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Subscriber-Assisted Hando Support in Multimedia PCSy Shengming Jiang, Danny H.K. Tsang, IEEE member Department of Electrical and Electronic Engineering The Hong Kong University of Science and Technology feejiang,
[email protected] Bo Li, IEEE & ACM member Computer Science Department The Hong Kong University of Science and Technology
[email protected] ABSTRACT
Hando support is one of the key elements in cellular Personal Communication Systems (PCS). Traditional approaches hide hando support from the subscriber. However, the main diculty in hando support stems from terminal mobility which can only be controlled by the subscriber, who may again have di erent requirements of mobility support under di erent environments. Therefore, we suggest that the subscriber should participate in hando support in the following manner: rst, the subscriber is encouraged to declare the requirement of mobility support at call setup time second, when a hando cannot be supported, the subscriber should be informed in advance so that (s)he can decide whether or not to control movement since a subscriber may sacrice mobility for maintaining communication in progress. This approach can reduce call dropping rate and improve resource utilization. We will describe this approach and propose a service classication for mobility support in this paper. (y This work is supported by Hongkong Telecom Institute of Information Technology under the HKTIIT 93/94.EG01 grant.)
1 Introduction Future personal communication systems (PCS) will permit a subscriber 1 to communicate from any where at any time with di erent types of trac (e.g., data, voice and video). One of the key elements to achieve this in cellular PCS is hando support. Hando denotes the process of changing the channel associated with a connection in progress as a mobile moves to the coverage of a new cell. There are two types of hando , namely, intra-cell hando due to deteriorated channel quality or resource re-arrangement and inter-cell hando caused by mobile movement away from the current radio cell
6]. The basic requirements of hando support claimed in the literature are execution speed, reliability and transparency to the users 1]. The execution speed is measured in time which is needed to complete the hando procedure, and is particularly crucial to delay-sensitive applications such as voice. The reliability is concerned with maintaining the continuity of the communication in progress during hando . The transparency refers to that the user is not aware of any changes to quality of service during hando . The transparency of hando support requires hando procedure to be imperceptible to the users 1] 11], i.e., the user will not be aware of the hando process. This approach is referred to as transparent hando (TH) in this paper. To The subscriber here refers to the person - the user of the mobile terminals. Henceforth, the terms \user" and \subscriber" will be used interchangeably throughout the paper. 1
support quality of service (QoS) guarantee in a global roaming environment, adequate resource needs to be guaranteed in both wireline and wireless parts2 during call's lifetime. This requires the call admission control (CAC) to be implemented to ensure sucient resource to a mobile user in the radio cells that the user may roam into during communication. That is, when a hando occurs, the target radio cell should always have enough resource to support the incoming hando . However, it is dicult to provide such kind of hando support while achieving high resource utilization. The diculties mainly stem from user's mobility since (i) it is often dicult to predict user's movement and (ii) the network cannot control user's movement. Therefore, most existing hando schemes based on the TH approach estimate call's lifetime and mobility behavior of users through either modeling or measurement. Based on estimation, the CAC controller reserves an amount of resource for potential hando s when accepting a new call. However, the potential movement of a user cannot always be known by the CAC controller. Therefore, it is possible that an active mobile user may move to a radio cell which has no adequate resource for hando . In this case, the communication QoS will be degraded or even worse the call will be dropped if the movement continues. However, sometimes a user may prefer 2 Since the scarce wireless resource is often the bottleneck compared to the abundant wireline resource, by default, \resource" used in the paper means the wireless ones.
2 Transparent Hando and User Mobility In the following subsections, we will rst give a brief description to the transparent hando (TH) approach, and then classify the user's requirements of mobility support under di erent environments.
