int,, (2)

3) E-UTRA Carrier Received Signal Strength Indicator (RSSI): is the total received wideband

power observed by the UE from all sources, including co-channel serving and non-serving cells, adjacent channel interference, thermal noise, etc. RSSI can be written as:

noiseues RSRPRSRPRSSI int,, (3)

4) Reference Signal Received Quality (RSRQ)：is defined as the ratio RSSIRSRPN ,

where N is the number of Resource Block (RB) of the E-UTRA carrier RSSI measurement bandwidth. RSSI includes thermal noise and interference generated in the

target eNodeB，so RSRQ can express the relation between signal and interfence plus noise as follow:

RSSI

RSRPNRSRQ (4)

3. Two kinds of Rapid Handover Algorithms In Fig. 2, an example of HO triggering within 3GPP LTE is illustrated. The event detected and

reported is the so-called event A3 within 3GPP LTE [5]. As mentioned in section I, handover is triggered at the UE on the basis of triggers defined by the network. Namely, a set of triggers is signaled to the UE, one of them is named hysteresis, or “HO hysteresis”, and the second one is called “Time to Trigger” (TTT) [16][17]. It is very important to set right HO hysteresis and TTT based on UE speed, radio network deployment, propagation conditions and system load.

A very important aspect which has a great influence on handover performance is UE speed. For high-speed railway networks, trains go through the cells frequently. Accordingly, they will perform handover frequently. Obviously, it will increase call drop ratio (CDR) and handover failure rate. A handover is considered as failed when the transmission of one RRC HO-involved message exceeds a predefined delay. In this system simulation platform, this delay is set to 280ms, accounting for 4-5 RLC retransmissions [18]. Therefore, it is necessary that optimization of hysteresis and TTT should be investigated to satisfy customer’s wireless communication requirement in high-speed train.


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A. The rapid handover algorithm based on UE velocity

Since the velocity of train is various dynamically from 0km/h to 350 km/h during the travel, hysteresis and TTT of handover algorithm should be adjusted accordingly to ensure handover success rate and satisfying wireless communication quality in train. So hysteresis and TTT should be two variables correlated with velocity of UE. In Fig. 3, it shows that under the condition of different velocity intervals, hysteresis and TTT value are different accordingly. When velocity of UE becomes higher, the hysteresis and TTT value will be decreased smaller. For research’s simplification, three velocity intervals will be considered, 1st interval is 0km/h~120km/h, 2nd interval is 120km/h~250km/h, the last interval is 250km/h~350km/h.

B. The rapid handover algorithm based on optimized time-to-trigger (TTT) value

Figure 2. Triggering of classical HO

Figure 3. Triggering of optimized HO based on velocity


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Table 1. Handover Simulation Parameter

Parameters Values

UE number 1

eNodeB 3

Carrier Frequency 2.6GHz

Bandwidth 20MHz

Antenna Gain More than 18dBi

Antenna Max Transport Distance 1500m

Antenna Direction ParameterHorizontal 120/150deg

Vertical 65deg

Distance to railway line 200m

Handover execution time 0.25s

Distance between RRUs 1.5km

The number of RRU in cell 6

RRU Transmitting Power 46dBm

Path Loss Cost 231 Hata model

Hysteresis 0~120km/h, 6dB

120~250km/h, 4dB 250~350km/h, 2dB

TTT 0~120km/h, 1.5s

120~250km/h, 1.0s 250~350km/h, 0.5s

Nthreshold 0~120km/h, 6

120~250km/h, 4 250~350km/h, 2

Figure 4. The comparison of HSR between 1st algorithm and A3 in SINR=-10dB

The UE can measure RSRP and RSRQ periodically. Handover procedure is to be triggered if the difference of RSRP and RSRQ between source eNodeB and target eNodeB exceed the pre defined threshold (hysteresis). At this time, the UE sends the corresponding measurement report to source eNodeB. Under the high velocity environment, the wireless signal channel is time variant channel. So


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RSRP and RSRQ of source eNodeB and target eNodeB will change up and down. To avoid excess and/or ping-pong handovers the time N that the difference of RSRP and RSRQ between source eNodeB and target eNodeB exceed hysteresis should be utilized. When N excess thresholdN , the

handover procedure will be triggered. Therefore, it is assumed that when the velocity of the UE is 0~120km/h, 120km/h~250km/h, 250km/h~350km/h respectively, hysteresis is normalH , mediumH , highH

andthresholdN is normalN , mediumN ,

highN .

TTT will become a dynamic variable via this handover algorithm and will reflect channel condition directly to avoid handover failure and ping-pong HO effect according to threshold N. 4. Simulation Results

A. 1st Algorithm Handover simulation results

Figure 5. The comparison of HSR between 1st algorithm and A3 in SINR=-7.5dB

Figure 6. The comparison of HSR between 1st algorithm and A3 in SINR=-5dB


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For 1st handover algorithm, it is assumed that in 0~120km/h velocity interval normalH and normalTTT

are 6dB and 1.5s, in 120km/h~250km/h velocity interval mediumH and mediumTTT are 4dB and 1.0s, in

250km/h~350km/h velocity interval highH and highTTT are 2dB and 0.5s for the first algorithm. And

the Hysteresis and TTT of 0~120km/h velocity interval is the same as classical A3 event algorithm. The handover simulation parameter is shown in Table 1.

Figure 4, 5 and 6 is the comparison results of 1st handover algorithm and event A3, which show HO success rate of 1st handover algorithm is better than A3 event in the different velocity when SINR equals to -5dB, -7.5dB and -10dB. And HO success rate values of 1st handover algorithm show good performance when SINR equals to -5dB, -7.5dB and -10dB.

