The i4Ih IEEE 2003 International Symposium on Persona1,lndoor and Mobile Radio Communication Proceedings

Optimized Handover Procedure based on Mobile Location in Cellular Systems

A. Markopculos, P. Pissaris, S. Kyriazakos. Prof'E. Sykas

National Technical University of Athens, Greece Tel: +30 107721 478, email: a n t o t i y ~ , t e l e c o m . n t u a . ~

A / ~ . ~ i r w - Future-generation mobile communications w i l l provide broadband multimedia services to users. anywhere aiid anytime. On t l i e other Iiand network performance should he guaianteed to support these applications and x r v i c c i . In existing cellular systems handover is one of the Iiroccdures that causes serious network shoitconiings. This pi-occdui-e is much iniore complicated in next generation systeiiis (UM-TS) and is o f great interest for investigation arid op~iniization. Both these systems and those of the second peneration (GSM & GPRS) w i l l require redefined Iiandover algoritliins of active connections as the !nobility sup poi^ i s a vital issue foi- cellular systems. In this paper we /presetit a set o f Location Aided Handover mechanisms tlint use t l ie lncatioii information to assist safe Iiandover decisions. The impleniented algorirlims are validated by iiieaiis of a cellular network siinulator that clearly shows the impact o f these techniques to the handover performance. Finally. we briefly describe how this can be integraied iii the cellular system architecture.

I. INTRODUCTION

The paper iiiaiiily focuses on t l ie improvement of network performance when [he user's position i s taken into account. IFor tliai purpose two network siiiiulators are developed. oiie ftir GSM and one foi- UMTS. both based partially 011 rlic saii ie core. The simulators were used to evaluate the performancc o f existing handovcr alyorithnis and also to validate t l i ~ simulator models [I 1. Subsequently a large number of siiiiiilations was performed in order to evaluate tlie proposed Location Aided I-landover(LAH) algorithms.

'This paper is organized around 5 sections. Section 1 is the introduction. In the next section the L A H algorithms are preseiitcd. There are currently a lot o f L A H algorithms oiider investgation. but in this paper we only present 3 o f them that liave already been validated. In section 3 we

improvement. The results are rather optimistic since show iiicreascd inetwork performance under normal and high t ra f l ic load sitiiations. In addition we present liow i A I i can be intepi-atcd in a real networking eiiviroiiment. Finally in section 5 w e si11i1 up with t l ie conciusiotis.

pi-esetit the result of the siiiiulatiotis that show the network

II. LOCATION AIDED HANDOVER ALGORITHMS

:I / , 7 0 ~ ~ 1 ~ / l i ~ ~ l 0 l 7 While iiieasureiiient and experimentation provide a means for cxploring t l ie "real world". siniiilatioii is restricted to cxploriiiy a constructed. abstracted tnodel of the world. Measui-ements are needed for a crucial "reality check". Experiments are fi-cquently vital for understudying the behavior of otherwise inti-actable systems. However,

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iiieasureinents and experiments have limitations in that can only be used to explore the existing Iiandover procedures. They cannot be used to explore different possible new handover procedures. Simulations are not only complemental-y to analysis. but allow exploration o f complicated scenarios that would be either difficult or impossible to analyze [2]. Simulations can also play a vital i-ole in helping researchers to develop iiiruition about t l ie behavior o f new handover procedures. So i t ' s important to develop a reliable simulation environment for the investigation o f the intelligent handover procedures. The development o f the simulator that i s implemented within t l ie scope of IST CELLO project can be seen in two phases. The first phase i s the development o f a simulator. capable o f investigating the typical handover procedure. The second phase includes the implementation of the L A H algorithms that take into account the location of the user. The component with tlie iiiost fundamental in the L A H simulator i s the Location Aided Handover module (LAHm) that enables tlie location-aided handover. This module i s the bedrock for the simulator. So. it processes the location-related information and applies it on the algorithms that have been impleinented. Location-Aided Handovcr uses t l ie information o f instantaneous mobile location and the MGlS data to inake the decision o f the inost appropriate target base station for handover.

