2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC)

Enhanced Mobility Load Balancing Optimisationin LTE

Peter Szilagyi, Zoltan Vincze and Csaba VulkanNokia Siemens Networks

Budapest, Hungary{pcter.Lszilagyi, zoltan.vincze, csaba.vulkan} @nsn.com

Abstract-Self-Organising Network (SON) use cases are seenas key enablers of efficient Long Term Evolution (LTE) systemoperation. Mobility Load Balancing Optimisation (LB) is aprominent SON use case defined by 3GPP with the scope ofbalancing the load in a given coverage area by reconfiguring thehandover thresholds. When overload is detected at a given cell,the LB reduces the handover thresholds of those user equipmentsthat can be redirected to the underutilised neighbouring cells.This mechanism improves the user plane performance in theoverloaded cell. Despite the potential benefits, the available LBmechanisms have two major deficiencies, both of them causinguser experience degradation: on the one hand, they tend to over­estimate the load on the air interface, resulting in unnecessaryhandovers; on the other hand, they are either transport agnosticor have limited capability to consider the transport load duringtheir decision process. This paper provides an overview of the LBrelated problems and proposes an improved solution includingaccurate evaluation of the radio load and a transport awaremechanism for end-to-end optimisation. The performance of thesolution was evaluated by simulations.

Index Terms-Long Term Evolution, Self-Organising Net­works, Mobility Load Balancing, QoS

I. INTRODUCTION

Automated network management functions are seen askey enablers for efficient operation of large communicationnetworks such as LTE and Heterogeneous Network (HetNet)deployments, which consist of several coexisting resourcelayers (e.g., LTE macro/pico/femto cells) and different radioaccess technologies including legacy technologies such asGSM, High Speed Packet Access (HSPA) [1] and EvolvedHSPA [2]. Self-Organising Networks is a current trend with thegoal of defining use cases where automated functions can helpminimise human intervention, thereby reducing managementcost and errors caused by manual factors. Currently, SONfocuses mainly on radio driven use cases that improve theRadio Network Layer efficiency [3]. However, the reconfigu­ration of the radio parameters can have negative impact on theTransport Network Layer performance and thus on the overallquality of service (QoS): the improved efficiency at the airinterface might lead to increased load on the transport network,possibly causing QoS deterioration, resulting in poor userexperience whenever the transport resources are narrow (whichis common in case of last mile links) or when the transportlayer has been configured with a lower load assumption.Proper and efficient system operation requires that the SONmechanisms consider the status of the transport network and

its potential QoS and user experience impacts during theirdecision process whenever their scope is to improve the userplane performance. Therefore, some of these use cases mustbe extended with capabilities that prevent their negative impacton the end-to-end (e2e) QoS and user experience.

This paper discusses the e2e impacts of the Mobility LoadBalancing Optimisation use case within LTE systems, referredto in this paper as Load Balancing (LB) for short. The scopeof the LB is the optimisation of handover (HO) parametersin order to balance the load between neighbour cells withthe lowest possible number of HOs. Through the optimisedHO parameters, the system encourages earlier HOs from anoverloaded cell to its neighbours. Self-optimisation of the HOparameters according to the actual load in neighbour cellscan improve the user experience by eliminating or preventingthe overload and at the same time it can increase the systemcapacity compared to the case when static or non-optimisedHO parameters are used. In principle, such mechanisms canminimise human intervention in the network management andoptimisation and can simplify the planning process as theyallow the system to fine tune some of its own parameters.

Although LB has significant impacts on the system's userplane performance, the 3GPP documents define only theframework of LB; design and implementation details areleft open. Minimising the side-effects and the amount ofreconfigurations require that LB is activated only if thereis a real need to shift load from the overloaded cell to theneighbour cells (referred to as target cells in this context),thus proper overload detection is essential for efficient LBoperation. In certain cases, the overload detection mechanismsproposed so far (i.e., virtual [4], [5] or real load [6], [7] basedones) tend to overestimate the cell load as explained later.Therefore, we propose a new overload detection mechanism,which is able to avoid such overestimation by combining airinterface utilisation and bearer throughput measurements toenable accurate air interface load assessment.

