Adaptive Handoff Initiation Scheme in Heterogeneous Network

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In wireless heterogeneous network, nodes are mobile
equipment and can move freely from one area to another. A
group of users with a large range of mobility can access around
in the overall network cause high traffic. In these
heterogeneous networks, resources are shared among all users
and the amount of available resources is determined by traffic
load. The traffic load can seriously affect on quality of services
for users thus it requires efficient management in order to
improve service quality. If traffic load is concentrated in a
cell, this cell becomes the hotspot cell. There is a need to have
a proper traffic driven handoff management scheme, so that
users will automatically move from congested cell to allow
the network to dynamically self-balance. This research
proposed an approach which adopts a hard handoff scheme to
dynamically control the handoff time according to the load
status of cells. The result shows that the effect of hotspot
threshold is the most important in initiation the handoff
process. Therefore, by incorporating value of traffic load as
adaptive factors, it shows how the handoff initiation criteria
might be set in accordance with the quality of services
requested by users.

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Adaptive Handoff Initiation Scheme in Heterogeneous Network

  1. 1. ACEEE Int. J. on Network Security , Vol. 03, No. 02, April 2012 Adaptive Handoff Initiation Scheme in Heterogeneous Network Azita Laily Yusof, Norsuzila Ya’acob, Mohd Tarmizi Ali, Norbaiti Sidik Faculty of Electrical Engineering, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia laily012001@yahoo.com, norsuzilayaacob@yahoo.com, mizi732002@yahoo.com, sidikmanzil@yahoo.comAbstract—In wireless heterogeneous network, nodes are mobile below a certain threshold value. However, in a heterogeneousequipment and can move freely from one area to another. A network environment, more criteria are needed to initiate thegroup of users with a large range of mobility can access around appropriate time to perform the handoff.in the overall network cause high traffic. In these This paper presents a traffic driven handoff managementheterogeneous networks, resources are shared among all users scheme which adopts a hard handoff scheme to adaptivelyand the amount of available resources is determined by trafficload. The traffic load can seriously affect on quality of services control the handoff time according to the load status of cells.for users thus it requires efficient management in order to Before accepting a new user, it requests the load informationimprove service quality. If traffic load is concentrated in a of the target cell in advance before handoff execution. Then,cell, this cell becomes the hotspot cell. There is a need to have the value of adaptive RSS is applied in the scheme to initiatea proper traffic driven handoff management scheme, so that the right handoff time. A dynamic simulator which is basedusers will automatically move from congested cell to allow entirely on MATLAB software is developed, using thethe network to dynamically self-balance. This research designed scheme.proposed an approach which adopts a hard handoff scheme todynamically control the handoff time according to the load II. PREVIOUS WORKSstatus of cells. The result shows that the effect of hotspotthreshold is the most important in initiation the handoff There also have been many proposals to solve the hotspotprocess. Therefore, by incorporating value of traffic load as cell problem. Two methods for resource controlling andadaptive factors, it shows how the handoff initiation criteria allocating in a roaming based scenario were proposed inmight be set in accordance with the quality of services [2,3,4]. A number of channel borrowing algorithms whichrequested by users. utilize available resources of lightly loaded cells andIndex Terms—heterogeneous, mobility, traffic load, hard alternatives have been proposed [5]. In the research area ofhandoff the load distribution scheme, power control and handoff based algorithms have been investigated [6,7]. In Adaptive I. INTRODUCTION Cell Sizing (ACS) scheme [6], this algorithm controls the transmitting power of the base station based on CDMA Long Term Evolution (LTE) is one of the latest cellular system. Similarly, in soft handoff resizing algorithmcommunication technology that is currently being tested and [7], it reduces the size of soft handoff area in the hotspot celldeployed. Third Generation Partnership Project (3GPP) by increasing the value of the threshold value but theseRelease 8 defines the standards for LTE and Release 10 algorithms can be only used in the particular system and itpertains to defining the standards for LTE-Advanced. SAE requires the negotiation between cells in order to supportis the core network