Interference aware vertical handoff decision algorithm for quality of service support in wireless heterogeneous networks

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Interference aware vertical handoff decision algorithm for quality of service support in wireless heterogeneous networks
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  Interference aware vertical handoff decision algorithm for qualityof service support in wireless heterogeneous networks Celal Çeken a, * , Serhan Yarkan b , Hüseyin Arslan b a University of Kocaeli, Technical Education Faculty, Electronics and Computer Education Department, 41380 Kocaeli, Turkey b Department of Electrical Engineering, University of South Florida, 4202 E. Fowler Avenue, ENB–118, Tampa, FL 33620, United States a r t i c l e i n f o  Article history: Received 9 January 2009Received in revised form 8 September 2009Accepted 25 September 2009Available online 12 October 2009Responsible Editor: Ing. W. Kellerer Keywords: Vertical handoff Heterogeneous networksDecision makingFuzzy logicInterference a b s t r a c t Next generation wireless networks concept aims at collaboration of various radio accesstechnologies in order to provide quality of service (QoS) supported and cost efficient con-nections at anywhere and anytime. Since the next generation wireless systems areexpected to be of heterogeneous topology, traditional handoff (horizontal handoff/hand-over) mechanisms are not sufficient to meet the requirements of these types of networks.More intelligent vertical handoff algorithms which consider user profiles, applicationrequirements, and network conditions must be employed in order to provide enhancedperformance results for both user and network. Moreover, frequency reuse of one (FRO)seems to be the strongest candidate of deployment options for next generation wirelessnetworks; therefore, interference conditions gains a significant attention in vertical hand-off decisionmakingprocess. Inthisstudy, afuzzylogic-basedhandoffdecisionalgorithmisintroduced for wireless heterogeneous networks. The parameters; data rate, received sig-nal strength indicator (RSSI), and mobile speed are considered as inputs of the proposedfuzzy-based system in order to decide handoff initialization process and select the bestcandidate access point around a smart mobile terminal. Also, in contrast to the traditionalfuzzy-based algorithms, the method proposed takes ambient interference power, which isreferred to as interference rate, as another input to the decision process. The results showthat the performance is significantly enhanced for both user and network by the methodproposed.   2009 Elsevier B.V. All rights reserved. 1. Introduction Aswirelesscommunicationevolves, manydifferentsig-nalingschemesandmethodsemergeandarestandardized.Despite the obvious dominance of some specific types of networks in daily life such as cellular mobile networks,emergence of new standards forces different types of net-works to coexist. Therefore, the concept ‘‘next generationnetworks” needs to allow for heterogeneous structureand to aim at collaboration of these various wireless tech-nologies in order to provide quality of service (QoS)supported and cost efficient connections at anywhere andanytime.Even though heterogeneous network structure is a verybig concern by itself, terminals within the networks bringabout some other issues for the next generation wirelessnetworks. In this regard, it can be said that the next gener-ation wireless networks need to include terminals that areableto: (i) beawareof the existenceof heterogeneousnet-works around, and (ii) manage seamless transitions be-tween existing networks when necessary. Considering (i)and (ii) together, one can deduce that recently emergingtechnology called cognitive radio (CR) can be a remedyfor both, since CRs are able to be aware of, learn about,andadapt tothechangingconditionsinradioenvironment 1389-1286/$ - see front matter   2009 Elsevier B.V. All rights reserved.doi:10.1016/j.comnet.2009.09.018 *  Corresponding author. Tel.: +90 2623032240. E-mail addresses:  cceken@kocaeli.edu.tr (C. Çeken), syarkan@mail.usf.edu (S. Yarkan), arslan@eng.usf.edu (H. Arslan). Computer Networks 54 (2010) 726–740 Contents lists available at ScienceDirect Computer Networks journal homepage: www.elsevier.com/locate/comnet  [1]. Here, note that the term ‘‘radio environment” hasmany aspects such as physical propagation environment,radio frequency spectrum, available networks and