B. Ping-Pong Avoiduncr One very undesirable effect that occurs relatively frequently i s so-called ping-pong handover. This i s a Iiandover to a neighboring cell that retwns to the original cell after a short time. The cause o f a ping-pong handover i s the power budget criterion. The parameter HO-MARGIN determines which level of hysteresis must be exceeded so that a change to a neighboring cell takes place. In iiorinal operation a 5-10 dB HO-MARGIN i s selected to prevent minor variations iii signal level of different base stations from causing a handover [;I. However, nei(her is appropriate in actual operation. A high hysteresis value would practically eliminate a power budget handover and delay a change in the boundary area o f two cells far beyond the boundary. A high averaging length makes the handover process too slugyish and leads to a situation in which a really necessary handover sometimes is not carried out in time and t l ie connection is then broken off. This i s why, with the current handover algorithm and the modified variants. ping-pong handover cannot be avoided even by using appropriate parameter adjustments. The "ping-pong" algorithm goal is to try to inininiize such undesirable handovers. The concept o f this i s to use the location data o f each user and so to avoid continual i~nnecessary handovers between two neighboring

cells. Tlie basis of the whole algorithm is the movement prediction of each user. who appears to have such a behavior. As mentioned before. our tirst concern is to detect those users. who ai-e probably going tu request handover between two iieighhoring cells. Thus. we compare each user prcvio~is serving cel l with tlie one to which he i s requesting a Iiandover. Of course. i f a user is requesting a handover to a cell. which was l i i s previous one. after a long period (e.g. after 70 seconds). that i s not a ping-pong effect. Su. a iiiner (for each iiser) is used to indicate the time period that has passed froni the last successfiil handover. If t l iat tinier i s within a specific threshold (e.g. 10 seconds) and the i iser is requesting a handover to his previously serving cell the algorithni is triggered. Whenever the algorithm is triggered. the Location Server (LS) is used to provide t l ie user location. Holding the user lucation info. our alyorithm predicts his future move. In cur iiiiI)/enietitation a iiiobility iiiodel is already in use in order to iiiove every active user. The same inobility model is iised for each user i i i w e i i i e i i t prediction. every time tlierc is such a need. .Ihe iiio\'eineiit pi-ediction consists of a loop, each ofwhich step corresponds io a step o f 480 insec [;I. A selected aiiioiint o f steps (i) is used. so that this loop corresponds to a specific time period (e.s. i f 25 steps are selected, the algorithin predicts tlie user iiiove for the next 12 sec). According to the user ciirrcnt position and velocity (i.e. speed and direction) each ofthese steps estimates the user position of next ~ * l i . J 8 secc. In Fig. I the accuracy o f the predicted inoveinent depending on the real inoveinent is shown Tlie concurrence o f predicted and real movenient results to the calculatioii to be more precise.

By predicting the inoveinent o f each user we ai-e able to see which cel l appears to be the strongest in the potential iiser iiioveinent path. 111 01-der to estimate the "predicted cell" the following procedure is laking place. Suppose that the algorithm i s tl-iggercd at position A . Since the algorithm is triggered. i l ie i isei- is attached to cell I and iisiher previous cell i s cell 2. Assimic that [ l ie inoveineiil 131-edicted by the algorithm is the one shown in tiyiire 2. For each o f the different pixels tliat tliis path contains. we calculate an indicator. If the strongest ce l l in each of these pisels is the current serving cell (cell I in oiir tigiire). the Rx Level o f l l i e correspuiiding pixel o f this cell i s added to the indicator. If the slriitigesr cel l is the user previous cell (cell 2 in our l i p r e ) . [lie Kx Level of this cell is subtracted froin the

indicator. The sum o f all pixels wi l l then be a positive or a negative amount. If it i s positive. the predicted cell is the current one (cell I), otherwise is the previous one (cell 2). A t the end o f the loop we can decide the most probable cell to cover the user. The handover wi l l take place only if the predicted "proper" cell i s different to the already user serving cell. Whether or not. the user i s locked to the estimated strongest cell for an also selected time period. This ineans that this "locked" user can't request a handover within this p r i o d .