architecture for establishing a LTE seamless services for mobiles.Network. The important factor of this network architecture is A cell which has heavier traffic load than adjacent cells isthat it is heterogeneous. A heterogeneous network is referred to as hotspot cell which can be determined bycomposed of several wireless technologies that constitute resource affordability, the ratio between the amount oftogether a network that connects users to the Internet [1]. available resources and the total amount of resources in aCore network, sometimes called backbone network, combines cell. Hotspot cell can be generated by sudden concentrationall access networks together. The technologies utilized in of traffic load and this hotspot cell problem can cause poorcore and access networks may be different, resulting in service quality [8]. [9] proposed an effective trafficdifferent characteristics. In these heterogeneous networks, management scheme using adaptive handover time. Handoffmobile users can move between different networks. In this time is adaptively controlled according to the amount of traffickind of environment, handoff management is the essential load of cells.issue that supports the handoff of users between variouswireless technologies. Handoff decision, one of the handoff III. ADAPTIVE HANDOFF TIME ALGORITHM APPROACHmanagement issues consists of finding the appropriate timeto perform the handoff and which cell to hand over in cellular In this research, an adaptive handoff algorithm for dynamicnetworks. Traditionally, the need for initiating the handoff traffic load distribution in the hotspot cell is proposed. Trafficarises when the RSS of the serving base station deteriorates© 2012 ACEEE 1DOI: 01.IJNS.03.02.15
  2. 2. ACEEE Int. J. on Network Security , Vol. 03, No. 02, April 2012arises when the RSS of the serving base station deterioratesthe acceptable service quality. Active communications between user and base stationoccur in HOLD and ON state [9]. The HOLD state has fulldownlink and thin uplink channel while ON state has bothfull downlink and uplink traffic channel. In this measurement,the load which will be added by the handoff calls also hasbeen considered and it is defined as HANDOFF. The handoffcall is assume in the ON state right after the handoff processcompleted. So, the traffic load can be estimated by measuringthe number of users in the states, HOLD, ON and HANDOFFwhich is described in Equation 1[9]. Nt = Non + β x Nhold + Nhandoff (1)where Nt is the number of traffic loads, Non is the number ofusers in the ON state, Nhold is the number of users in theHOLD state and Nhandoff is the number of handoff calls. InEquation (1), β is an adaptive factor and the number of trafficload varies from 0 to 1. The value of traffic load is approximatedto 0 when the current cell is regarded as the lightly loadedcell and as the number of mobile nodes is increase, the trafficload is approximated to 1. The current cell becomes to be thestatus of hotspot. Figure 1 shows the handoff time algorithm.The handoff time algorithm is based on the handoff schemeproposed by [10]. As shown in Figure 1, when the receivesignal strength of the serving cell is less than threshold value,it sends the load request status to the target cell and receiveload response status from the cell. The target cell calculatesthe number of traffic load using Equation (1). If the number of Figure 1. The handoff time algorithmavailable resources of the target cell is less than the hotspotthreshold, Hd, the current serving sends to hotspot alarm III. RESULT AND DISCUSSIONstatus to the target cell. After receiving the status, the proper The simulations were performed in MATLAB. Variousthreshold value should be carefully selected in order to initiate initial typical parameters assumed in the simulation arethe handoff process. However, the previous work used fixed described in Table 1 [9].RSS to initiate the handoff process. An adaptive RSSthreshold is recommended to be used so that the mobile has TABLE 1. SIMULATION PARAMETERS [9]enough time to initiate the handoff process. Therefore, thethreshold value for initiating handoff should be carefullyselected in order not to degrade the service quality of otherusers. The algorithm has been modified by applying amathematical formulation that had been derived in the [11]for controlling the handoff time and called as an adaptivereceive signal strength threshold. Receive signal strengthvalue avoids too early or too late initiation of the handoffprocess. They are completed before the user moves out ofthe coverage area of the serving network.© 2012 ACEEE 2DOI: 01.IJNS.03.02.15