2.1 Transparent Hando Approach
The hando process consists of three successive phases: measurement, initiation and hando control, and resource allocation 8]. During the measurement, both the mobile terminal and the network keep measuring the quality of the channel in use, and tracking candidate radio cells and channels for potential hando s. When the quality of the channel is detected below a given threshold, a hando is initiated. Once a hando decision is made, crucial things are to build a new path
and allocate adequate resource for the hando -connection as quickly as possible to keep the continuity of the communication in progress. With the TH approach, the user is excluded from the hando process and cannot do anything for the hando . If a hando is successful, that is, there is sucient resource for it, the hando process is indeed transparent to the user otherwise, the user will su er QoS degradation or call dropping. To guarantee QoS for a mobile user, the CAC controller needs to consider the overall resource available in the network, the QoS requirement and the potential movement of a user in deciding whether accepting or refusing the call request. However, it is dicult to predict accurately the potential movement of a user and consequently over-allocating resource for QoS guarantee often happens. For example, a state information-based CAC strategy proposed in 4] considers not only the resource available in the current cell, but also those to be available in the adjacent cells sometime in the future 3]. Consequently, the end-user will be using expensive service caused by the extra-allocated resource. The resource for potential hando s is often estimated according to user's mobility behavior such as velocity. Faster users are generally encouraged to join macrocells and slower users typically join microcells 7]. The speed and direction of the movement of a mobile user can be detected, but the call's residual time is not easily known in prior. Therefore, it is still possible for a mobile user to move to a radio cell which has no enough resource for hando so that the QoS will degrade or the call will be dropped. Figure 1 shows the hando process with the TH approach, where a user will get one of the following results: successful hando (SHO), QoS degradation (dQoS) or call dropping (FHO). SHO pdQoS QoSd FHO minQoS
movement
to control movement in order to maintain the communication in progress. But the user cannot do so with the TH approach since no information is fed back to the user when a failing hando will happen. Consequently, the user can only su er either QoS degradation or call dropping caused by movement. Therefore, it is dicult to support unrestricted mobility without QoS degradation 2]. Observe that only the user can control the terminal mobility, and on the other hand, the unrestricted mobility support is not alway required by the user since (s)he will have di erent requirements of mobility support in di erent environments (e.g., in a bar, a car or a train). For example, a mobile-phone user sitting in a bar may not need the hando support for communication with other people however, the hando support is indispensable for a passenger who uses a mobile-phone in a moving train. With classication of these requirements, a user can declare the requirement of mobility support in the call request so that the CAC controller can allocate resource accordingly which may benet the user with cheaper services. In addition, the user's assistance in the hando procedure may facilitate the hando support and reduce call dropping rate caused by user's movement. Therefore, we suggest that the transparent hando support is only used for a successful hando . When a failing hando caused by user's movement is detected, the user should be informed in advance so that (s)he can determine whether to continue or restrict movement. With restricting movement, the continuity of the communication in progress can be maintained. These are the basic ideas of the Subscriber-Assisted Hando (SAH) approach proposed in this paper. The remainder of the paper is organized as follows. Section 2 is devoted to the introduction of the TH approach and the classication of user's requirements of mobility support. The detailed description of the SAH approach and a service classication for mobility support are given in Section 3. A comparison between TH and SAH is given in Section 4. Finally, we conclude the paper in Section 5.
QoS end of handoff
B A
handoff decision
SHO = Successful Handoff FHO = Failing Handoff dQoS = Degraded QoS pdQoS = Predefined QoS for a call minQoS = Minmum Acceptable QoS
time
Figure 1: Diagram of hando support with TH A main disadvantage of the TH approach is that it ignores the fact that a user will have di erent requirements of mobility support under di erent environments, and can assist in hando support to avoid call dropping. With this approach, a user does not declare the requirement of mobility support in the call request so that (s)her (e.g., a mobile telephone user) should pay the same price no matter whether the user is sitting in a bar or in a moving train. The requirement of mobility support under these two environments may
be di erent as discussed in the following subsection. Moreover, when a failing hando caused by user's movement is detected, the user is not informed so that (s)he cannot control the movement to maintain the conversation in progress even if the user likes to sacrice mobility. b) Controllable-moving state (CMS)
2.2 User's Requirements of Mobility Support
A user will present di erent mobilities (i.e., stationary, low speed and high speed) in di erent environments (i.e., oce building, urban area and rural area) 6]. User's requirements on mobility support will also depend on the user states during communication. In 12], the mobilities were classied into high and low mobilities, and the characteristics of di erent mobilities were discussed in 13]. In the following, we classify the user states during communication into three categories which will require di erent mobility supports as shown in Figure 2. 1. Forced-Moving State (FMS, Figure 2.a): A user in this state cannot control movement of moving objects such as a bus, train and plane where the user is only a passenger. The user can only control his/her movement within the moving objects but this movement is often trivial compared to that of the objects. Therefore, the communication QoS for a FMS user3 should be maintained during the movement of the user and the moving objects. 2. Controllable-Moving State (CMS, Figure 2.b): A user in this state often has an explicit destination of movement such as walking home, driving a car to workplace or riding a bike to school etc.. Di erent from the FMS user, a CMS user can control movement. For example, a pedestrian can temporarily stop at a conner or in a shop along with a street, and driver can reduce velocity. For the CMS user, it is better to maintain the communication QoS during movement. However, the user may be required to restrict movement to maintain the communication in progress if necessary. 3. Quasi-Static State (QSS, Figure 2.c): A QSS user often has no explicit destination of movement (e.g., roamer) or even is in a static state (e.g., sitting in a bar). This kind of users can keep themselves in a static state, or restrict movement within a given area, if necessary. Therefore, maintaining the communication QoS for a QSS user may need no inter-cell hando support. The \mobility" provided by PCS includes terminal mobility and personal mobility. The terminal mobility supports mobility of terminal equipment, and permits a user to use portable terminals through a wireless access to xed base stations. The personal mobility supports dynamic combination between users and terminal equipments with a portable 3 For simplicity, a user in FMS is called a FMS user, the same for a CMS or QSS user.