termi-nals around, and so on. Because these aspects are highlydynamic, capabilities of CRs become crucial from the per-spective of both individual terminals and networks includ-ing them. Along with CR, cooperative networks conceptshouldalsobeconsideredinthecontextofnextgenerationwireless systems. The cooperative networks concept as-sumes that all of the wireless technologies such as cellularnetworks,wirelesslocal/metropolitanareanetworks,wire-less personal area networks, short range communications,anddigitalvideo/audiobroadcastingcancoexistinaheter-ogeneous wireless-access infrastructure and cooperate inan optimal way in order to provide highspeed and reliableconnectivity anywhere and anytime [2].In addition to the considerations related to the capabil-itiesofbothterminalsandnetworks,nextgenerationwire-less networks should also provide high data ratetransmission despite their heterogeneous topology andcomplex structure. Moreover, they are desired to performas close to wired networks as possible over wireless med-ium in terms of cost efficiency and of supporting highlysophisticated services that imply seamless transmissionof different traffic types such as voice, data, and video.Handoff is described as a process of transferring anongoing call or data session from one access point to an-other in wireless networks. When all of the aforemen-tioned aspects are contemplated, it is not difficult toconclude that handoff will be one of the vital mechanismsfor next generation wireless networks. Traditional handoff process, which is called horizontal handoff, takes place toprovide an uninterrupted service when a user moves be-tween two adjacent cells. Generally, horizontal handoff process is initialized when the link quality conditionparameters such as received signal strength indicator(RSSI), signal-to-noise ratio (SNR), and so on drop belowa specified handoff threshold. Because the next generationwireless systems involve a heterogeneous topology, tradi-tional handoff mechanisms will not be sufficient. There-fore, a new type of handoff, which is known as ‘‘verticalhandoff,” is introduced. Vertical handoff is defined as aprocess which transfers a user connection from one tech-nology to another such as a transfer from Global Servicefor Mobile (GSM) to WLAN or to WiMAX. Vertical handoff requires more intelligent algorithms which evaluate moreparameters such as interference power, monetary cost,QoS, remaining energy, and so on in addition to alreadyexisting link quality condition quantifiers. Among all of the parameters, interference must be treated in a separateplace, since every wireless system is interference limited.In traditional cellular-based systems, harmful impact of interference is tried to avoid/minimize by reusing theavailable frequencies in distant cells, which is called ‘‘fre-quency reuse.” In the literature, frequency reuse is quanti-fied by a factor called ‘‘frequency reuse factor” whichrepresentsthedistinctnumberoffrequencysets(orequiv-alently, number of cells) in a cluster. In this regard, mini-mum frequency reuse factor can be one and it is called‘‘frequency reuse of one (FRO)” or universal frequency re-use. FRO implies that each cell is allowed to use the entirespectrum available. Although frequency reuse is a veryeffective method in combating interference, it comes attheexpenseof inefficientspectrumusageandof expensivedesign processes. In contrast to traditional systems, FROseems to be the strongest candidate in order to avoidexpensive planning process and to overcome the problemof under utilized resource use in next generation wirelessnetworks. It must be noted that FRO causes significantinterference levels especially in the vicinity of cell bordersin return. This renders interference one of the most criticalparametersinhandoff processfor next generationwirelessnetworks.In the light of discussions given above, it is clear thatinterference, data rate, and mobility constitute the threeprominent aspects of the next generation wireless net-works. In this study, a new smart mobile terminal (SMT)is proposed. The proposed SMT is assumed to have cogni-tive capabilities such as sensing the environment periodi-cally for available radio access technologies (RATs),evaluating their working conditions using its fuzzy logic-based algorithm, triggering handoff process if necessary,and deciding the best access point (AP) to camp on. Thedecision is based on interference rate, data rate, and RSSIdue to the following reasons: Interference rate