SUPPORT OF HANDOVER IN MOBILE ATM NETWORKS

SUPPORT OF HANDOVER IN MOBILE ATM NETWORKS Péter Fazekas fazekasp@hit.hit.bme.hu Tel: (36) 1-463-3256 Fax: (36) 1-463-3263 Department of Telecommunications Pázmány Péter sétany 1/D Polytechnic University of Catalonia 1117 Budapest Hungary 1. Abstract In this paper I give an outline of the problems of the mobile ATM networks due to user mobility. I propose some possible solutions. I describe an optimized version one of these and also describe a modeling method to analyze these kind of mobile ATM networks. Keywords: mobil ATM, Virtual Connection Tree, location prediction, BCMP networks 2. INTRODUCTION To maintain high bit rate and good quality access to Internet in the future we need a fast and reliable backbone network that carries the Internet traffic in a MAN/WAN environment. The speed and reliability of the access network is also indispensable. ATM was developed to operate as a reliable multi bit-rate transmission technique, which provides specified Quality of Service (QoS) parameters to the users. Given that the number of internet users grows exponentially and their required bandwidth and the variety of internet applications grows even more rapidly it is reasonable to think about ATM as a convenient bearer of the internet traffic. So the concept of IP over ATM is becoming to be seen as the transmission technique of the future. As the capacity and speed of the laptopsized computers has increased dramatically in the past few years, the demand of accessing the internet with laptops via the radio channel while the user is moving also became significant. Thus, the mobility support of the Internet protocol was developed and next version of IP (IPv6) also contains mobility support. If we assume that the future network is an IP over ATM type, it is important to deal with the mobile extension of the ATM. Of course a lot of work has been done about this topic so far. The main problem of extending the connection-oriented ATM technique to mobile environment is that the users access point to the network may change during an ongoing connection (handover). Theoretically the network should re-establish the connection after each handover with all the procedure of the connection setup. As cellular networks move towards using small cells to increase frequency reusability and system capacity and to decrease used powers, the rate of handovers increases. This raised number of handover could cause overload of the network intelligence if all the handovers are followed by a connection setup procedure. Thus a lot of research is done in the field of avoiding the need of frequent re-establishment of connections. 3. SOLUTIONS OF THE FREQUENT HANDOVER PROBLEM To avoid the overload of the call processor and to provide seamless connectivity to mobile users in micro- and picocellular environment, several techniques were proposed. One of the possible solutions is to predict the users mobility patterns [1-3]. Location prediction is a dynamic strategy in which the system proactively estimates the mobile s location based on a user movement model. Location tracking capability depends on the accuracy of this mobility model and the efficiency of the prediction algorithm. If the system predicts the user s movement accurately, it is able to allocate resources for the user at the future access points. Thus, if the system is able to determine the mobile s future locations and access points as it moves inside the network while being connected it could improve the system efficiency and the connection quality significantly. One way for the system to know the future direction of the mobile is to have a mechanism in place that allows the mobile to indicate to the system its intended destination and the duration of the connection. The system uses this information to determine the future path of the mobile. To achieve this, it uses its knowledge about the terrain and locations of the base stations of the terrain. However, this might not be a conclusive solution,

because there could be multiple paths to a destination within a terrain. Moreover, it is not unreasonable to assume that the mobile may diverge from its stated path without warning, in order to adjust to its dynamically changing environment. Some of the location prediction algorithms based on the proposal, that the mobile s location may be determined based on its quasi deterministic mobility behavior represented as a set of movement patterns stored in a user profile. A more sophisticated method is when a user s moving behavior is modeled as repetitions of some elementary movement patterns. Based on this mobility patterns, a pattern recognition, pattern matching based mobile motion prediction (MMP) algorithm is used to estimate the future locations of the mobile. The drawback of this method is that it is sensitive to the random movements. Any movement that cannot be classified by the simple mobility patterns is a random movement. Another approach to pre-allocate system resources for communicating mobile users that change their access point in the network is to reserve resources in all the cells to which the mobile is able (or likely) to move in the near future. To achieve this, it is necessary again to predict the movement of the user. But in this case the prediction does not have to be as accurate. In location prediction algorithms the system tries to predict the path of the user and allocate resources at the base stations of which this path is consist of. In this other case the system estimates a larger set of possible cells in the neighborhood of the mobile s actual cell. This is the so-called shadow cluster concept [4]. The shadow cluster defines the area of influence of a mobile terminal (i.e. the set of base stations to which the mobile is likely to attach in the near future). Like a shadow, this set moves along with the mobile, incorporating new base stations while leaving old ones as they come under and out of the mobile s influence. Each base station in the shadow cluster anticipates the mobile s arrival and reserves resources for it. The accuracy of the mobile s path prediction determines the number of base stations that reserve resources and this determines the system efficiency. With a