a) Forced-moving state (FMS)
c) Quasi-static state (QSS)
Figure 2: State classication for users using wireless services Table 1: Mobility requirements versus user states FMS CMS QSS NAM indispensable indispensable indispensable OLM0 indispensable indispensable indispensable OLM1 indispensable with best-e ort dispensable identity card 8]. These two kinds of mobility provide the users with network connectivity from any where and at any time. Since the personal mobility is not related to the hando issue, we only focus the terminal mobility below. The terminal mobility support is decomposed to network access mobility (NAM) and on-line mobility in communication (OLM). NAM permits a user to have network service access from any where and at any time while OLM means that if a call is accepted, the communication in progress should be guaranteed even when the user moves from one radio cell to another. Only OLM will cause the hando problem. OLM can be further divided into OLM0 and OLM1 according to the scope of user's movement. OLM0 provides a mobility support only within the landing cell where the call is admitted. In this case, no intercell hando support is required. OLM1 provides the intercell hando support which permits a user to move across cell boundaries. Table 1 lists di erent mobility requirements imposed by a user in various states. Observe that the three kinds of users have the same requirement on NAM and OLM0, which are the basic requirements to mobility. That is, all users hope to have the network access from any where and at any time, and limited movement within the landing cell during communication. However, the users will have di erent requirements to OLM1. For the FMS user, since the movement of the moving objects cannot be controlled, the OLM1 support is needed to maintain communication QoS during call's lifetime. For the CMS user, OLM1 is used as best-e ort support, and in the case of no OLM1 support, the user can maintain communication by controlling movement. For the QSS user, the OLM1 support is not necessary since the user can avoid movement
3.2 SAH-Based Service Classi cation
3 SAH and Service Classication In this section, we rst give an introduction to the SAH approach, then present a SAH-based service classication in terms of mobility support and discuss the SAH implementation.
3.1 Subscriber-Assisted Hando (SAH)
As mentioned above, a successful hando can be transparent to users however, a failing hando will make the user to su er QoS degradation or call dropping. Therefore, the network should notify the user in advance that a failing hando will happen due to user's movement so that the user can decide whether continuing or controlling movement as shown in Figure 3. Suppose at point C, the network detects a failing hando caused by user's movement and informs the user. The user may have two choices as follows. One is to restrict movement (illustrated by the dashed line) to hold the conversation in progress until enough resource is available for the hando (i.e., point D). The other is to continue movement and the call will be dropped around point B.
With the SAH approach, the network services for hando support can be classied into three categories as shown in Figure 4 according to the user states mentioned in Section 2.2. Class A corresponds to the QSS user, class B to the CMS user and class C to the FMS user. Class A service does not provide inter-cell hando support and the user can only move within the landing cell during call's lifetime. If a QSS user insists to hando to other cells, its request can be treated just as a new call request. Class B service permits a user to move anywhere during communication however, the user will be required occasionally to control movement to maintain the communication in progress. With class C service, communication QoS should always be guaranteed after the call is admitted. + allowable mobility
across cell boundaries to maintain communication.
