A SMART HANDOFF PROCEDURE IN 4G NETWORKS

Yuseung Jeong, Namgi Kim, and Hyunsoo Yoon

Department of Electrical Engineering and Computer Science

Korea Advanced Institute of Science and Technology, Daejeon, Korea

Keywords:

Handoff, handover, service quality, adaptive modulation and coding, OFDM, OFDMA, 4G, B3G

Abstract:

For the next generation mobile communication systems, all IP packet networks instead of the legacy networks

that are mixture of circuit and packet switching services have been studied to guarantee the high-speed data

transfer rate even in the high-speed mobile environments. In the packet networks, the rate that mobile users

are serviced varies according to the number of users in a single cell. Moreover, as the adaptive modulation and

coding adjusts the data rate in terms of channel conditions, the service quality are dominated by two compo-

nents; service rate by cell load and data rate by channel conditions. Therefore, we propose the smart handoff

procedure considering both the service rate and the data rate for the service quality in the next generation

communication systems.

1 INTRODUCTION

The upcoming next generation mobile communica-

tion networks such as 4G will be all IP packet net-

works (J. Manner, 2002). The packet switching net-

works have the advantage in terms of the highly ef-

ﬁcient utilization on the limited resources by using

shared resources rather than dedicated resources. In

the other words, available resources are not deter-

mined in advance. Instead, resources are scheduled

by packet scheduler, and new resources are allocated

temporarily whenever users transfer packets provid-

ing better quality of services to more users with higher

probability. However, the opportunity for each mo-

bile terminal to get services varies with the number

of users in a cell in case of the wireless packet net-

works (Y. Gwon, 2002). Namely, the less loads with

less users in a cell, the more services each terminal

can get, and vice versa.

It is essential to improve the entire system through-

put as well as the instantaneous throughput in the

wireless systems. The application of adaptive mod-

ulation and coding (AMC) is introduced to enhance

the entire system performance. The AMC scheme se-

This work was supported by the Korea Science and En-

gineering Foundation (KOSEF) through the advanced Infor-

mation Technology Research Center (AITrc) and University

IT Research Center Project.

lects the appropriate modulation and coding scheme

(MCS) in accordance with the estimated channel con-

dition (J. Yang, 2002; E. Armanious, 2003). For

the fourth generation wireless systems, the AMC can

be applied, because it is suitable to OFDM systems.

That is, the AMC can be applied on each subcarrier

to optimally assign subchannels, because OFDM sys-

tems assign different subcarriers to each user and the

orthogonal subchannel assignment reduces interfer-

ence among users. However, channel condition varies

continuously and it is difﬁcult to send channel infor-

mation in the wireless systems. In case of systems

exploiting the adaptive modulation and coding, the

channel condition would be better as the data rate be-

comes higher, and vice versa.

Therefore, the service quality varies with the cell

load as well as the channel signal condition in base

stations in the beyond 3G (B3G) systems. In this pa-

per, we propose the handoff algorithm based on the

two related factors to enhance the service quality; the

service rate and the data rate.

2 RELATED WORKS

The service quality is not easy to measure instanta-

neously due to the packet burstiness, self-similar traf-

ﬁc pattern, or high-speed packet processing in the

172

Jeong Y., Kim N. and Yoon H. (2004).

A SMART HANDOFF PROCEDURE IN 4G NETWORKS.

In Proceedings of the First International Conference on E-Business and Telecommunication Networks, pages 172-177

DOI: 10.5220/0001387301720177

 SciTePress

wired packet networks. To make things worse, routers

have no information about the current number of users

or cell loads exactly. The L4 router could make it pos-

sible, but it is not widely deployed yet. The IP QoS is

the other approach to measure the service quality. It

is classiﬁed into integrated and differentiated services

(Y. Tang, 2001). However, the IP QoS cannot be eas-

ily guaranteed in wireless systems because wireless

resources are much lesser than wired ones (S. Sen,

1999; M. Ricardo, 2002). The IP QoS cannot main-

tain service qualities of all calls. This scheme sim-

ply rejects calls to obtain the QoS of other calls and

it cannot resolve trafﬁc congestion problems. More-

over, QoS is not yet widely available even on the ﬁxed

networks.

