1

A Handoff Algorithm Based on Combination of RSSI and

Distance for Wireless Relay Networks

Guowei CHEN, Wipaporn CLAYBOOT, Kenichi ITOH, and Takuro SATO

Summary A handoff algorithm with the criterion of linear combination of

RSSI (Received Signal Strength Indicator) and distance is

proposed. The system model under study is a multi-hop network

with two fixed access points, some moving terminal repeaters,

and a mobile terminal. The mobile terminal moves from one

access point to the other, and makes handoff thru the terminal

repeaters to maintain access to service. Simulation is made and

the results are compared against two other algorithms, which

either count on RSSI only or count on distance only. It is found

that the proposed algorithm achieves lower handoff percentage

and outage occurrence.

Key words: Distance, Handoff, Multi-hop, RSSI

1. Introduction

Recent findings in the literature have shown that the

performance of wireless relay networks can be improved

through the application of distributed spatial diversity

techniques that leverage cooperation between wireless

terminals, where some Mobile Terminals (MTs) can serve

as Terminal Repeaters (TRs) to extend the network

coverage. Such a network structure can be applied in

multiple situations, e.g., in a disaster area, where the ability

of coverage has been greatly compromised due to damage

of large-scale antenna, an emergency solution is to turn

some powerful user terminals into repeater mode, which

help relaying for other users. Another applicable situation

can be found in communication of underway community,

where deployment of some moving small-ranged

transmission devices provide relaying functions for

underground mobile users to certain access points, which

connecting the underground and the surface

communication. One more application can be found in

certain local areas where large-scale antenna are sparse and

the coverage is limited, and thus certain powerful user

terminals can take responsibility as repeaters to help in

enlarging the coverage.

The above situations of applications require multi-hop

handoff technology. In abstract, it can be described as

follows, an MT disconnecting from an Access Point (AP)

can relay its handoff to a TR and use it as a temporary AP.

Decision of handoff triggering can be on various criteria,

such as received signal strength. But with either signal

strength or distance as criterion, there are situations where

unwanted handoff happens. For example, due to shadow

fading, a temporary drop (20 db ~ 30 db) in the measured

signal strength from a serving node (AP or TR), may lead

the signal strength algorithm to perform a handoff to an

adjacent node even if the MT is well within in the service

area of the serving node. As the drop is temporary, the MT

is then handed over to the original base station when the

measured signal strength level recovers. Handoffs in this

situation are not necessary, which leads to unnecessary

consumption of channel resources. On the other hand,

imprecision in distance estimation makes the distance

algorithm not always reliable. These unwanted handoff

cases can compromise performance in handoff percentage

and outage percentage. On the distance, Recently radio

location techniques such as hyperbolic positioning [1]

using Time Difference Of Arrival (TDOA) signals from

neighboring base stations or Time Of Arrival (TOA)

signals from a Global Positioning System (GPS) has

provided the capability for mobile stations to continually

track the location, so distance can be used as an indicator

for handoff.

Article [2] gives a research on distance-assisted handoff,

whose network model is cellular system with fixed base-

stations. Wireless relay networks have emerged as a new

form of networks and attract research focus, a research

with consideration of mobility of the intermediate nodes is

done in this paper. Furthermore, in [2] with the distance-

assisted handoff algorithm the average outage number is

increased, which is a drawback. This is because the

algorithm requires both distance and RSSI conditions

satisfied to start a handoff procedure. In this paper, a new

criterion of combination of distance and RSSI has been

proposed to remove the absoluteness of both conditions.

In the rest of this paper, the content will be organized as

follows. Section 2 presents the new criterion of handoff

and the outage notion used in this article, section 3

describes the system model, section 4 presents the

derivations of handoff and outage probability functions

and sets out the performance criteria, section 5 gives the

simulation results, and conclusion is made at section 6.

2

2. Proposed Criterion for Handoff

As similar to handoff procedures adopted in [2], the

handoff procedures used in this paper are Mobile-Assisted

Hand-Over (MAHO) algorithms. A handoff process

becomes requested when the value of a certain criterion

from the serving node (AP or TR) falls below that of an

adjacent node by a threshold. Once a handoff is requested,

the MT searches among the other nodes for those which

are capable of serving it. A handoff is performed to the

most appropriate node among them in terms of the

criterion used.