  3. 3. ACEEE Int. J. on Network Security , Vol. 03, No. 02, April 2012A. Comparison Between Conventional Handoff Scheme, AnAdaptive Handoff Time Scheme and Proposed Traffic DrivenHandoff Management Scheme This section analyzes the effect of the Thresmin for theproposed traffic driven handoff management scheme.Thresmin is the most important parameter in initiating thehandoff process. It is responsible for the quality ofconnection. If it is set very low, the neighbor’s eNodeB cannotinvolve into the connection until the mobile goes far fromserving eNodeB where it is considered to be at the boundaryof the cell and the quality of service reaches a bad condition.So, there is a need for an optimum value for this threshold toget the optimum quality of service and optimum systemcapacity. In the following graphs, the curves labeled as“Thres_min=-86 dBm” indicate the proposed scheme and thecurve labeled as “Thres_min=-83 dBm” indicate an adaptive Figure 3. Effect of the Thres min on the performance of handoff drophandoff time scheme proposed by Kim et al. 2007. The labeled call rate“Thres_min=-90 dBm” indicate the conventional handoff The reason the conventional handoff scheme has a highscheme. handoff drop call rate is that it just tries to reduce traffic load of the hotspot cell even though the neighboring cells are in the hotspot status and these handoffs may be dropped in the cells. As compared to an adaptive handoff time scheme, the scheme executes handoffs without considering the speed and type of handoff. On the other hand, the proposed scheme shows lowest handoff drop call rate compared to other schemes. The current serving cell delays all handoff executions if neighboring cells are in hotspot status, which can lead to a small dropping of handoff calls. The proposed scheme also adaptively controls the handoff initiation time based on the mobile’s speed and type of handoff. From these figures, the simulations show that the optimum value for this threshold is -86 dBm. Therefore, it can be concluded that the proposed scheme can reduce the traffic load of a hotspot cell like an adaptive handoff time scheme and can achieve more a Figure 2. Effect of the Thresmin on the handoff probability balanced distribution of traffic load than the compared As shown in Figure 2, the simulation result indicates the schemes.handoff probability increases as the Thresmin increases. The B. Effects of the Hd on the Performance of Handoff Drop Callhigher the Thresmin, the earlier the mobile device initiates Ratehandoff. Therefore, the mobile device can finish handoff Figure 4 shows the effects of the Hd on the performancebefore the RSS falls below the acceptable level. However, if of the traffic driven handoff based management scheme. Thethe handoff is initiated too early, the ping-pong effect may handoff drop call rate increases as the Hd increases. If the Hdoccur causes the degradation of service performance. If the is higher than the threshold which causing significant delay,handoff is initiated too late, a UE may not have enough time the proposed scheme will not initiate handoff and thus causefor making handoff, which increases the dropping probability high handoff drop call rate. The impact is that by increasingif neighboring cells are in the hotspot status. the Hd, the network delay time will increase and this make the The following Figure 3 shows the effect of the Thresmin on duration of handoff more longer. This implies that datathe performance of handoff drop call rate. As shown in Figure communications will be delayed or even dropped when the3, the conventional handoff scheme shows a highest handoff mobile device moves across cell boundaries during heavydrop call rate among the three schemes. The proposed scheme traffic. Hence, the higher the handoff drop call rate.shows similar results to an adaptive handoff time schemeproposed by Kim et al. 2007 and a decrease of 17% at lowercapacity in the handoff drop call rate compared to theconventional handoff scheme.© 2012 ACEEE 3DOI: 01.IJNS.03.02.15
  4. 4. ACEEE Int. J. on Network Security , Vol. 03, No. 02, April 2012 scenario is higher than random distribution scenario. This is true because the number of mobiles in the hotspot scenario cross the boundary area much greater than random distribution scenario. In reality, hotspot scenario causes a big consumption in the system resources, especially the system capacity, as most of the mobiles connected to the same eNodeB which has limited number of channels and this problem will appear as an increase in the handoff drop call rate.Figure 4. Effect of the H d on the performance of handoff drop call ra teC. Effects of the Hd on the Performance of Satisfaction Rate Figure 5 shows the effect of the Hd on the performance ofsatisfaction rate. A user is said to be satisfied if his/her call isneither blocked nor dropped during the total call holdingtime. As shown in Figure 5, the satisfaction rate increases as Figure 6 Effects of the random and hotspot traffic scenario on thethe Hd decreases. In cellular systems, QoS guarantee for users performance of handoff drop call rateis the important factor to determine the system performance. D. Effects of the Different Movement on the Performance