good prediction, only a few base stations compose the shadow cluster, thus in this case the efficiency of this pre-allocating of resources is high. With a perfectly accurate prediction, the shadow cluster consists of only one cell (the next one). As we have seen, the shadow cluster concept may strongly utilize the results of several location prediction algorithms and can be seen as a kind of extension of the location prediction idea. Another solution is the so-called umbrella cell. This approach deals with the handover problem at the physical and data-link layer; thus it is applicable for not only ATM but also any other types of networks. Yet it is worth knowing it because it might be a simple solution in ATM networks too. An umbrella cell is a cell, which is much larger then the other ones of the network. This cell may cover a geographical area, where users are likely to hand over frequently. Naturally this area is also covered by a number of original cells, but obviously the umbrella cells and the other cells use different physical channels. When a user s behavior shows that it isgoing to hand over frequently, its call is switched (handed over by the system) to the base station that serves the umbrella cell. Since the umbrella cell covers a large geographical area, the mobile will not initiate any more handovers until it stays in the coverage of the umbrella cell. The decision of switching a user s call to the umbrella cell might based on measurements of the user s velocity, or the number of handovers it has already completed or again the location prediction algorithms might be used to calculate the number of handovers the user is going to make according to the information of its velocity, direction, etc 4. VIRTUAL CONNECTION TREE The other way to avoid the degradation of the QoS parameters due to frequent handovers is to group a set of radio cells and provide, that handovers between these cells do not effect in new call setup and call admission control procedure. To obtain this, the so-called Virtual Connection Tree (VCT) concept was proposed in [5]. A Virtual Connection Tree is a collection of cellular base stations and wired network switching nodes and links. The leaves of the tree are the base stations; the branches are the links between the ATM switches. The VCT is connected to the fixed network with a root switch. The other switches also can be nodes of the fixed network, and can be connected physically with more links, not only with the links of the VCT. So the elements of the VCT (except the base stations) can also carry traffic of the other parts of the network, but all the

traffic of the VCT (i.e. the communication of the mobiles admitted to the VCT) is switched through the root of the tree. The geographical area covered by the VCT is called neighboring mobile access region. When a mobile connection is admitted to a virtual connection tree, a collection of Virtual Circuit Numbers (VCN) is assigned to the call. Each VCN defines a path between the root of the connection tree and a distinct base station. There are two sets of the VCN, one in each direction (upstream and downstream). While the mobile user roams in the VCT, it can hand over its call to a base station without the need of rerouting the call, because the mobile simply informs the root switch about the handoff by continuing the transmission with the new VCN. The root has a table with entries of all the mobiles that are admitted to the VCT. The table contains the identifiers and the actually used VCNs (i.e. the locations) of the users. When the root receives a call it looks up the VCN of the called mobile from its table by the identifier of the called party (this information of the called party s identity must be contained in the incoming call) and forwards the call to the called mobile according to the last received VCN from that user. The call processor of the VCT is only involved when a handoff to or from the VCT occurs. In each node of the tree, the received ATM cells are relayed according to the VCN of the communicating user. So each switch of the tree contains a routing table with the entries of VCNs and input/output ports. So, when a new mobile initiates a call from the VCT, or a call arrives to a mobile at the VCT, the call setup procedure is divided into to parts. First, the fixed part of the connection is set up (between the root switch and another fixed terminal of the network or the root switch of another VCT). This fixed portion is maintained during the connection s lifetime or as long as the mobile stays within the connection tree. If the caller and the called party both dwell in the VCT, this part of the call setup evidently does not take place. As a second step, the variable part of the connection is established inside the VCT. This means that the routing tables of the switches are appropriately updated according to the new sets of VCNs. However all the connections between the root switch and the base stations are set up in terms of the updating of the routing tables, only two of them (one in both direction) is in use at a moment. The operation of the VCT is similar to the pointmultipoint connection but only one path of the tree is in use at any time. If a handover between base stations of the VCT occurs, the mobile simply continues its communication with the appropriate new VCN. If it is not communicating, but it is switched on, it must send a handover message to the root with the new VCN. Otherwise the root would not know its new location and would possibly route an incoming call to a wrong path. The root then updates its table of mobiles according to the new VCN. Whenever a mobile reaches the boundary of a connection tree, it seeks admission to a new connection tree. This procedure is the virtual connection tree handoff. At this point, the network call processor must again become involved. However, since the geographical area a VCT covers is large compared to the size of the radio cells which comprise the tree, the rate of connection tree handovers is assumed to be acceptably low and manageable by the call processor. To prevent the connection of a mobile situated at the boundary of two connection trees from oscillating between the two, connection trees would overlap