The use of AMC is one of the state-of-the-art tech-

niques in the standards for third and fourth gener-

ation wireless systems that have been developed to

achieve high spectral efﬁciency on fading channels

(A.J. Goldsmith, 1998). The principle of AMC is to

change the modulation and coding format adaptively

depending on instantaneous variations of the channel

conditions. These conditions are subject to the sys-

tem restrictions. The AMC extends the system capa-

bility to adapt to good channel conditions. Channel

conditions should be estimated based on the feedback

from the receiver. For the AMC-OFDMA systems,

higher order modulation with higher code rates (i.e.,

16 QAM with R=5/6 Turbo Codes) are typically as-

signed to users near the cell site. On the other hand,

lower order modulation with lower code rates (i.e.,

QPSK with R=1/3 Turbo Codes) are assigned to users

at the cell boundary. The AMC allows various data

rates to be assigned to different users depending on

their channel conditions. Since the channel conditions

change over time, receivers collect a set of channel

statistics which are used by both the senders and the

receiver to optimize system parameters such as mod-

ulation and coding, signal bandwidth, signal power,

training period, channel estimation ﬁlters, automatic

gain control, etc (Lu, 2004).

Most of the handoff algorithms are designed to per-

form handoff based on the link gain or the received

signal strength (RSS). These algorithms can ﬁnd tar-

get base stations in terms of the link gain or the signal

strength before the current signal power is too weak to

sustain communications (M. McGuire, 1997). Thus,

the conventional handoff algorithms can help to get

services from a base station which has the better sig-

nal strength, but they cannot optimize the service

quality in the packet networks. In the circuit switch-

ing networks, the received signal strength can be a

metric to measure the service quality for the allocated

resources, because resources are dedicated. However,

new factors besides the link gain or the received sig-

nal strength have to be considered in case of packet

networks (N.D. Tripathi, 1999; Cao, 2003). There-

fore, we need new handoff methodology in terms of

the service quality each terminal gets instead of the

legacy handoff algorithms which only considers the

link gain or the received signal strength.

3 HANDOFF PROCEDURE

In this chapter, we propose new handoff algorithm

based on the service quality which is related with two

components; the service rate and the data rate.

3.1 System Environments

Our handoff algorithm operates on the shared channel

with a lot of users in the packet-based networks. How

many users exist in the same cell determines how of-

ten each user can be served because the channel is al-

located by the segment, the fundamental transfer unit

scheduled by there exist data to send. If the number of

users is small, then users can be served frequently. On

the other hand, intervals each user is served become

longer as the number of users increases.

7

6

5

4

3

2

1

Figure 1: Example of the cell layout with AMC

We consider the cell layout with the adaptive mod-

ulation and coding to enlarge the system capacity as

Figure 1 and Table 1.

Table 1: Example of adaptive modulation and coding

Fraction Code Rate Modulation

1 1/3 QPSK

2 1/2 QPSK

3 2/3 QPSK

4 5/12 16QAM

5 1/2 16QAM

6 2/3 16QAM

7 5/6 16QAM

The AMC helps more users can be served with the

higher data rate in a permissible range of the bit error

rate (BER) by applying the appropriate modulation

and coding method depending on the signal to inter-

ference plus noise ratio (SINR). Hence the actual data

rate each terminal gets differs with the received signal

strength and the amount of noise which varies with

the trafﬁc condition. Generally, mobile terminals near

A SMART HANDOFF PROCEDURE IN 4G NETWORKS

173

the base station can be served with the higher data rate

while the terminal far from the base station are served

with the low data date by applying AMC.

3.2 Smart Handoff Algorithm

To optimize the service quality, we make a smart

handoff algorithm which performs handoffs consider-

ing both the received signal strength and service qual-

ity simultaneously. We discuss how to measure the

service quality in the following sections. The smart

handoff algorithm follows:

Smart-Handoff-Algorithm

1 If (RSSCUR > threshold)

2 Begin}

3 For (each neighbor)

4 Begin

5 Measure the RSS;

6 If (RSSNEIGHBOR > threshold) Then

7 Begin

8 Measure Service Quality (SQ);

9 If (SQNEIGHBOR > SQCUR) Then

10 Handoff to new cell;

11 End

12 End

13 End

14 Else

15 Begin

16 For (each neighbor)

17 Begin

18 Measure the RSS;

19 If (RSSNEIGHBOR > threshold) Then

20 Handoff to new cell;

21 End

22 If (No neighbor cell to handoff) Then

23 Handoff to highest RSS cell;

24 End

Figure 2: Smart handoff algorithm

The smart handoff is mobile-controlled. It tries to

perform handoffs when the RSS from any base sta-

tion of the neighbor cells is stronger than the speciﬁc

threshold and the target base station of selected cell

is expected to provide better service quality than the

serving base station. Therefore, mobile terminals per-

form handoffs to the cell which is estimated to offer

the highest service quality among the adjacent cells

as long as its RSS is above the threshold. If the RSS

from all neighbor base stations including the serving

base station, then mobile terminals will try to handoff

to a cell which has the highest RSS between its base

station and the mobile station.

3.3 Estimation of Trafﬁc Amount

The subchannels assigned to a speciﬁc user can be

hardly detected and the amount of channel utilization

often changes sharply due to the packet burstiness in

the packet-based channel sharing systems. It is not

appropriate to determine the trafﬁc amount by mea-

suring the static channel occupancies in packet net-

works as cellular networks being currently used (Cao,

2003).

Null

Access

Hold

OnSleep

Figure 3: MAC state diagram

We determine the amount of trafﬁc by the num-

ber of users in the speciﬁc MAC state in our algo-

rithm. Figure 3 illustrates the MAC state diagram

which indicates the trafﬁc amount (A. ONeill, 2000;

A. ONeill, 2001). The ON state means that data is

being transferred while the HOLD state indicates that

data is not currently exchanged but the station is wait-

ing for the trafﬁc. Therefore, the station has the down-

link and the uplink trafﬁc channels in the ON state,

while it has the downlink and the thin uplink chan-

nels in the HOLD state. It has no trafﬁc channel in

the other states. In other words, the service quality

is the product of the data rate and the service rate.

The service rate is inverse proportion to the cell load,

and the data rate is related with the channel condition.

Consequently, we determine the amount of trafﬁc by

measuring the amount of terminals in ON and HOLD

states.

CU RREN T

+ α × HOLD

CU RREN T

, 0 ≤ α ≤ 1 (1)

In (1), the value of α decides the amount channels

potentially assigned to users. Therefore it has inﬂu-

ence on the trafﬁc amount calculation. We can make

a handoff function depending on the service quality

by this equation. The complete handoff function will

be discussed in the following sections.

3.4 Estimation of Data Rate

By the adaptive modulation and coding, we are able

to estimate the coding rate and modulation scheme for

the current subchannels being used when the chan-

nel condition is known by the value of the pilot sig-

nal’s SINR. After the coding rate and modulation is

determined, then we can decide the data rate that

means how many bytes can be loaded to the unit seg-

ment. For instance, the amount of data per segment

ICETE 2004 - WIRELESS COMMUNICATION SYSTEMS AND NETWORKS

174

can be determined in accordance with the coding rate

and modulation as Table 2 in the Flarion’s FLASH-

OFDM technology (Flarion, 2004).

Table 2: Data size per trafﬁc segment (Case of Flarion’s

FLASH-OFDM)

Coding Rate Modulation Data per Trafﬁc Segment

1/3 QPSK 420 bits (2 frames)

1/2 QPSK 630 bits (3 frames)

2/3 QPSK 840 bits (4 frames)

5/12 16QAM 1050 bits (5 frames)

1/2 16QAM 1260 bits (6 frames)

2/3 16QAM 1680 bits (8 frames)

5/6 16QAM 2100 bits (10 frames)

3.5 Estimation of Service Quality

The service quality is up to how often services are

provided and how many data can be sent or received.

The problem of how often each user can be served

is in inverse proportion to the amount of trafﬁc on a

serving base station (load), and how many data can

be transferred each time is in proportion to the data

rate in case of the multicarrier communication sys-

tems which share subchannels. Therefore, the equa-

tion to calculate the service quality is as below:

ServiceQuality = DataRate ×

Load

T S

× DATA

T S

TIME

sslot

cur

+ α × HOLD

cur

, 0 ≤ α ≤ 1 (2)

In (2), the NTS is the number of trafﬁc segment

available for each cell and it varies with the load of

the neighbor base stations. The DATATS

CH means the

amount of data per trafﬁc segment according to the

channel condition, and TIMEsslot is the frame duration

of the superslot. The ONcur and HOLDcur is the num-

ber of users in the state of ON and HOLD respectively.