quantifieshowsevere the ambient co-channel interference power le-vel, data rate takes into account the available transmissionrate for applications carried out, whereas RSSI roughlyhelps to evaluate the mobility. The proposed SMT is mod-eledandsimulatedusingOPNETModelerSoftwareforper-formance evaluation. Besides, the fuzzy logic-basedhandoff algorithm incorporated in SMT is implemented inMATLAB Software. The contributions of this study can besummarized as follows:   Consideringthefactthatmost ofthewirelesscommuni-cation systems are interference limited, in contrast tothe most of the fuzzy-based algorithms, the decisionmechanism in the method proposed takes into accountinterference rates from different base stations as inputtoitsfuzzylogicsysteminordertomakeamorereliablehandoff.   A new adaptive multi-criteria handoff decision system,which has the ability to adapt its structure accordingtotheapplicationrequirementsandnetworkconditions,is proposed.   A new cognitive smart terminal, which senses the envi-ronment for available APs and changes its workingparameters such as frequency band, bandwidth, modu-lation scheme, medium access control (MAC) protocoland so on in order to camp on an appropriate AP, isdeveloped.Theremainderofthepaperisorganizedasfollows:Sec-tion 2 presents related works to the vertical handoff in theliterature.Section3providestheproposedmodelsforSMT,handoff, and base station (BS). Section 4 includes exampleheterogeneous network scenarios which have overlappingRATs with different working parameters as well as pro-posedSMT,followedbyperformanceevaluation.Thepaperis concluded with Section 5 providing final remarks and adiscussion. C. Çeken et al./Computer Networks 54 (2010) 726–740  727  2. Related works Although the vertical handoff concept is relatively new,several studies can still be found in the literature. In [3],the authors discuss different factors and metrics whichare considered when triggering handoff. Besides, they de-scribe a vertical handoff decision function (VHDF) whichenables devices to assign weights to different network fac-tors such as monetary cost, QoS, power requirements, per-sonal preference, and so on.A novel fuzzy logic-based handoff decision algorithmfor the mobile subsystem of tactical communications sys-tems is introduced in [4]. Handoff decision metrics used in[4] are: RSSI, the ratio of the used capacity to the totalcapacity for the access points, and relative directionsand speeds of the mobiles to APs. The authors comparetheir algorithmwith the RSSI-based handoff decision algo-rithm as well. Note that in [4, Eq. (3)], ambient interfer-ence power is embedded into the parameter of capacity,rather than being used as a direct input to the decisionprocess.In [5], the author presents a review on the proposedvertical handoff management, and focuses on the decisionmaking algorithms in vertical handoff. The article [6] pre-sents a tutorial on the design and performance issues forvertical handoff in an envisioned multi-network fourth-generationenvironment.In[7], theauthorsgiveafuzzylo-gic based vertical handoff scheme involving some keyparameters andthe solutionof the wireless networkselec-tion problem using a fuzzy multiple attribute decisionmaking (FMADM) algorithm.Itisconsideredthatadaptationiscrucialfornextgener-ationwirelessnetworksfromeveryaspect,suchashandoff management and scheduling, since FROseems to be one of the strongest deployment candidates [8–10]. Becauseinterference is a very dynamic phenomenon, success of the adaptation of next generation wireless networks de-pends on being aware of the factors affecting it [11,12].Therefore, the traditional fuzzy-based algorithms mightnot be able to meet the requirements of next generationwireless networks unless they take into account interfer-ence in their decision procedures. To the best knowledgeof authors, none of the fuzzy-based handoff algorithmsconsiders ambient interference power level as a direct in-put to their decision mechanisms. 3. The proposed models and algorithms for verticalhandoff  Verticalhandoffisaprocessissuecomparedtohorizon-tal handoff as explainedearlier. The cognitivesmart termi-nal proposed in this study is in complete charge of managing the handoff process as well as its other func-tions. It scans the environment periodically for availableAPs, obtains the operating parameters, combines and pro-cesses all necessary parameters using its fuzzy logic-basedclassifier, initializes handoff process, and chooses the bestcandidate AP. The following subsections include the pro-posed models and algorithms implemented using OPNETModeler simulation tool and MATLAB software.  