Handing over User Equipments (UEs) from one cell toanother impacts the user experience of the active connectionsserved by the affected cells, therefore the LB algorithm shouldconsider both the air interface and transport load of the targetcells. The majority of the available LB algorithms focuses onthe radio network only and operate in a transport agnosticway; there is no guarantee that during their operation, uponresolving the overload, the user experience in the target cells is

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not affected negatively. The standardised enabler of transportaware LB is the usage of the optional Transport NetworkLoad (TNL) Information Element (IE) [8] exchanged betweenthe evolved Node Bs (eNB) over the X2 interface. Thispaper discusses why this solution is not suitable for propertransport status assessment and proposes a new mechanismthat can provide accurate information on the available transportcapacity.

The rest of this paper is organised as follows. Section IIintroduces the available LB mechanisms and discusses theirshortcomings. The proposed overload detection and transportaware mechanisms are discussed in Section III. The solutionwas evaluated with simulations; the results are presented inSection IV. Finally, Section V concludes the paper.

II. MOBILITY LOAD BALANCING MECHANISMS

When LB is activated at a given eNB (cell), prior toany other action, it initiates the Resource Status Reportingprocedure [8] with eNBs that have neighbour cells, i.e.,the potential target eNBs. After successful initialisation, thepotential target eNBs start reporting their resource availabilityperiodically to the initiating eNB. The reported IEs denotethe guaranteed bitrate (GBR) and non-GBR Physical ResourceBlock (PRB) usage, the total available PRBs, the hardwareload, the already mentioned TNL, according to [8]. These IEsenable the originating cell to keep track of the load status ofthe neighbour eNBs. The active DEs in the cell periodicallyreport those cells whose signal is worse than that of the currentserving cell but would still be acceptable. When overloadis detected in a cell, the potential target cells for LB HOscan be selected by considering the cells reported by the DEsas acceptable ones. The LB has to pick which DEs may behanded over based on how much they would decrease the loadafter their successful handover. The most suitable target cellfor each DE should be selected based on the latest knownreported status of the neighbour cells, considering that thetarget cells should still be able to cope with the additionalload both on the radio and the transport.

The LB resolves the air interface (radio) overload detectedat a given cell by indirectly triggering the HO of DEs locatedat the edge of an overloaded cell towards less loaded adjacentcells (Figure 1). The mechanism is indirect as it encouragesHOs by relaxing the HO conditions towards these cells butdoes not force the DEs to execute the HOs. In LTE, HOs areDE-assisted with eNB-based decision, i.e., the DEs measureand report the RSRP or RSRQ (Reference Signal ReceivedPower/Quality) of adjacent cells and trigger the so-called A3event when the signal of a neighbour cell becomes betterthan that of the current serving cell by a cell pair specificthreshold referred to as the HO_offset [9]. The HO conditioncan be formulated as follows (not considering hysteresis andfrequency specific offsets for the sake of simplicity):

RSRPt - HO_offseti,j > RSRP~ (1)

where DE u is served by cell i and HO_offseti,j controls whenthe DE should be handed over from cell i to j. Based on the

Figure 1. The operation of the Load Balancing: the HO_offsets between theoverloaded and neighbour cells are reduced so that UEs at the cell edge arehanded over to the less loaded cells.

reported A3 event, the serving eNB decides if a HO is neededand instructs the DE to connect to the other cell by sending itthe HO Command Radio Resource Control (RRC) message.For compatibility and consistency reasons, there are no LBspecific HO procedures or commands but the LB algorithmuses the existing HO mechanism. Accordingly, the LB algo­rithm can encourage the HO of a set of selected DEs from anoverloaded (source) celVeNB to a less loaded (target) celVeNBby reducing the cell-specific HO_offset corresponding to thetarget cell and signalling it to the selected DEs via the SystemInformation RRC message [9].

The LB framework specified by 3GPP requires four mainfeatures that each LB solution has to implement: (1) monitor­ing the air interface load in the cells controlled by the LB; (2)detecting overload in these cells; (3) selecting the set of DEsto be handed over and their respective candidate HO targetcell; and finally (4) reconfiguring the HO parameters, namelythe HO_offset. Accurate and efficient overload detection (i.e.,implementing the first and second features) is important asunnecessary reconfigurations as well as too early or too lateactions should be avoided in order to minimise the transportand user experience impacts of the LB on the neighbour cells.These impacts depend on how the candidate HO target cellis selected; the rest of this section discusses the available LBimplementations and their limitations.