For the conventional algorithm that is only based on signal

strength, the above criterion is RSSI (Received Signal

Strength Indicator). For the algorithm based only on

distance, the criterion is distance.

For the proposed algorithm in this paper, a linear

combination of RSSI and distance, denoted as c as below,

is used as the criterion.

RSSIDISTWc (1)

where W is a constant, which is referred as weight of

distance here. With the nature of linear combination, many

computation methods used in analysis of the conventional

RSSI-only algorithm can be inherited.

1. Handoff conditions:

The two conditions below are required for a complete

handoff process.

1) Handoff requested condition

The criterion value from the serving node falls below that

of an adjacent node by a hysteresis value h.

2) Handoff selective condition

The criterion value from the candidate node is the

maximum among all nodes.

Likewise, correspondent handoff conditions can be defined

for an RSSI-only algorithm, with only differences on the

criteria and the directions of quantity comparison.

2. Outage definition:

To make it comparable for all the above three algorithms,

in this paper, outage is defined in terms of signal strength:

An outage event occurs if the handoff requested condition

is not satisfied when the measured signal strength level

from the serving node falls below an absolute quality

threshold level. From here, EAP is referred as the threshold

below which the signal from an AP to the MT falls,

causing an outage, and likewise, ETR for the threshold of

the signal from TR to the MT.

3. System Model

The network model is illustrated in figure 1. There are two

fixed Access Points (APm, m = 1, 2) deployed, and a

mobile terminal (MT) moves from AP1 to AP2 in a straight

line at a constant velocity α. A certain number (N) of

Terminal Repeaters (TRs) are in between of the two APs.

Different from [2], they are moving randomly. As for

simulation’s purpose, their initial locations are set on the

straight line with equal distance to each other dividing the

whole distance between the two APs, and their movement

is designed to be moving at random speed, with the mean

of β, changing direction in random periodically. They

serve as service relay for the

MT. As long as the MT moves along its route, it tries to

maintain the access to service by making handoff among

the APs and TRs.

Regarding to the propagation of the received signal

strength level, it is assumed signal strength is affected by

path loss as well as shadowing effect [3]. Rayleigh fading

is neglected here because it can be averaged out over the

time scale considered. The signal level received from APm

in the kth

interval of sampling, denoted as yAPm(k) , is given

by

)())(log()( 21 kkdKKky APmAPm (2)

where K1 and K2 represent the path loss factors, dAPm(k)

denotes the distance between the MT and the APm, and μ(k)

represents the shadowing variables, which are modeled as

an independent WSS (Wide-Sense Stationary) Gaussian

process with auto-correlation as follows:

0

2 exp)(d

(3)

where d0 denotes the decay of correlation with distance

and 2

denotes the variance of the shadowing process.

AP1

AP2

MT TRn

TR2

TR1

Fig. 1. Network Model

3

μ(k)

The signal level received from TRm (m=1, 2, … , N),

denoted as yTRm(k) , is given by

)()())(log()( 21 kkkdKKky TRmTRm (4)

where dTRm(k) denotes the distance between the MT and

the TRm, and υ(k) represents TR’s random movement

factor, which are modeled as an independent WSS

Gaussian process with the variance 2

.

Fig. 2. Signal Strength Propagation Model

Figure 2 is the signal strength propagation model. The

received signal levels are smoothed using an exponential

window function in order to reduce short-term fading

effects. The smoothed signal levels are given by the

convolution

)(exp1

)(101

lkyd

l

dky APm

l

APm

(5)

)(exp1

)(101

lkyd

l

dky TRm

l

TRm

(6)

where d1 is the distance constant of the smoothing window.