3.1. Smart terminal process model Theproposedsmartterminalprocessmodelhasacross-layer design and is developed using OPNET Modeler soft-ware. It includes physical, MAC, and some upper layerfunctions. It has a carrier sense multiple access/collisionavoidance(CSMA/CA) MACmoduleforthewirelessfidelity(WiFi) capability and a GSMmodule to handle GSMopera-tions. Besides, it has a fuzzy logic-based smart handoff decision unit which is in charge of managing all of thehandoff operations.Fig. 1 outlines the state transition diagram of the SMTprocess model. The process starts with the  Init  state. Thisstate performs a delay until the other processes in thesimulation are initialized and loads the control variables.Then the process enters the  Spectrum Scan  and  Handoff  Fig. 1.  The SMT cross-layer process model.728  C. Çeken et al./Computer Networks 54 (2010) 726–740  Decision  states which are responsible for scanning theenvironment for available APs and managing the entirehandoff process exploiting the proposed fuzzy logic-basedhandoff algorithms. The WiFi Mode and GSM Mode statesstand for WiFi and GSM functionalities, respectively.During the spectrum sensing phase, SMT listens towireless medium for any handoff broadcast packet whichmight be sent by potential APs for a specified time span.All of the GSMAPs has a broadcast control channel (BCCH)whichisthefirstchannelofallocatedspectrumandisusedfor broadcasting network information periodically for pos-sible handoff process in additionto its other functions. Thedetailed information about GSM technology can be foundin [13]. The WiFi APs broadcast a handoff informationpacket periodically for this purpose as well. During the lis-tening period, the SMT changes its working parameterssuch as frequency, modulation, data rate, and bandwidthin order to adapt to any possible AP and to receive handoff broadcast packet.When any AP is available, SMT receives the handoff broadcast packet and extracts the network workingparameters. It then invokes fuzzy-based handoff decisionalgorithm which takes these parameters as inputs; pro-cesses them; and produces an output called AP candidacyvalue (APCV). APCV is generally defined by a real numberin order to quantify the strength of the candidacy level of the AP found. For instance, APCV can be designed to varybetween one and ten where one denotes the weakest,whereas ten represents the strongest candidacy level of quantification. Subsequently, all the aforementioned net-work parameters along with APCV are stored in the hand-off decision table (HDT) for further usage.All of these steps are repeated until the scan process isterminated. In each turn, SMT listens to the environmentfor potential APs, receives the handoff broadcast packetof theAPfound, calculatestheAPCVusingitsadaptivefuz-zyinferencesystem,andstoresallofthepiecesofinforma-tion required in the HDT.The sequencediagramof the proposedhandoff decisionalgorithm is outlined in Fig. 2. This schema is repeated inevery 10s throughout the simulation run time.As soon as the scan process is completed, APCV of eachavailable AP is compared with that of current APs. If thedifference between the compared values is equal to orgreater than the handoff resolution (HR) 1 , that is a valuedetermined by user, then the second condition, i.e., mo-bile speed, is evaluated. The mobile speed 10km/h is se-lected as a threshold value. Any speed value below thisthreshold is regarded as walking speed and in this case,either any GSM or WiFi AP can be chosen as a servingnode. Otherwise, only GSM network can be preferred,since the WiFi AP might serve SMT only for a very shortduration. When these conditions are satisfied, handoff process is initialized.  