C beyond the landing radio cell with guarantee B beyond the landing radio cell without guarantee A within the landing radio cell
SHO pdQoS
0 FHO
movement
minQoS
QoS failing handoff detected
C A
B end of handoff (stop movement)
resource available
D
handoff decision SHO = Successful Handoff FHO = Failing Handoff
pdQoS = Predefined QoS for a call minQoS = Minmum Acceptable QoS
time
Figure 3: Diagram of hando support with SAH Two kinds of assistance can be provided by a user for hando support with the SAH approach. One is that a user declares the requirement of mobility support (see Table 1) in the call request so that the CAC controller can allocate resource and charge accordingly. The other is the network should inform the user in advance that a failing hando will occur if the movement continues. By knowing a failing hando may happen, a FMS user can try to terminate communication as soon as possible a CMS user can have time to decide if it is necessary to control the movement to maintain the communication in progress and a QSS user can learn the scope of movement allowed by the QSS request.
A
B
C
+
resource allocation
Figure 4: Diagram of service classication based on SAH Declaration of mobility support requirement can help the network to eciently allocate resource. This, on the other hand, can reduce the cost per call and provide cheaper service to the user. Therefore, a user, either the sender or receiver, is encouraged by the cheaper service provided by the SAH approach to declare option of mobility support (i.e., classes A, B, C) according to the current state (i.e., FMS, CMS, QSS). Class B service can be used as the default option. The above service options will be taken into account by the CAC controller to make decision of whether accepting or refusing a call, and to allocate resource accordingly if the call request is accepted. For class A, if enough resource is available in the landing cell, the call can be accepted, and resource allocation only within the landing cell is needed. For class B, the resource allocation in both the landing cell and other cells is required but without guarantee of that the resource will always be available in the other cells in time as a hando occurs. For example, if there is enough resource in the landing cell and in its neighboring cells, the call can be accepted and the same resource allocation procedure will occur each time the user migrates to a new cell as done by the shadow cluster CAC scheme 5]. If no enough resource available in the target cell for hando is detected, the network notify the user to control movement, and inform the user again as soon as the required resource is available. For
class C, the CAC procedure needs to allocate sucient resource for a call during its lifetime. However, the trace of a FMS user is often predictable according to the topology of rail-trace and highway etc.. The detailed discussion on CAC schemes is outside the scope of the paper.
3.3 Issues on SAH Implementation
As mentioned above, the SAH approach consists of mobility declaration and mobility control. 12] suggested to have calling users key in the \tag" which indicates types of mobility during call setup for users to declare mobility support requirement. We think the same operation should also be provided to the called users. However, the mobility declaration is not mandatory. In the case of no mobility declaration made by a user, a default option, e.g., the CMS user, is used as mentioned in the above subsection. The \tag" mentioned above can be implemented by adding a special key in the future mobile terminal. Another \tag" implementation which can be used in the existing mobile terminals is to combine the mobility declaration function with the numbering scheme. For example, suppose 0, 1 and 2 are used to indicate users FMS, CMS and QSS illustrated in Figure 2, respectively. A user can compose 0, 1 or 2 just following the normal dialing to declare mobility support requirement, and the network controller will pick this number from the normal telephone number. The called user can also choose her/his option before communication when (s)he receives the calling message. To let a mobile user know when to control mobility, some kind of short alter message is necessary. When the target base station that the mobile user is going to hando to nd no enough resource available for the coming hando , the base station sends a message to the current base station with which the mobile user is communicating. Then, the current base station send an alter message to the mobile user. This message can be either embedded into the voice channel (e.g., for mobile phone) or sent via the control channel. If the alter message is embedded into the voice channel, the user will hear a special tone which tells the user to control mobility. The alter message sent via the control channel can be either displayed or sounded. Ideally, a PCS system should be designed to eciently support the TH approach while the user will seldom su er from call dropping. However, the tradeo in system design lies between low hando dropping rate and high resource utilization due to the user mobility. In the case where the user mobility is not predictable, resource reservation seems to be necessary in all the radio cells that the mobile user will probably roam into to guarantee the continuous connection during call's life-time. This is expensive since the radio resource is scarce. Therefore, the system can just guarantee the continuous connection with a certain degree to avoid such kind of resource reservation just mentioned above. In this case, the call dropping will happen during hando s. Efcient channel assignment schemes and the call admission control (CAC) are needed to reduce call dropping rate. The
CAC tries to control admission of new calls and leave reasonable space for hando s. When the current capacity of the system cannot meet the user's requirement and gives high call blocking rate, the system should increase the capacity. However, the call dropping may still happen even though all of the above have been done, Since users are bored with interruption of communication in progress and sometimes can sacrice mobility, another e ort to avoid call dropping is to ask a user to control mobility. In this case, the user will envisage two choices: either restricting movement or dropping call as mentioned in Section 3.1. What a user will benet from restricting movement are having the continuity of communication and maybe cheaper service since the system can make less resource reservation in this case.