in space (i.e. some base stations might belong to two trees). Thus it is unlikely that after a handover a connection will immediately seek to handover again to another tree. The virtual connection tree concept integrates the advantages of both the micro- and macrocellular approach. Since the connection tree might consist of micro- or picocells, the higher radio spectrum efficiency, frequency reusability and thus the higher capacity of microcellular networks is utilized by the connection tree. On the other hand, because from the handover point of view the connection tree behaves like a large cell, it exploits the advantages of the low handover rate in networks of cells with large radius. So the VCT approach maintains QoS by minimizing latency during handover initiation and completion, by minimizing cell loss and by reducing processing delay during handoff. The strength of the VCT is the admission control and rerouting algorithms, which are fairly simple to implement. There are some drawbacks of the VCT too. One of these comes from the single call admission control mechanism that take place when a mobile enters the VCT. Namely, though the state of the VCT and the QoS measures might be acceptable at the time a mobile admits to the tree, due to the arbitrary movements of the users within the tree overload of resources could occur at base stations or at switches. This overload might seriously degrade the QoS parameters (like cell loss

ratio, cell delay etc.). It is reasonable to assume, that the bottlenecks of these overload states are the base stations, since we consider that there are enough resources at the wired part of the connection tree, but the physical channel of the radio base stations is limited. Thus a new QoS parameter of the virtual connection tree, the base station overload probability might be introduced. More accurately, base station overload occurs, when the required capacity of the mobiles that are under the coverage area of a base station exceeds the maximum capacity that a base station could provide without violating other QoS parameters. Besides the possibility of system overload, the inefficient use of the network resources and the long setup processing time needed to assign VCNs on a large geographical area are also the drawbacks of the VCT. In addition, most of the VCNs are wasted, since in a large VCT the mobile is not likely to visit all the cells. To avoid these latter inefficiencies, one might combine the VCT approach with location prediction algorithms. With location prediction one can reduce the usage of unnecessary VCNs if only the VCNs of the predicted locations are assigned to a mobile's call. Each of these connections is maintained for time duration determined from the mobile's predicted velocity and predicted cell dwell time. There are some other possible drawbacks of the VCT concept, due to the centralized routing; i.e. that all the communications initiated from inside or outside the VCT is switched through the root switch. This is the case, even if both the caller and the called party are in the coverage area of the same base station. In a large VCT in the upstream direction there might be several hops between the initiator and the root and another number of hops from the root to the destination in the reverse direction. This wastes the capacity of the links and nodes of the VCT. Since as it was described above, the elements of the VCT might carry traffic of the other parts of the network, thus this additional load may degrade the quality of other connections at the whole network. Moreover, the centralized routing and handover management of the VCT may result in the degradation of cell loss ratio and cell delay due to handovers. When a mobile hands over to a new base station, the root updates its location table only if it receives an ATM cell with a new VCN that indicates the handover. In large VCNs the latency between a handover and the detection of the handover might be significant. During this time the root might forward ATM cells towards the old base station of the mobile, with wrong VCN. These cells become lost or significantly delayed at switches, which try to reroute these cells to the appropriate destination. However, by adding more intelligence to the nodes of the VCT, these drawbacks might be reduced. 5. OPTIMIZING A VCT We have seen that switching all connections through the root may cause unnecessary load at the network. Moreover the latency between the handover and the refreshment of the root s location table may increase cell loss ratio or cell delay. These problems might be avoided if those cells from which mobiles are likely to call each other (for instance cells that are covering different buildings of a company) are connected to switches that are not far from the root at the tree topology, or directly to the root itself. The same holds about cells between which handovers frequently occur. However in most cases it is difficult to carry out this solution. Namely, the convenient switches or the root may be geographically far away from the base stations that are planned to be connected to these switches. Moreover the number of base stations that might be connected to a switch is limited. The other solution is to add more functionality to some of the switches of the VCT, namely these changed nodes should act as roots if receiving a call to one of its ports that connect the lower parts of the VCT to that node (i.e. the call is coming from a switch or base station that is under the node in tree topology. This means, that each of these nodes should have a table of the identifiers of those mobiles that dwell under the node in the tree. To fill up and refresh these tables is possible when a mobile is admitted to the connection tree. While asking for admission the mobile must send registration messages towards the root. Then all the nodes between the base station to which the mobile is admitted to and the root switch receives these messages and fill up their own location tables. So each node creates entries in its table only about the mobiles that dwell under it in the tree. Besides these table of locations the switch need to have information of the VCT topology to perform the handover operation described later.