We assume that there exists at least one user.

3.6 Smart Handoff Procedure

The smart handoff procedure applying the algorithm

suggested in the previous section is as Figure 4. Each

mobile subscriber station (MSS) perceives the time to

perform the handoff by measuring the received sig-

nal strength through the pilot signals from the serving

and neighbor base stations. The information about the

trafﬁc load and the modulation and coding to be ap-

plied is broadcasted to the MSSs periodically. The

MSSs determine the adaptive modulation and coding

by measuring the pilot signal’s SINR. Finally, each

MSS calculates the service quality from the informa-

tion measured which is described earlier. If there is

any base station providing better services, then MSS

initiates the handoff by sending handoff request mes-

sage to the target base station.

Figure 4: Smart handoff procedure

4 SIMULATION RESULTS

We compared the smart handoff with the conventional

handoff measuring handoff performance on simula-

tion results with the OPNET simulator (Opnet, 2004).

The simulation models and parameters used in this

simulation are shown in Table 3.

Table 3: Simulation environments

Radio model One level modulation and coding

Pilot and frame duration: 20ms

Trafﬁc model ON users

Mobility model Random way-point

10 moving nodes

0-10 stationary nodes

Simulation time 1 hour

For simplicity, single-level modulation and coding

scheme has been applied for the radio model. Only

users in the ON state are considered for trafﬁc for

one-hour simulation. The pilot signal and frame du-

ration is 20ms and this simulation is performed on the

single-tier seven-cell environment. By reducing the

capacity of the center cell gradually, it can be consid-

ered that the center cell has more users (see Figure 5).

The random way-point movement model is used for

A SMART HANDOFF PROCEDURE IN 4G NETWORKS

175

the mobility. There are twenty MSSs in this simu-

lation. We changed the number of stationary nodes

from zero to ten meanwhile we ﬁxed the number of

mobile nodes to ten.

high load

Figure 5: Cell layout for simulation

We deﬁne the node throughput as the number of

frames received from a base station per second for

handoff. The performance of the mobile and station-

ary nodes is measured by this metric according to the

number of stationary terminals as Figure 6. The ex-

perimental results verify that the smart handoff is bet-

ter than the conventional handoff in terms of perfor-

mance, because the number of frames processed for

the smart handoff is more than the one for the con-

ventional handoff.

0 1 2 3 4 5 6 7 8 9 10

10

15

20

25

30

35

frames per second

stationary load

Smart Handoff

Conventional Handoff

Node Throughput

Figure 6: Handoff performance for the mobile and the sta-

tionary nodes

The handoff performances of the mobile and ﬁxed

terminals are shown in Figure 7 and Figure 8 re-

spectively. For the mobile nodes, the handoff per-

formance is more remarkable than the one in the sta-

tionary nodes. This is because the number of station-

ary nodes increases while the amount of data which

MSSs can receive is limited on the serving base sta-

tions. From these simulation results, the smart hand-

off performance is better in terms of both the mobile

and stationary users.

0 1 2 3 4 5 6 7 8 9 10

20

25

30

35

frames per second 

stationary load

Smart Handoff

Conventional Handoff

Mobile Node Throughput

Figure 7: Handoff performance for the mobile nodes

1 2 3 4 5 6 7 8 9 10

0

5

10

15

20

25

30

frames per second

stationary load

Smart Handoff

Conventional Handoff

Stationary Node Throughput

Figure 8: Handoff performance for the stationary nodes

5 CONCLUSION

In the next generation ”all-IP” packet switching sys-

tems, the network or radio resources are shared by

users. The resource allocation is temporarily sched-

uled by the packet scheduler whenever packet com-

munications occur rather than that allocation is deter-

mined earlier. Therefore, the opportunity that each

user can use the shared resources decreases as the

number of users in a cell increases. Moreover, the

adaptive modulation and coding will be applied for

the next generation mobile communication networks.

It helps communications applying various data rate

in accordance with the current channel condition.

Hence the service quality each mobile station can get

changes with the current load condition in the serving

base station as well as the link gain.

The smart handoff algorithm we proposed in this

ICETE 2004 - WIRELESS COMMUNICATION SYSTEMS AND NETWORKS

176

paper simultaneously considers the service rate deter-

mined by the number of users belong to the serving

base station and the data rate varied with the adaptive

modulation and coding by the instantaneous channel

condition besides the received signal strength or the

link gain. We demonstrated that the smart handoff

enhances the service quality for each user and it is

optimal for the all IP packet networks, particularly in

4G wireless systems.