4 Performance Comparison between TH and SAH The CAC controller needs to system-widely allocate resource to guarantee the QoS for an accepted call during call's lifetime. With the TH approach, the user does not declare the type of mobility support in the call request so that the network will treat all the users listed in Table 1 as the FMS users. As mentioned above, the network cannot always know in advance the user's movement and the call duration so that CAC-level resource allocation is often based on estimation from statistics, simulation or analytical model. This will cause the resource allocation for an accepted call overallocated compared to what the user really needs. However, the over-allocated resource cannot always provide QoS guarantee since the user may roam into a cell with lack of resource. As a result, the extra-allocated resource will be wasted and increases call-blocking rate while the user may have to pay for the extra-allocated resource. In fact, the QSS user may need no inter-cell hando support so that the resource allocation only in the landing cell can satisfy the QSS user's requirement, and the CMS user can restrict movement if necessary, as mentioned above. The SAH approach provides an opportunity for a user to declare types of mobility support in the call request so that overresource allocation for the QSS user can be avoided. This approach also lets the network to inform a user in advance that the call will be dropped if movement continues so that the user can determine what to do accordingly. QoS degradation and call-dropping will be avoided if the user restricts movement immediately. On the other hand, since the user knows the call will be dropped if movement continues, (s)he can try to terminate communication in advance, which is particularly useful for the FMS user since the FMS user cannot control the movement of the moving object where (s)he is. In the following, numerical results of call dropping rate (for hando s) and call blocking rate (for new calls) given by the two approaches are compared.
4.1 Call Dropping Rate
The TH and SAH approaches can be modeled as bu erless queues with multi- and innite- servers respectively as shown in Figure 5. Figure 5.a corresponds to the TH approach, where N is the system capacity in channels and ;1 1 is the mean time that a call will spend in the cell. Figure 5.b represents the SAH approach, which consists of Figure 5.a and a bu erless system with innite servers (Queue 2). Denote respectively by 1 and 2 the arrival rates of new calls and hando s. For the TH approach, the hando requests directly attempt to enter Queue 1, and will be dropped if all the servers in Queue 1 are busy. With the SAH approach, the hando requests will enter Queue 1 directly if there are idle servers available in Queue 1 otherwise, the requests will go to Queue 2. The time a customer spends in Queue 2 depends on (i) the time until an idle server is available in Queue 1, (ii) the residual lifetime of the call, and (iii) the time that the user can restrict movement. Therefore, ;2 1 should be the minimum time given by these three factors, and a customer will leave Queue 2 if this time is achieved. The customer will disappear if the residual time is zero otherwise, it will attempt to enter Queue 1 and will be dropped if no idle server is in Queue 1. λ1
λ2
1
µ2
µ1 µ1
(handoff)
Queue2
Queue1
2 λ2 3
N
(handoff)
otherwise
µ2
if call is terminated
(new call)
1 2
(new call)
λ1
otherwise
3
Queue1 1 µ1 µ1
2 3
N
infinite if Queue1 has idle servers
a) TH approach
b) SAH approach
Figure 5: Modeling of TH and SAH approaches The call dropping probability for hando given by TH (Ph ) and the call blocking probability for new calls given by TH (Pn) and SAH (Pn0 ) equal the probability of no idle server in Queue 1. However, the call dropping probability for hando given by SAH (Ph0 ) is a ected by the time the hando request spends in Queue 2 so that the two queues are not independent of each other. In this paper, only simulation results are given. In the simulation, we assume Poisson arrival process for both hando and new call requests, and exponential distribution for 1 and 2 (the analytical solution of this case for the TH approach can be found in 10] and 9]). In addition, 1 = 2270/hour, 1 = 35:71/hour, N = 70 channels 9], and 2 is respectively set to 220, 150 and 80 per hour. An additional parameter for SAH, mean movement control time ( ;1 ), is set to 0.02, 0.005 and 0.0001 (hour). As shown in Table 2, the call dropping probability for hando s given by SAH is smaller than that given by TH, especially in the case of ;1 = 0:02. However, the call blocking probability for new calls given by SAH is a little higher than that given by TH because the priority of using idle servers in Queue 1 is given to hando requests in Queue 2 with SAH. Observe that the e ect of ;1 to Pn0 is not monotonous. This
is because both the number of hando requests in Queue 2 and the input rate to Queue 1 from Queue 2 will a ect Pn0 , and ;1 will eventually determine ;2 1 of Queue 2. Note that the number of hando requests in Queue 2 increases with the increase of ;1 while the input rate to Queue 1 from Queue 2 decreases with the increase of ;1 since the residual lifetime of some customers leaving Queue 2 depends on ;1 for a given xed call's lifetime. Therefore, Pn0 will depend on the two e ects just mentioned. The above fact that the hando dropping probability given by SAH is smaller than that given by TH will not depend on the assumptions we used in the simulation. In fact, the reason that SAH giving smaller hando dropping probability is that the mobility control is equivalent to queuing hando requests if no enough resource is available in the target cell for hando s. Although the new call requests can also be queued, the priority of using idle servers is always given to the hando s over the new call requests with the SAH approach.