When a mobile initiates a call from the connection tree, each node to which this call arrives should check if the called party is in its location table. If it is, the node redirects the call according to the called party s VCN. If the node does not have an entry of the called party, it forwards the call towards the next node that is above it in the tree. At last the call might arrive to the root which might switch it out of the VCT if the called party is outside the VCT. But if a switch receives a call that is coming from the upper parts of the connection tree, it switches the call according to its rooting table (so in this case the switch operates as in the original VCT concept). Similar operation is needed at the time of handover. Before the handover happens, the mobile should send a message which contains the VCN that corresponds to the next base station to which the mobile is immediately going to admit to. The switch that receives this handover message checks if the new base station is under it in the tree or not (this could be achieved with the knowledge of the tree topology and the assignment of base stations and VCNs). If the next base station of the mobile is under it, the node updates its table of mobiles and its routing table according to the new VCN. Thus when ATM cells bearing the VCN of the mobile arrives to the switch, it forwards them towards the new base station. If the new base station is not under the switch, it forwards the handover message to the switch which is above it in the tree (it results from the tree topology that each switch has only one neighbor that is above it) and deletes the entry of the mobile from its table of mobiles. So the handover message goes as high in the tree as it is necessary (i.e. until a node that recognizes that the new base station to which the mobile hands over is under it). This highest point might be the root switch. If the mobile hands over from the VCT the root deletes its entry of the mobile. If the VCT has these changed switches with a farseeing planning the extra load due to intra VCT connections and the degradation of QoS due to handovers might be significantly reduced. Namely if base stations of cells that are covering areas between which users are likely to communicate or to handover should be connected to the same switch that performs this modified, root-like operation. The price of this reduction of extra load and amelioration of QoS measures is the increased switching delay due to the looking ups and refreshments the nodes should fulfill. But since these nodes should store information only of the mobiles that dwell under it in the tree. Thus these tables do not need to be large. By the development of the speed of switching elements and the reduction of the price of such elements there is a possibility to apply these kind of advanced nodes at the VCT. 6. MODELING TOOL FOR ANALYZING VCTS In [5-6] simple analytical models were proposed to calculate the previously described base station overload probability in a VCT. These models were homogenous. These models assumed the handover probabilities between cells to be uniformly distributed (even between nonneighboring cells) and the call initiation probabilities from cells were also uniformly distributed. The sojourn time of users in cells and the call holding times were assumed to be exponentially distributed. A new model is proposed in [7]. This model can handle the following new properties: the handoff probability is not equal between each cell pairs and it is zero between not neighboring cells the residential time spent by a user within a cell depends on the type of the user and the cell as well and is arbitrary distributed the call holding time and the required capacity depend on the type of the user, the call holding time is exponentially distributed the new calls generated within the VCT are not equally distributed i.e. the call rate in different cells is different the incoming stream of handoff-calls to a VCT and the total stream of new calls within the VCT are approximated as two independent Poisson processes, the arrival rate depends on the total number of users in the VCT We can model the VCT with these assumptions as a network of queues. A queuing network consists of a set of queues. The network could be either closed or open, i.e. there are customers entering and leaving the network, or the number of customers in the network is constant. When a customer gets served, it may enter another queue (or the same queue again), or, in case of open networks leave the network with certain probabilities. To understand our modeling concept, it is worth describing shortly one type of queuing networks, described the so-called BCMP theorem [8]. According to the BCMP theorem, a set of