B. 2nd Algorithm Handover simulation results

Figure 7. The comparison of HSR between 2nd algorithm and A3 in SINR=-10dB

Figure 8. The comparison of HSR between 2nd algorithm and A3 in SINR=-7.5dB


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For 2nd handover algorithm, it is assumed that in 0km/h~120km/h velocity interval hysteresis and

normalN are 6dB and 6 times, in 120km/h~250km/h velocity interval hysteresis and mediumN are 4dB and

4 times; in 250km/h~350km/h velocity interval hysteresis and highN are 2dB and 2 times. The

handover simulation parameter is also shown in Table 1. Figure 7, 8 and 9 is the comparison results of 2nd handover algorithm and A3 event, which show

HO success rate of 2nd handover algorithm is better than event A3 in the different velocity when SINR equals to -5dB, -7.5dB and -10dB. And HO success rate of 2nd handover algorithm shows good performance the same as 1st handover algorithm.

Figure 9. The comparison of HSR between 2nd algorithm and A3 in SINR=-5dB

5. Conclusions

The system simulations are based on the simulation parameter settings in Table 2. 1 mobile user which is the train has been considered that never leave the simulation area. According to the above handover simulation results, it is clearly shown that the proposed both handover algorithms have better handover success rate than classical A3 by the adjustment of hysteresis and TTT in the different velocity interval. By the measurement of UE velocity, the handover decision rule may modify the handover parameter---hysteresis and TTT self-adaptively to avoid the increasing of handover failure rate while the UE velocity increases. The simulation result shows 1st and 2nd HO algorithms have good performance whether channel environment is good or bad according to SINR. 6. Acknowledgements

The research is supported by The National Science and Technology. Major Projects (No.2011ZX03001-007-03) and Beijing Natural Science Foundation (No.4102043). 7. References [1] 3GPP TR 25.913 V7.3.0 (2006-03), “Requirements for Evolved UTRA [2] 3GPP TR 25.814 V7.0.0 (2006-06), “Physical layer aspects for Evolved [3] Mohmmad Anas, Francesco D. Calabrese, “Performance Evaluation of Received Signal Strength

Based Hard Handover for UTRAN LTE” Vehicular Technology Conference, 2007. VTC2007-Spring. IEEE 65th

[4] Cheng-Chung Lin, K. Sandrasegaran, “Optimization of Handover Algorithms in 3GPP Long Term Evolution System”, Modeling, Simulation and Applied Optimization (ICMSAO), 2011 4th International Conference on Publication Year: 2011, Page(s): 1 – 5.


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[5] S. Sesia, M. Baker, and I. Toufik., LTE-The UMTS Long Term Evolution. John Wiley and Sons Ltd, 2009.

[6] H. G. Myung, "Technical Overview of 3GPP LTE" May 18, 2008. [7] Mohmmad Anas, Francesco D. Calabrese, Per-Erik Ostling “PERFORMANCE ANALYSIS OF

HANDOVER MEASUREMENTS AND LAYER 3 FILTERING FOR UTRAN LTE”, Indoor and Mobile Radio Communications. PIMRC 2007, IEEE 18th International Symposium on Personal.

[8] G.P. Pollini, “Trends in handover design,” IEEE Communications magazine,1996. [9] Puttonen, J., Kurjenniemi, J., “Radio Problem Detection Assisted Rescue Handover for LTE”,

Personal Indoor and Mobile Radio Communications (PIMRC), 2010 IEEE 21st International Symposium on.

[10] Cheng-Chung Lin, Sandrasegaran, K., “Optimization of handover algorithms in 3GPP long term evolution system”. Modeling, Simulation and Applied Optimization (ICMSAO), 2011 4th International Conference on

[11] Shih-Jung Wu, Steven K.C. Lo, "Handover Scheme in LTE-based Networks with Hybrid Access Mode", JCIT: Journal of Convergence Information Technology, Vol. 6, No. 7, pp. 68 ~ 78, 2011

[12] Zdenek Becvar, "Efficiency of Handover Prediction Based on Handover History", JCIT: Journal of Convergence Information Technology, Vol. 4, No. 4, pp. 41 ~ 47, 2009

[13] “Evolved Universal Terrestrial Radio Access (E-UTRA); Physical layer; Measurements,” 3GPP TS 36.214, version 8.0.0, September 2007.Article in a conference proceedings:

[14] “Evolved Universal Terrestrial Radio Access (E-UTRA); Physical layer; Measurements,” 3GPP TS 36.214, version 8.0.0, September 2007.Article in a conference proceedings:

[15] “Evolved Universal Terrestrial Radio Access (E-UTRA); Physical channels and modulation,” 3GPP TS 36.211, version 8.0.0, September 2007.

[16] Thomas Jansen, Irina Balan, “Handover parameter optimization in LTE self-organizing networks” Vehicular Technology Conference Fall (VTC 2010-Fall), 2010 IEEE 72nd.

[17] 3GPP TS 36.331, "Evolved Universal Terrestrial Radio Access (E-UTRA); Radio Resource Control (RRC); Protocol Specification (Release 8)", version 8.4.0, December 2008.

[18] Konstantinos Dimou, Min Wang, “Handover within 3GPP LTE: Design Principles and Performance”, 2009 IEEE 70th Vehicular Technology Conference Fall (2009).


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optimization of handover algorithms in lte high-speed railway

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