I

I -442 I 1 --+t-e--i i s Predicied cell = I

The "ping-pong algorithm", as mentioned before. uses some parameters in order to operate. These parameters can be selected as inputs o f the whole program. The first one is the number o f steps for the prediction duration. The second one i s the "locked" time period. O f course the niost appropriate i s to select the same period. Although an extra parameter was mentioned above, i t i s not exactly a parameter o f the "ping-pong algorithm" but a parameter of the ping-pong effect and thereby of the general handover algorithm. This i s the time period that indicates if a handover to a previously serving cell can be considel-ed as ping-pong

B. "Ton'uro's Ihe border'' ulgorirhfn The algorithm that we call "ping-pong algorithm" tries to avoid continuous liandovers between two cells. That usually occurs whenever users move almost parallel to cell borders. What if users move almost vertically to borders? In this case it is certain enough to expect a handover froin one cell to another. These users are also expected to move towards the cell internal area. so that i t is not possible to reclaim sources from their previously serving cell. The above certainty Qives us a significant opportunity. A user moving towards a different cell i s almost certain that i s going to ask for a handover within a sniall time pel-iod. The idea i s whenever such a behavior (i.e. vertical iiioveinent toward a different cell) i s detected. t l ie corresponding new cell to bind sources but for a dynamically configured period of time. For example. assume that a user is inside cell I and moves toward cell 2. The algorithm predicts that within a specified time period this user wi l l cross over. Cell 2 binds resources for this user'before his real handover request. When this request takes place, user utilizes the already bound resource to the effect that the call will not be blocked. This algorithm uses

The 14" IEEE 2003 International Symposium on Personal,lndoor and Mobile Radio Communication Proceedings

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tlie position and velocity o f each user. in order to predict t l ie new cell as mentioned before. which we call "future cell'.. ILncatioti Server estimates the position in each step. User c~iireiit velocity shows the direction. to which user is moving. We extend this direction by a selected angle (a). With the speed value. the pi-ediction time and the specified angle a. wliicli are all parameters to our simulatoi- in order to gi\'e the opportunity to find out the optimum value o f them through several simulation. we can design the arc that is formulated by the potential final destinations o f the user. l - l ie re f (xe . we know if the user i s tnoving towards another cell than the one serves the user. As shown in fig. :. we are then able io take into account more than one pixel in user future nocition

p icd l c l cd c c l l ~ C C l l L = " l i l l l l re Ce l l ' '

111 h i i t example. "fiiture cell" wi l l be cell 2, as at future wide area of user iiioveiiient there are 5 pixels o f that cell and only I of cell I. How far the algorithm wi l l predict depends on a selected time period (e.g. 8 sec) that previous is refei-red as the prediction time. The parameters of the algorithm are mainly two. The pi-ediction time period is the one that w i l l lead the prcdiclion deep enough itit0 user's future movement and rherefot-e w i l l indicate the final pixel o f this move. It i s crucial because it may be inefficient to select a small aiiiouiit 01- a long one. as it ii i ight happen to pi-edict wrong cell. The other parameter is t l ie angle o f the "direction steti is ion". Supposing that this angle is a small one (close 10 zero). the user's future position wi l l be one pixel. We desire to .'open" a bit this direction so that we can cover a wider area (more pixels). This makes inore certain the user's real future cell.

As h r as the network performance metrics which are affected by applying this technique ai-e the handover block rate and t l ie drop call rate. I t ' s obvious that by the combination o f user location and the network area we could manage to achieve an efficient resource inanagement for traffic channel allocation.