4.2 CAC-Level Resource Allocation
To provide steady QoS, the CAC controller needs to ensure enough resource for a call during its lifetime and resource pre-allocation is often adopted. As mentioned above, the TH approach treats all the users almost in the same manner in terms of mobility support. The SAH approach overcomes this weakness by asking the users to declare requirements of mobility support in the call request so that the CAC controller can allocate resource accordingly. Given the capacity of a radio cell (N channels), the number of calls the cell can admit depends on (i) demanded QoS, (ii) hando and new call arrival rates, (iii) call departure rate, (vi) the state of the adjacent cells, and (v) CAC algorithms. One crucial criteria of QoS in wireless systems is call dropping probability (PQoS ) which is the probability that an active call will be dropped during the call's lifetime. In the following, we compare the maximum number of calls a radio cell can admit (Nmax ) with TH and SAH for a given PQoS by using the distributed CAC algorithm (D-CAC) proposed in 4]. D-CAC proposed an algorithm to calculate Nmax according to the number of the active calls in the current cell and its neighboring cells, the probability of a call remaining in the same cell (ps ) and the probability of a call handing-o to the adjacent cells (pm ). These parameters are measured every estimation time T. For the case that a cell (Cn ) only has two neighbors, namely, left cell (Cl ) and right cell (Cr ), the Nmax for cell Cn at t0 + T is given by: Nmax = minfn1 n2 n3g (1) where n1 , n2 and n3 represent the individual maximum number of calls that can be accepted respectively by cells Cn, Cr and Cl at time t0 + T, which are calculated according to: n1 = 2p1 a2(1 ; ps) + 2N ; ; s
Table 2: Call dropping and blocking probability comparison between TH and SAH new call arrival rate 2 = 80 2 = 150 2 = 220 TH Ph = Pn 0.0565 0.0719 0.0876 ;1 = 0:02 0:0012 0:0015 0:0018 Ph0 ;1 = 0:005 0:0045 0:0057 0:0072 ;1 = 0:0001 0:0465 0:0578 0:0706 ;1 = 0:02 SAH 0.0589 0.0744 0.0914 Pn0 ;1 = 0:005 0.0592 0.0753 0.0930 ;1 = 0:0001 0.0582 0.0729 0.0887
p
n2 n3
a a2(1 ; ps )2 + 4N(1 ; ps ) ; pm + 2ps] (2) = 2p1 a2(2 ; pm ) ; 4 ; 2E(n)pm ;
pm
a a2(2 ; pm )2 + 16N + 8pm ; 16rp2s ] = 2p1 a2(2 ; pm ) ; 4 ; 2E(n)pm ;
(3)
m p a a2(2 ; p
m )2 + 16N + 8pm ; 16lp2s ]
(4) where r, l and n are the number of active calls in cells Cr , Cl and Cn at time t0 , respectively ( = pm r + l]). , mean new call admission rate ( = T + rps ; N and = T + lps ; N) and E(n), mean number of active calls in a cell. Parameter a are chosen based on the QoS provided by the systems according to Q(:), which is the integral over the tail of a Gaussian distribution expressed in terms of the error function (refer to 4] for detail). We consider only the CMS and QSS users since the FMS user may be treated almost identically by TH and SAH. For the comparison purpose, suppose the ratio (R) between CMS and QSS requests (either new calls or hando s) to a cell is a constant, and channel allocation for the two types of users (with SAH) is static and proportional to R. That is, NCMS =NQSS = R and NCMS + NQSS = N, where NCMS and NQSS are the number of channels allocated to the CMS and QSS users, and are equal to NR=(R+1) and N=(R+1), respectively. With the TH approach, the CAC controller does not distinguish between CMS and QSS users, and Nmax of cell Cn is given directly by Eq (1), where, pm and ps can be approximated by NCMS =N and NQSS =N, respectively. However, with the SAH approach, the CAC controller only needs to allocate resource in the landing cell for the QSS users, and can admit a new QSS call without a ecting the QoS of other calls. Therefore, the channels allocated to the QSS users, NQSS , can be fully used. Suppose SAH will treat the CMS users in the same manner as TH. Then Eq (1) can also be used to calculate the maximum CMS calls admitted by cell Cn with SAH using capacity NCMS . However, N, r and l in the original equation should be replaced by NR(R + 1);1, lR(R+1);1 and rR(R+1);1 (which are similar to the calculation of NCMS mentioned above). We use n1 , n2 and n3 to distinguish them from n1, n2 and n3 used for TH. Therefore, Nmax for cell Cn with SAH is given by: Nmax = NQSS + minfn1 n2 n3 g