The estimated distances from MT to APm or TRn are given

by

)()()( knkdkx APmAPmAPm (7)

)()()()( kTRnTRnTPnTPn knkdkx (8)

where nAPm(k) represents the distance estimation error,

nTRn(k) represent the estimation error which is modeled as

white, zero-mean independent Gaussian data with variance 2

n ; and )(kTRn represents the random movement factor of

the TRs, which is modeled as zero-mean, independent

white Gaussian process with variance 2

. The estimated

distance xAPm(k) , xTRm(k) are smoothed over a window of L

samples for handoff decision. The distance estimation error

then becomes a Wide-Sense Stationary (WSS) Gaussian

signal with auto-correlation, as follows

Lnn

1exp)( 2 (9)

According to (1), the values of the criterion are defined as

)()()( kykxWkc APmAPmAPm (10)

)()()( kykxWkc TRmTRmTRm (11)

The relative values of the criterion are defined as

)()()( kckckc APnAPmAPAPmn (12)

)()()()( kckckckc TRnAPmTRAPmnAPTRmn (13)

)()()( kckckc TRnTRmTRTRmn (14)

4. Performance Analysis

4.1 Derivation of Handoff and Outage Probability

Functions

Let Pho(k) denote the probability that there is a handoff in

interval k, let PAPn|APm(k) denote the probability of handoff

from APm to APn, and let P|APm(k) be the probability that

the MT is assigned to APm. We have the following

recursive relations:

N

mnn

TRmTRn

n

TRmAPn

N

m

TRm

N

n

APmTRn

mnn

APmAPn

m

APmho

kPkP

kP

kPkP

kPkP

,1

|

2

1

|

1

1

|

2

,1

|

2

1

)()(

)1(

)()(

)1()(

(15)

N

n

TRnAPmfindTRn

mnn

APnAPmfindAPn

N

n

APmTRn

mnn

APmAPn

APmAPm

kPkP

kPkP

kPkP

kPkP

1

|_

2

,1

|_

1

|

2

,1

|

)()1(

)()1(

)(1)(1

)1()(

(16)

distance

signal

level

K1 – K2 log(dAPm(k))

dAPm(k)

υ(k)

4

N

mnn

TRnTRmfindTRn

n

APnTRmfindAPn

N

mnn

TRmTRn

n

TRmAPn

TRmTRm

kPkP

kPkP

kPkP

kPkP

,1

|_

2

1

|_

,1

|

2

1

|

)()1(

)()1(

)(1)(1

)1()(

(17)

where Pfind_APm|APn(k) denotes the probability of successful

handoff. It can be expressed as follows:

})({)()( ||_ APAPnAPmAPnAPnAPmfind FkcPkPkP

AP

APnAPAPmAPn

kCFQkP

)()(|

(18)

where FAP is the threshold correspondent to EAP, whose

value is linked by the linear combination, and )(kCAPn and

AP denote the expected value and the standard deviation

of the criterion )(kcAPn. And it is noticeable that a linear

transformation on a Gaussian process yields a Gaussian

process.

Let Pout(k) denote the probability that there is an outage at

interval k.

N

mnn

TRmTRnlost

n

TRmAPnlost

N

m

TRm

N

n

APmTRnlost

mnn

APmAPnlost

m

APmout

kPkP

kP

kPkP

kPkP

,1

|_

2

1

|_

1

1

|_

2

,1

|_

2

1

)()(

)1(

)()(

)1()(

(19)

where Plost_APn|APm(k) denotes the probability of an outage

from APm to APn.

})({)()( ||_ APAPnAPmAPnAPmAPnlost FkcPkPkP

AP

APnAPAPmAPn

kCFQkP

)(1)(|

(20)

It can be seen that if PAPn|APm(k), PAPn|TRm(k), PTRn|APm(k) and

PTRn|TRm(k) are solved, the above computation can all be

solved. As an example, PAPn|APm(k) is evaluated as below.

1

11

1

max,

max,

|

)1(

)1(,)(

)()(

)1(

)1(,)(,

)1(|)(,

)}1(|)({)(

G

FE

hkcP

hkchkcP

kckcP

hkcP

hkchkccP

hkchkccP

kAPmkAPnPkP

APAPmn

APAPmnAPAPmn

N

l

TRlAPn

APAPmn

APAPmnAPAPmnAPn

APAPmnAPAPmnAPn

APmAPn

(21)

where max,APncP denotes the probability that the criterion

value from APn is the maximum. Probability functions E1,

F1 and G1 above can be computed as follows:

N

l

kAPn

TR

TRl dttfkCt

QE1

)(1 )()(

1

(22)

h

kAPAPmn

APAPmn

APAPmnAPAP

APAPmn

dttf

kCt

kCh

QF

APAP

)(

)1(

)(

1

)1(

11 2

(23)

APAPmn

APAPmn kChQG

)1(1

(24)

where )(kCTRland

TR denote the expected value and the

standard deviation of the criterion )(kcTRl, fAPn(k)(t) and

fAPAPn(k-1)(t) are the probability density function,

)(kCAPAPmnand

APAPmn denote the expected value and the

standard deviation of the relative criterion )(kcAPAPmn, and

APAP is the correlation coefficient between

)1( kcAPAPmnand )(kcAPAPmn

.

PAPn|TRm(k), PTRn|APm(k) and PTRn|TRm(k) can be computed in

a similar manner.

4.2 Performance Criteria

As stated at the beginning, the aim of the research is to

avoid unnecessary handoff events while keeping an

acceptable outage ratio. The average number of handoff

and average number of outages are to measure the

performance of the algorithms. The average number of

handoffs can be defined here as

K

k

hoho kPN1

)( , where K is

the number of samples. The average number of outages

5

can be defined as

K

k

outout kPN1

)( .

Main parameters for simulation are shown in table Ⅰ.

TABLE Ⅰ

DEFAULT VALUES OF MAIN PARAMETERS

Parameters Value

Distance between AP1 and AP2 300 m

Numbers of TRs 3

Factor K1 0

Factor K2 -30

Velocity of mobile terminal (α) 20m/s

Velocity of terminal repeaters (β) 5m/s

Min RSSI thresholds (EAp & ETR) -75db

Numbers of sampling filter (L) 1

Correlation decay (d0) 20 m

Correlation filter (d1) 30 m

Handoff hysteresis value (h) 6

S.D. of distance estimation ( 2

n ) 3

S.D. of random movement of TRs ( 2

) 2

4.3 Analytical Results

1) Performance vs. influence by 2

It is expectable that the value of W will affect the values of

Nho and Nout. Below, calculation with different values of W

has been done, and results with several values of W will be

shown. Figure 3 and Figure 4 shows the different values of

Nho and Nout against 2

, with algorithm RSSI-only and

Linear Combination algorithm with different W values.

4

4.5

5

5.5

6

6.5

7

1 5 9 13 17 21 25

Handoff

Times

RSSI W=-0.1 W=-0.2 W=-0.3 W=-0.4

Fig 3 Handoff Times (Influence of Shadowing Process)

From figure 3, it shows that generally handoff times

increase, except that curve RSSI goes down when shadow

effect is too serious, whose reason is signals from both two

APs are too weak and thus RSSI-only condition will

trigger less handoffs, but the price is that outage goes

higher, as shown in figure 4.

0

0.0002

0.0004

0.0006

0.0008

0.001

0.0012

1 5 9 13 17 21 25

Outage

Times

RSSI W=-0.1 W=-0.2 W=-0.3 W=-0.4

Fig 4 Outage Times (Influence of Shadowing Process)

It is seen that RSSI-only algorithm will result in significant

outage increase as the variance of shadowing process

increases; and it is seen that the Linear-combination brings

less outage with all the enumerated values; furthermore, W

= -0.3 has quite good performance in the whole selected

range of 2

.

2) Performance vs. Influence by 2

n

Figure 5 and figure 6 shows the influence of the error in

distance estimation.

4

4.5

5

5.5

6

6.5

7

1 4 7 10 13 16

Handoff

Times

rssi -0.1 -0.2 -0.3 -0.4

Fig. 5 Handoff Times (Influence of Distance-Estimation)

0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0.0007

0.0008

1 4 7 10 13 16

Outage

Times

rssi -0.1 -0.2 -0.3 -0.4

Fig. 6 Outage Times (Influence of Distance-Estimation)

It is seen that as the error of distance-estimation increases,

both Nho and Nout increase, for all curves, which is natural;

S.D. of Shadowing Process ( 2

)

S.D. of Distance-Estimation Error ( 2

n )

S.D. of Shadowing Process ( 2

)

S.D. of Distance-Estimation Error ( 2

n )

6

and it is also seen that algorithm RSSI-only is

outperformed by Linear-Combination within a large part of

the selected range of 2

n , especially in terms of Nout where

distance-estimation is significant; furthermore, both W = -

0.3 and W = -0.2 bring fairly good results.