Our second algorithm iises the stored data collected by the Mobile Network Geographic Information System server (MGIS server) [ 5 ] . We assume that every selected cell has two ektra features: a) mean value of Drop Call Rate (DCR)

and b) mean value o f Block Rate (BR). Both of them come from the collected MGIS data. The above features are attached to the cells as a total attribute. We have to map these to each pixel inside the cell. A formula is used for this purpose based on these attributes and the signal strength. Each of the three components participates with a selected weight. Thereby, wk can write the formula as: C = wl*(l-R~-ind)+w~*DCR_ind+M,l*BR_ind (I 5CtO);

current Rx - Level current - Rx Level KY-illd = - max- Rx Level 63

cel I-average-Rx-Level current-Rx-Level

DCR-bid = cell-DCR *

cell-average-Rx-Level current-Rx-Level

BR-ind = ccIl_BR *

Where w I + w2 + w; = I

The 14m IEEE 2003 International Symposium on PersonalJndoor and Mobile Radio Communication Proceedings

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This formula calculates a cost for each cell at a specific pixel. This pixel i s the reply of the Location Server (LS). which is used (as in previous algorithm) to estimate the user position. The core of the algorithm is the cost of the serving cell. If a user, while he i s moving, conies to a place where the cost o f his serving cell is above a selected threshold, we consider that he i s in a critical area. Although a handover should be efficient then, an extra check has to be done. The cell o f the best cost (i.e. the lowest cost) must not be the same cell. Only if there i s another cell with a better cost. a handover should take place. So we could say that the criterion o f executing a handover procedure based on this second algorithm (The "MGIS-data algorithm") is that a user gets inside a "critical a]-ea" and that there i s a provision o f a better cost. As long as the new criterion i s satisfied, the already implemented handover procedure has to be executed. The difference o f that execution (compared to the one without using "MGIS-data algorithm") i s that we don't consider whether ,the candidate cell belongs in current cell's neighbors or not. The "MGIS handover" (as we could iiaine it) i s like a strict procedure and the user is forced to make a handover whenever such an occasion is detected. However, if "ping-pong algorithm" i s active and a user i s "locked". as explained in previous section, a handover (even a "MGIS handover") is not permitted and user s t i l l remains locked. As in "ping-pong algorithm", there are some palameters in this algorithm too. The first and most important i s the selection o f the cost threshold. That is the threshold that indicates whether a user is inside a "critical area" or not. It i s a number between 0 and I and if the cost o f user's serving cell gets over this amount, the user is inside a critical area. The other parameter i s the three weights used in cost calculation formula. Depending on what we consider inore critical in defining cell cost (i.e. Rx Level, DCR or BR), we have to choose the right weights. Of course we can choose one of those as I and the rest as 0

The 14m IEEE 2003 International Svmposium on Personal.lndoor and Mobile Radio Communication Proceedings

and therefore considcr only one of the three components (e.g. DCK) as iiiost determinant.

111. SIMULATION RESULTS The expected results o f the simulations can be included in [lie improvement o f network stability and efficiency. I t has been found that a typical GSMnetwork has an average hatidover failure of around 10% in city areas. Considering ilia! users making calls while inoving can require several handovers during a call. the call-drop probability increases. The causes of the handover failure. according to the inetwork system are iniainly. low field strength, quality or pouwr budget. In the reality, some of the inajor reasons are !he ones described in the previous sections. These causes cannot be easily detected from the network. Monitoring siiinultaneously the users inioveinent in addition to the sidtistical data from MGIS. all these effects can be encountered. Some performance metrics are very important for a cellular operator. These are

Handover Rate Handover Blocking Rate Drop Call Rate (DCR)

Iiandover Rate indicates the number o f needed handovers derived with the total calls. Handover Blocking Rate reveals the percentage that a handover during the call blocks due to lack of resources. Finally. Drop Call Rate s1nows the percentage of the calls that were dropped. In this paper we have investigated a cellular scenario characterized by:

An urban geometry (Downtown, Athens, Greece) given by 3.2 I .. . .. *

0 0.02 0.04 0.06 0.08 ~

I Erlangs Per U s e r Fig. 5: DCR progre.~.~ m d ,n!provemenr

A similar behavior can be observed in Figure 6 where the Handover Block Rate is plotted. Here. the improvement o f the HOBR is greater than the DCR in the previous figure. When an average erlangs per user reaches 0,06 inore than 50% reduction in blocked handovers i s achieved. Especially when the towards the border algorithm i s applied an improvement o f 80% i s observed in high traffic load situations.