(5)
Tables 3 and 4 list Nmax given by TH and SAH with N = 50 and 100 (channels) and PQOS = 0:01. Note that ps and pm indicate movement controllability of the CMS users in SAH. The larger ps , the stronger controllability the user has. As shown in Table 3, Nmax given by SAH is always larger than that given by TH for the same R, and this will become more apparent with large capacity setting as shown in Table 4. The results also show Nmax given by SAH increases when user's movement controllability becomes stronger (i.e., from ps : pm = 0:1 : 0:9 to ps : pm = 0:3 : 0:7).
5 Conclusion In this paper, a new hando support approach was proposed, which uses message between the user and the network to handle hando . By classifying the user's requirements of mobility support according to user states, this approach asks the user to declare the type of mobility support in the call request and requires the network to inform the user in advance if a failing hando will happen. It is shown that this approach can improve resource utilization by accepting more calls and reduce call dropping probability in comparison with the traditional approach. A service classication scheme based on this approach was also described, which aims to encourage the user to declare mobility support requirement to get cheaper services compared to that given by the traditional approach.
References
1] M. E. Anagnostou et al., Hando related Performance of Mobile Communication Networks, IEEE VTC, 1994, pp111-114. 2] O. Spaniol et al., Impacts of Mobility on Telecommunication and Data Communication Networks, IEEE Personal Communications, October 1995, pp20-33. 3] M. Schwartz, Network Management and Control Issues in Multimedia Wireless Networks, IEEE Personal Communications, June 1995, pp8-16. 4] M. Nagshineh and M. Schwartz, Distributed Call Admission Control in Mobile/Wireless Networks, IEEE JSAC, Vol. 14, No. 4, May 1996, pp711-716. 5] D. A. Levine et al., A Resource Estimation and Call Admission Algorithm for Wireless Multimedia Networks Using The Shadow Cluster Concept, IEEE/ACM Transaction on Networking, Vol. 5, No.1, February 1997, pp1-12. 6] Victor O.K. Li and X. M. Qiu, Personal Communication Systems (PCS), Proceedings of the IEEE, vol. 83, No. 9, September 1995, pp1210-1243
Table 3: Nmax comparison between TH and SAH with N = 50 NCMS Nmax given by TH Nmax given by SAH =NQSS ps : pm = 0:1 : 0:9 ps : pm = 0:3 : 0:7 (R) E(n) Nmax E(n) Nmax E(n) Nmax 0.1 35.00, 0.171 27.72 0.82, 0.0001 46.30 0.3 35.00, 0.115 35.78 6.07, 0.001 43.61 3.34, 0.01 44.62 0.5 35.00, 0.100 35.57 10.35, 0.01 41.67 8.35, 0.001 42.99 0.9 35.00, 0.104 34.26 16.58, 0.027 39.00 15.2, 0.001 40.67 1.5 35.00, 0.128 32.77 21.00, 0.073 36.61 21.00, 0.014 38.57 n
= 30 = = 40 at time r
l
t0
T
= 20
s
Table 4: Nmax comparison between TH and SAH with N = 100 NCMS Nmax given by TH Nmax given by SAH =NQSS ps : pm = 0:1 : 0:9 ps : pm = 0:3 : 0:7 (R) E(n) Nmax E(n) Nmax E(n) Nmax 0.1 65.00, 1.305 42.14 5.44, 0.0001 93.43 4.65, 0.0001 93.91 0.3 65.00, 1.223 53.92 20.75, 0.0001 86.64 20.75, 0.003 87.65 0.5 65.00, 1.185 54.61 33.30, 0.0001 81.62 33.33, 0.021 82.97 0.9 65.00, 1.155 54.00 47.37, 0.078 74.84 47.37, 0.116 78.84 1.5 65.00, 1.200 49.27 60.00, 0.163 68.63 60.00, 0.216 73.78 n