3.2. Proposed handoff decision algorithm Sophisticated handoff decision algorithms should con-sider more than one criteria and a methodology to com-bine and process them. Different decision algorithmshave been proposed in the literature for vertical handoff as mentioned earlier. Artificial intelligence-based systemssuch as fuzzy logic and artificial neural networks are goodcandidates for pattern classifiers due to their non-linearityand generalization capability [4,14]. Therefore, in the pro-posed handoff decision system a fuzzy logic-based ap-proach has been adopted.Vertical handoff decision algorithm should initializehandoff process considering available network interfaces(link capacity, power consumption, link cost, and so on),system information (remaining battery), and user/applica-tion requirements (cost, QoS parameters, and so on). Theblock diagram of the proposed handoff decision system isgiven in Fig. 3.The algorithm combines the user/application require-ments and network capabilities, and produces an outputwhich is utilized to make handoff decision and to choosethe best candidate AP. 2 In the proposed handoff system,there are three inputs (data rate, interference rate, and RSSI)for fuzzy inference system. Membership functions of theseinputs are given in Figs. 4–6, respectively. In the figures,the horizontal axis indicates the crisp values of the afore-mentioned handoff parameters, whereas the vertical axis(i.e.  l  values) stands for the membership value of relatedparameter. The crisp inputs are converted into the fuzzy var-iable by means of these membership functions. Trim andtrapezoid shapes are chosen as fuzzy membership functionsdue to their capability of achieving better performance espe-cially in real time applications. The data rate (DR) input has the ability to change itsstructure according to the application requirements aswell. For instance, if the DR requirement of an applicationis 9.6Kbps (GSM data transfer), then the membershipfunction is similar to the one given in Fig. 4a. On the otherhand, when the application needs more bandwidth, e.g.,25Kbps (GPRS Class 6 traffic), then it dynamically changesits structure to adapt the new working condition as seenfrom Fig. 4b.TheinterferencerateparameterisalsoobtainedbyeachAPandsenttotheSMTinordertobeconsideredinhandoff decision process. In the proposed algorithm, interferencerate refers to a special fuzzy logic variable whose value isdetermined by the ambient CCI power level. In GSM, Thespecification regarding the CCI level (GSM 05.05) recom-mends that the carrier-to interference ratio (C/I) is at least9dB in order to meet the bit-error rate (BER) requirement.This indicates that for a reference signal level of   101dBm, which is the standard value for a GSM mobilestation, CCI power level should be less than   110dBm.However, in a typical GSM deployment, it is reported that 1 Handoff resolution (HR) value is used to introduce a hysteresis to theproposed vertical handoff algorithm. Mobile terminal takes into accountthe HR value in order to decide whether any handoff process is required ornot. If the candidacy level of any potential AP is greater with an amount of specified HR value than that of the current AP, then the handoff process isinitialized. 2 It is worth mentioning here that data rate and interference ratiocalculations in Fig. 3 can be considered as parameters related to the user/application requirements, since there are certain values for these param-eters mandated by the application (e.g., data transmission or voiceservices). C. Çeken et al./Computer Networks 54 (2010) 726–740  729  C/I is around 14–15dB [15]. In this sense, interference rateparameter is designed in such a way that the power leveldifference between the desired signal and interference islowerthan  14dBisassignedtobealowfuzzylogicvalue,whereas a difference that is greater than 14dB is selectedto be a high fuzzy logic variable. The corresponding mem-bershipfunctionfor theinterferencerateparametercanbeseen in Fig. 5.The RSSI input of the fuzzy system has also the abilityto change its structure according to the network require-ments. The RSSI membership function for GSM and WiFinetworks are different as shown in Fig. 6a and b,respectively.As stated earlier, according to the inputs of availableAPs the fuzzy inference system produces an output valuebetween one and ten which describes the candidacy levelof related AP. Any handoff initialization process is decidedupon this value. One of the most crucial parts of this studyisthe newadaptivefuzzy inferencesystemwhichisdevel-oped in order to make handoff decision. A fuzzy logic sys-tem consists of three main parts: Fuzzifier, InferenceEngine, and Defuzzifier. Fuzzifier converts a crisp inputinto a fuzzy variable where physical quantities are repre-sented by linguistic variables with appropriate member-ship functions. These linguistic variables are then used inrule base of Fuzzy Inference Engine. Since there are three Fig. 2.  Sequence diagram of the proposed handoff decision algorithm.730  C. Çeken et al./Computer Networks 54 (2010) 726–740
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