The smart handoff is the mobile-controlled handoff

as mentioned above. Therefore, it can be applied as

the vertical handoff (Q. Zhang, 2003; A. Misra, 2002;

J. McNair, 2000) among the heterogeneous networks

which are expected to be common in the B3G sys-

tems.

We are currently working on the problem of how

to measure the cell load more precisely. We also have

plan to verify the smart handoff performance by simu-

lation in the multi-tier nineteen cell environments that

the adaptive modulation and coding is applied elavo-

rately.

REFERENCES

A. Misra, S. Das, A. D. A. M. S. D. (2002). Idmp-based fast

handoffs and paging in ip-based 4g mobile networks.

IEEE Communications Magazine, Issue: 3:138–145.

A. ONeill, G. T. (2001). Edge mobility architecture - route-

ing and hand-off. BT Technology Journal, Volume:

19, Issue: 1:114–126.

A. ONeill, M.S. Corson, G. T. (2000). Routing and hand-

off in the edge mobility architecture. SIGMOBILE

Mobile Computing and Communications Review, Vol-

ume: 4:54–66.

A.J. Goldsmith, S. C. (1998). Adaptive coded modulation

for fading channels. IEEE Transactions on Communi-

cations, Volume: 46, Issue: 5:595–602.

Cao, G. (2003). Integrating distributed channel allocation

and adaptive handoff management for qos-sensitive

cellular networks. Wireless Networks 9, pages 131–

142.

E. Armanious, D.D. Falconer, H. Y. (2003). Adaptive mod-

ulation, adaptive coding, and power control for ﬁxed

cellular broadband wireless systems: some new in-

sights. Wireless Communications and Networking,

Volume: 1:238–242.

Flarion (2003, 2004). Flash-ofdm technology.

http://www.ﬂarion.com/products/ﬂash

ofdm.asp.

J. Manner, A. Lopez, A. M. (2002). Evaluation of mobil-

ity and qos interaction. Computer Networks, pages

38(2):137–163.

J. McNair, I. Akyildiz, M. B. (2000). An inter-system hand-

off technique for the imt-2000 system. IEEE INFO-

COM 2000.

J. Yang, N. Tin, A. K. (2002). Adaptive modulation and

coding in 3g wireless systems. VTC ’02 - IEEE Vehic-

ular Technology Conference.

Lu, W. (2004). An insight into 4g.

http://www.4g.co.uk/PR2004/Jan2004/2004.htm.

M. McGuire, V. K. B. (1997). Analytical bounds on the

mean received signal strength for conventional hard

handoff. Communications, Computers and Signal

Processing, 1997. ’10 Years PACRIM 1987-1997 -

Networking the Paciﬁc Rim’. 1997 IEEE Paciﬁc Rim

Conference on, Volume: 1:49–52.

M. Ricardo, J. Dias, G. C. J. R. (2002). Support of ip qos

over umts networks. The 13th IEEE International

Symposium on Personal, Indoor and Mobile Radio

Communications, Volume: 4:1909–1913.

N.D. Tripathi, J.H. Reed, H. V. (1999). Adaptive handoff

algorithms for cellular overlay systems using fuzzy

logic. VTC ’99 - IEEE Vehicular Technology Con-

ference, pages 1413–1418.

Opnet (2004). Opnet technologies.

http://www.opnet.com.

Q. Zhang, C. Guo, Z. G. W. Z. (2003). Efﬁcient mobility

management for vertical handoff between wwan and

wlan. IEEE Communications Magazine, Volume: 41,

Issue: 11.

S. Sen, A. Arunachalam, K. B. M. (1999). A qos man-

agement framework for 3g wireless networks. IEEE

Wireless Communications and Networking Confer-

ence, Volume: 3:1273–1277.

Y. Gwon, D. Funato, A. T. (2002). Adaptive approach for

locally optimized ip handoffs across heterogeneous

wireless networks. 4th International Workshop.

Y. Tang, C.Mao, H. X. X. (2001). Research on adaptive

ip qos management framework. Computer Supported

Cooperative Work in Design, The Sixth International

Conference on, Volume: 46 , Issue: 5:149–152.

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