ofA side effect from this is that the Hd can be used to balance Handoff Drop Call Ratetraffic load between neighboring cells and thus enhancenetwork performance. Thus, it is important to consider traffic Figure 7 shows the effect of the different movement onload as an important factor for initiating handoff since heavy the increment of capacity. From the Figure 5.14, it shows thattraffic load causes significant degradation of network straight lines scenario causes more handoff drop call rateperformance. than random movement. This is because in straight lines all mobiles will leave the hotspot cell to the nearest cells. Thus, the minimum number of handoff drop call rate equals the number of mobile. Figure 5 Effect of the H d on the performance of the satisfaction ra teD. Effects of the Random and Hotspot Traffic Scenario on Figure 7 Effects of the different movement on the performance of handoff drop call ratethe Performance of Handoff Drop Call Rate Figure 6 shows the relation between capacity and handoff CONCLUSIONScall drop rate for random and hotspot traffic scenario. Fromthe figure, it shows that handoff call drop rate for hotspot An adaptive value for RSS using speed and handoff signaling delay information was proposed to initiate the© 2012 ACEEE 4DOI: 01.IJNS.03.02.15
  5. 5. ACEEE Int. J. on Network Security , Vol. 03, No. 02, April 2012handoff process. This handoff initiation procedure is applied [3] Johansson, K., Kristensson, M. and Schwarz, U. “Radioin a traffic driven handoff management scheme to manage resource management for roaming based multi-operator WCDMAoverloaded traffic in the SAE heterogeneous network. The networks”, Proceedings of the IEEE Vehicular Technology Conference VTC, 2004, pp. 2062-2066.handoff performance with respect to traffic load has been [4] Das, S., Sen, S. and Jayaram, R. “A dynamic load balancingevaluated. The results show that in heavy traffic load, the Hd strategy for channel assignment using selective borrowing in cellularshould be taken into account to control the handoff time. mobile environment”, Proceedings of the IEEE/ACM ConferenceThe effect of Thresmin also has been evaluated and it is on Mobile Computing and Networking (Mobicom96), 1996, pp.observed that the value of Thresmin is the most important in 73–84.initiation the handoff process. Therefore, by incorporating [5] Das, S., Sen, S., Agrawal, P. and Jayaram R. “A distributed loadvalue of traffic load, user’s speed and type of handoff as balancing algorithm for the hot cell problem in cellular mobileadaptive factors, it shows how the handoff initiation criteria networks”, Proceedings of the 6th IEEE International Symposiummight be set in accordance with the quality of services on High Performance Distributed Computing, 1997, pp. 254–63. [6] Chen, X.H. “Adaptive traffic load shedding and its capacityrequested by users. In this research, a dynamic simulator is gain in CDMA cellular systems”, Communications IEEEpresented, which incorporates the effects of the adaptive proceedings, 1995, 142(3): 186-192.and conventional handoff management schemes. The handoff [7] Verdone, R. and Zanella, A. “Performance of received powerdrop call rate has been evaluated in order to measure the and traffic-driven handover algorithms in urban cellular networks”,service quality. It was found that the proposed scheme could IEEE Wireless Communication, 2002, pp. 60-71.efficiently manage overloaded traffic in the system at lower [8] Kim, D., Kim, N. and Yoon, H. “Adaptive Handoff Algorithmscapacity, thereby support better service quality. for Dynamic Traffic Load Distribution in 4G Mobile Networks”, Proceedings of the 7th International Conference on Advanced ACKNOWLEDGEMENT Communication Technology, 2005, pp. 1269-1274. [9] Kim, D., Sawhney, M. and Yoon, H. “An effective traffic The authors would like to express their cordial thanks to management scheme using adaptive handover time in next-generationUniversiti Teknologi MARA for supporting this research. cellular networks”, International Journal of Network Management, 2007, 17(2), pp. 139-154. REFERENCES [10] Mohanty, S. and Akyildiz, I.F. “Performance analysis of a novel architecture to integrate heterogeneous wireless systems”,[1] Piamrat, K., Viho, C., Ksentini, A. and Bonnin, J-M. “Resource Journal on Computer Networks, 2007, 51(4): 1095-1105.management in mobile heterogeneous networks: state of the art and [11] Mohanty, S. and Akyildiz, I.F. “A cross layer (layer 2+3)challenges”, IRISA research reports.3G Americas, 2008. handoff management protocol for next generation wieless[2] Johansson, K., Kristensson, M. and Schwarz, U. “Radio systems”, IEEE Transactions on publication 5(10): 1347-1360.resource management for roaming based multi-operator WCDMAnetworks”, Proceedings of the IEEE Vehicular TechnologyConference VTC, 2004 pp. 2062-2066.© 2012 ACEEE 5DOI: 01.IJNS.03.02.15

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