= 50 = = 60 at time r
l
7] G. P. Pollini, Trends in Handover Design, IEEE Communications Magazine, March 1996, pp82-90. 8] B. Jabbari et al., Network Issues for Wireless Communication, IEEE Communications Magazine, January 1995, pp88-98. 9] William C. Y. Lee, Mobile Cellular Telecommunications Systems, McGRAW-HILL International Editions, 1989. 10] L. Kleinrock, Queuing Systems, Volume II, pp13, pp215. 11] T. S. Rappaport, Wireless Communications - Principles and Practice, Prentice Hall, 1996, pp31-36. 12] D. Hong, S.S. Rappaport, Priority oriented channel access for cellular systems serving vehicular and portable radio telephones, IEE Proceedings, Vol. 136, Pt. I, No. 5, October 1989, pp339-346. 13] S.S. Rappaport, Blocking, hand-o and trac performance for cellular communication systems with mixed platforms, IEE Proceedings, Vol. 140, No. 5, October 1993, pp389-401.
t0
T
= 20
s
Danny H.K. Tsang was born in Hong Kong.
He received the B.Sc. degree in Mathematics and Physics from the University of Winnipeg, Winnipeg, Canada, in 1979, and the B.Eng. and M.A.Sc. degrees both in Electrical Engineering from the Technical University of Nova Scotia, Halifax, Canada, in 1982 and 1984, respectively. He also received the Ph.D. degree in Electrical Engineering from the University of Pennsylvania, Philadelphia, PA, in 1989. He joined the Department of Mathematics, Statistics & Computing Science, Dalhousie University, Halifax, Canada, in 1989, where he was an Assistant Professor in the computing science division. He has joined the Department of Electrical & Electronic Engineering at the Hong Kong University of Science and Technology since summer of 1992. His current research interests include statistical modeling of variablebit-rate video trac, queuing analysis of ATM multiplexer, congestion controls in B-ISDN/ATM networks, and wireless ATM. He has been a member of the Technical Program Committee for IEEE INFOCOM since 1994. His email address is:
[email protected].
Shengming Jiang received the B.Sc degree in
Computer Science and Applications from Shanghai Maritime Institute, Shanghai, China, in 1988, D.E.A. (MPhil equivalent) and Ph.D degrees in Computer Science in University of Paris VI and Universityof Versailles, France, in 1992 and 1995, respectively. From 1988 to 1990, he worked as a computer engineer in Nanjing Oil Transportation Company, Nanjing, China. He has been a research associate in Department of Electrical & Electronic Engineering since February 1995 and then in the Computer Science Department at The Hong Kong University of Science & Technology since February 1997. His research interests include medium access control (MAC) protocol design for ATMcompatible high-speed LAN and MAN and HFC systems, ATM networking, ABR service, wireless ATM and PCS.
Bo Li received the B.S. (cum laude) and M.S. de-
grees from Tsinghua University (Beijing) in 1987 and 1989, respectively, and the Ph.D. degree in the Computer Engineeringfrom University of Massachusetts - Amherst in 1993. He was previously aliated with IBM Networking System Division as sta and advisory engineer before joining the Computer Science Department of Hong Kong University of Science & Technology in January 1996. Dr. Bo Li is an active member of IEEE Technical Committee on Computer Communications and ACM Sigmobile. He has been on the Technical Program Committee (TPC) for a number of conferences, IEEE Infocom since 1996, and most recently for IEEE ICDCS'97. He is also the IEEE TCCC representative for IEEE ICC'98. His current research interests are: wireless mobile networking supporting multimedia, active networking, internetworking of ATM and IP, and all optical networks.