Handover Block Rate

0 0,01 0.02 0.03 0.04 0,05 0.06 O.C Erlanos ~ e r u ~ e r

Fig. 6: ifO8llpi.ogrrss mid Wrprovrmenr

Another challenging issue about the network operators is the reduction o f the total number o f handovers in a certain number o f calls. By applying the -Ping-Pong avoidance algorithin inore or less a 5% fewer handovers take place.

Handover Rats 1

Fig. 7: HOR progess and iiiiprovemeni

From Fig. 8 we can state that the MGlS algorithm considered can optimize the network performance since two of the major metrics in a cellular network the handover block rate and the Drop Call experience an ineaningfully reduction. The mean decline is about 40% for the HOBR and 30% for the DCR.

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The 1 4Ih IEEE 2003 International Symposium on Personal,lndoor and Mobile Radio Communication Proceedings

D m 0- o m s 0 0 , O.*l, 0 0 2 O D 1 0 0 4 0.- Y I I

. . ~

Fr,y. S: l lu i i much ,tlGl.% o l g o r ~ f l u ~ ~ wzpmws OCR mid HOBR

Simi lar a major reduce o f inore or less 60% in Hand-off Block Rate and 40% in Drop Call Rate can be observed in

I On I

i-~,y. 0: / low rriiicii "7 imami .~ !lie hoidms" olguiirhnr sriprm'n DCR m d 11013R

IV. ADJUST L A H IN REALNETWORK One of the inajoi- goals o f t l ie L A H activity under the ti-amewoi-k oflST CELLO is the investigation how can this he iniegraled in a real networking environment. For the purposes of simplicity we introduce the L A H algorithm as an additional component to the system. while this can be inteyated as software patch to the BSC (RNC) software. 111 t l ic CBSC of CSM. following figure depicts the logical ilrcliitecture o f a network that supports both position locatioii and L A H . The figure is based on the proposal o f E.l.Sl .IS 101723. The ILAH component. as part o f the BSS interfaces with 2 components. namely the BSC and the LS. Since a L S architecture can be represented as LMUs (Location Measureinent Units) and SMLCiGMLC Sei-vingiGateway Mobile Location Centers. L A H should communicate with the SMLC to retrieve the user's location. For that reason it should be investigated the possibility to communicate and interact with these elements.

from BSCs; (ii) LAH component should be connected to a BSC and (iii) these should be performed at a real-time basis. Concerning the first one, each inanufactiire provides a list o f MMLs (Man Machine Language) commands that can be executed from a BSC. The L A H algor i thm can all be translated into MMLs that can be executed in order to control the handover as described in the previous sections. The MML commands add practically no delay to the system since they are immediately executed. The communication can be realized over telnet, RS-232 and also over the OMC, if centralized L A H is required. The requirements for the LAH-LS coniniunication can be summarized in: (i) LS requests should be foi-warded to the SMLC for processing and the response should be performed immediately, (i i) SMLC should be able to handle a large number o f requests, (iii) thc accuracy should be as high as possible. Concerning the requests to SMLC and the responses. this depends on the LS. since there are many LS implementations. A general architecture, as the one shown in the figure above. supports coniinunication of tlie L S components with the BSC, therefore, this is feasible. The inaiii liniitation is the number o f location requests that an SMLC can simultaneously handle. The accuracy is also an important parameter, but this is proven lo be a parameter for the L A H performance as described in the previous sections.

CONCLUSIONS

We have presented a work in the area o f network optimization, based on terminal localization. which is an outcome of extensive simulative studies performed both for GSM and U T R A systems. Position location is inostly exploited to offer value-added services. while wireless systems can use the location information to increase the performance o f several network procedures. In particular we have presented the impact on the handover procedure. which i s proven to cause several network shortcomings, such as drop call, ping-pong effect and H O block. The early results show that the exploitation of the location information and the use o f Location Aided Handover mechanisms can significantly contribute to the improvement o f network performance. In addition. we have briefly presented out a feasibility study about the possibility to port the L A H procedure into a generic cellular network architecture.

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