5. Simulation

Experiments of software simulation have been taken with

software OMNET++. In the following simulations, W = -

0.3 is used as the default value.

5.1 Performance Improvements in Simulation

In experiments of simulation, each occurrence of handoff

or outage is recorded with its happening spot. And with

repeated tests, such data is accumulated for examination.

Figure 7 and figure 8 shows the distribution of handoffs

and outages along the path from AP1 to AP2.

Fig 7. Handoff Times of Simulations of RSSI and Linear-Comb

Fig 8. Outage Times of Simulations of RSSI and Linear-Comb

As expected previously, the combination of RSSI and

distance brings the benefit of avoiding certain unwanted

handoffs. This can be shown in figure 7, where the vertical

axe is the times of handoff happening, and the horizontal

axis is the distance between MT and AP1. Figure 8 shows

the performance in outage occurrence of different

algorithms, where the vertical axis is the times of outage

happenings, and the horizontal axis is the distance between

MT and AP1. It can be seen that the combination of

distance and RSSI helps in reducing outage cases, since it

improve the likelihood of MT’s being served by a nearer

AP or TR, where outage possibility is obviously lower than

being served by a farther server.

5.2 Influence of MT velocity

To investigate the influence by MT velocity, experiments

have been done. Figure 9 and figure 10 show the handoff

times and outage times versus the MT velocity. It can be

seen that as MT velocity increases, handoff times and

outage times decrease. It can still be seen that the Linear

Combination outperforms in both Nho and Nout.

It shows that as MT velocity increases, Nho and Nout goes

less, which should hold if the velocity is within a certain

range. This is because higher velocity causes less duration

of the tour of MT between APs, and thus suffers less from

the occasional shadowing effect.

Fig 9. Handoff times vs. MT Velocity

Fig 10. Outage Times vs. MT Velocity

7

6. Conclusion

In this article, a handoff algorithm with combination of

RSSI and distance has been proposed, and from the

analytical results and simulation results, it achieves a lower

handoff rate then the traditional RSSI-only algorithm, and

has a better result in outage percentage too, which shows

better ability to resist the influence by shadow fading.

And according to the parameter-influence results, this

conclusion is relatively insensitive to the levels of shadow

effect, distance estimation error, and MT’s velocity. If the

standard deviation of the estimated distance can be

improved by employing a high-accuracy location method

such as differential GPS or real-time kinematic GPS, the

average number of handoffs and outages may be reduced

even further.

Deploying more TRs is expected to provide larger

coverage area and then bring less outage, but a side effect

would be that more handoffs might be caused between the

TRs. Therefore, an approach to decide the reasonable

number of TRs should be considered, especially in cases

where some user terminals are chosen to be TRs.

For the continuation of this paper, it is significant to

develop a more practical solution to the computation of the

optimum value of W via formulas. And it is possibly

beneficial to develop a mechanism of dynamic W value

subject to changes in network environment.

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[3] P. S. Kumar and J. Holtzman, “Analysis of handoff algorithms using both bit error rate and relative signal strength,” Proc. 3rd Annual Intl. Conf. Universal Personal

[4] Kenich Itoh, Souich Watanabe, Jew Shuh Shih, and Takuro Sato ”Performance of Handoff Algorithm based on Distance and RSSI Measurements”, IEEE Transactions on Vehicular Technology, Vo;.51 ,No.6, pp.1460-1468 ,Nov.,2002.

[5] M. Gudmunson, “Analysis of handover algorithm,” Proc. IEEE 41th Veh. Technol. Conf., pp. 537–542, 1991.

[6] N. Zhang and J. Holtzman, “Analysis of handoff algorithms using both absolute and relative measurements,” IEEE Trans. Veh. Technol., vol. 45, pp. 174–179, Feb. 1996.

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[8] K. Itoh, S. Watanabe, and T. Sato, “Performance analysis of handoff algorithm using both distance and RSSI measurements,” presented at the 3rd Int. Symp. Wireless

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Fig 5. Outage

distribution of

different handoff

algorithms