server per user (in other terms infinite server, however there is no physical realization of infinite servers) queues with Coxian service times connected into a network of queues has a product form solution in equilibrium. The theorem allows the use of several customer classes and the service times may depend on the user class as well. Within subsets of customer classes class switching is also allowed (i.e. the customer enters a queue as of class i, but after getting served, enters the next queue as of class j). Moreover, the BCMP networks may consist of three other types of queues, but there is no need using them in this present work. The state space of such a queuing network is quite complex. We must track and consider the number of customers receiving the ith phase of the service time related to the jth class at the kth queue. This is a large number of possible state combinations, even in the case when we want to calculate the probability of having n i customers at queue i, i runs from 1 to N, where N is the number of queues at the network. However, we may reduce this state space due to the so-called insensitivity property of the BCMP networks [8]. According to this property, the steady-state probabilities of the network do not depend on the service time distribution, but only the mean service time. This simplifies the numerical calculations of a network. 7. MODELING A VCT AS A BCMP NETWORK No we have the tool to analyze a VCT. The goal is to obtain the overload probability of the VCT, with respect of different assumptions. Because we do not exploit any property of the VCT, only that it is a set of cells, we can extend this model to any cell group, where we are interested in the base station overload probabilities. We can model different user types, according to their motion characteristics, call-holding times and required capacities. These types are the customer classes from the queuing point of view. Each cell is modeled as a server per customer queue, with several user classes. A new user can enter a cell in tree cases: as a new call initiated at that cell, as a handover call from outside the VCT, or as a handover call from another cell of the VCT. In the queuing network the first two cases correspond to a new customer arrival, the third is a hop from a queue to another. Similarly, a customer can leave the network by terminating its call, or by handing out of the VCT. Given the handover probabilities between cells, these are one component of the transition probabilities of the queuing network. To obtain the correct value of the transition probabilities, we need information about the call holding time and the sojourn time of the users at cells. The service time of a queue is the time that a communicating user spends in the corresponding cell. What is then the distribution of this time? As a user can leave a queue by terminating its call or by handing out of the cell, the service time is the minimum of the two time variables: call holding time and time spent in a cell between two handovers. To keep the model proper, we must assume that each call holding time is exponentially distributed. With this assumption when a mobile hands over to a new cell its service time is the same as if it had initiated its call in that cell, due to the memoryless property of the exponential distribution With the knowledge of the distribution of the time a user spends within a cell, we can determine the proper transition probabilities of the queuing network: when a handover occurs, this probability is the handover probability to the next cell (here next cell could be outside the VCT), multiplied by the probability, that the call has not terminated yet (i.e. the probability that an exponential random variable is bigger than the other with the distribution of F(t)). Now knowing the attributes of the user types (call holding time, time spent within a cell depending on the cell as well, required capacity), the probability of handovers between cells, the arrival rate of users (new calls or handover calls from outside the VCT) and the maximum capacity of the base stations we can calculate the overload probability of the VCT and the single base stations as well. 8. CONCLUSIONS In this paper I gave an outline of the problems due to handovers in the future s cellular networks and some possible solutions of this problem. I described in details the operation of the so-called Virtual Connection Tree. I described the drawbacks of the original VCT concept and proposed a possible optimization to improve the performance of the VCT. I also showed a modeling method to calculate some properties of a VCT.

REFERENCES [1] T. Liu, Bahl P., Chlamtac I, Mobility Modeling, Location Tracking and Trajectory Prediction in Wireless ATM Networks, IEEE Journal on Sel. Areas in Comm.,vol 16., Aug. 1998 [2] S. Tabbane, An Alternative Strategy for Location Tracking, IEEE Journal on Sel. Areas in Comm., vol 13., June 1995 [3] G.Y Liu, G.Q. Maguire, A Predictive Moobility Management Algorithm for Wireless Mobile Computation and Communication, Proc. IEEE Int. Conf. Universal Personal Commun., 1995 [4] D.A. Levine, I.F. Akyildiz, M. Naghshineh, The Shadow Cluster Concept for Resource Allocation and Call Admission in ATM Based Wireless Networks, IEEE Trans. on Networking, vol 6., Feb. 1997 [5] A. Acampora, M. Naghshineh, An architecture and methodology for Mobile-Executed Handoff in Cellular ATM Networks, IEEE Journal on Sel. Areas in Comm.,October 1994 [6] T.C. Wong, J.W. Mark, Connection Admission Control in a Cellular Wireless ATM Access Network, Proc. of the IEEE Globecom 98 [7] P. Fazekas, Modeling a Virtual Connection Tree Based Mobile ATM Network, accepted paper to IEEE VCT 99 Fall Conference, Amsterdam, Sep. 1999 [8] E. Gelenbe, I. Mitrani, Analysis and Synthesis of Computer Systems, Academic Press, London, 1980