A. Overload detection and candidate target cell selectionIn LTE, Radio Access Bearers (referred to as bearers in

this paper) can be mapped to nine distinct QoS classes, whichare either GBR or non-GBR classes. GBR defines the targetaverage bit rate that the air interface packet scheduler at theeNB should try to guarantee to the bearer. The scope of theLB is to assist the system in providing at least the GBR toeach active bearer even in case of overload. Optionally, the LBmechanism may be extended to non-GBR bearers as well byconsidering a desired minimum non-GBR throughput that is

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LB actions; however, it is not practical to reconfigure theHO_offset in a cell where the majority of the active bearerscan be served according to their QoS parameters (i.e., theirGBR) except for a few with bad radio conditions.

An alternative solution for overload detection is to explicitlymeasure the PRB utilisation instead of estimating it. This realload based overload detection mechanism [6] evaluates theload situation at a cell based on the measured PRB utilisationfor a given time period:

needed to provide acceptable service to these bearers; however,without loss of generality in this paper, LB is discussed incontext of GBR bearers only.

The radio overload detection mechanisms published so farcan be categorised as virtual and real load based ones. Thevirtual load based mechanisms [4], [5] estimate the amountof PRBs required to serve the GBR bearers in the cell and,based on that, calculate the ratio of the estimated number ofrequired PRBs and the number of PRBs available for user datatransmission at the cell. The amount of PRBs required to servethe GBR bearers of DE u (denoted by D u ) is estimated basedon the wideband CQlu (Channel Quality Indicator) of the DE:

,,\RL == PRB~sed(~T)c PRBc ~T

available . TTl(4)

where GBRu denotes the sum of the throughput requirementof the DE's GBR bearers in bitls, MCS(CQlu ) provides thenumber of bits that could be transmitted in one PRB for theDE and TTl is the Transmit Time Interval. The load of thecell is evaluated as the follows:

where N; is the set of the DEs in cell c and PRB~vailable

denotes the number of PRBs available for user plane datatransmission at cell c. A cell is considered overloaded andLB is activated when the virtual load exceeds 1.0, i.e., thenumber of PRBs required to serve all GBR traffic in a cell ismore than what is available.

The virtual load based overload detection has a major dis­advantage: in most of the cases, it significantly overestimatesthe PRB demand of the active bearers. The reason for thisis that the estimation is based on the wideband CQI of theDE; however, the combined time and frequency domain radiointerface scheduling in LTE systems uses frequency selectiveCQI at scheduling decisions and thus it can utilise the PRBsmore efficiently compared to the wideband CQI based capacityestimation. In [10], it was shown that the capacity gain offrequency selective CQI may reach 40%. The overestimationcould be avoided by the introduction of a corrective factor tothe PRB demand estimation but this is problematic as the exactgain of the frequency selective scheduling depends on thevelocity of the DEs and on the inter-cell interference, whichvaries with the load of the interfering cells. An additionalfactor causing overestimation is that the virtual load basedapproaches assume that the GBR bearers always use up alltheir guaranteed bandwidth. In practice, due to the limitednumber of possible bearer configurations, the GBR of thebearers may not be fully utilised by the applications runby the user; e.g., certain web applications use a keep-alivemechanism by periodically sending small packets that keeptheir connections alive and the corresponding bearers in activestate. DEs with exceptionally poor radio channel quality alsocontribute to the estimation error as their increased PRBdemand can easily raise the virtual load above 1.0, triggering

GBRu · TTlD; = MCS(CQlu )

AVL = I:uENc Du

C PRB~vailable

(2)

(3)

where PRB~sed (~T) denotes the amount of PRBs scheduledfor user data plane transmission during the previous ~T timeinterval in cell c. This mechanism detects overload when,,\~L exceeds a predefined threshold. This simple measurementmethod has the drawback that it can falsely detect overload incase the connections in the TCP dominated traffic mix (whichis the case nowadays as the vast majority of data applicationsdominating the traffic demand use TCP as transport protocol)increase their rate as long as there is free capacity. If the airinterface is the narrow resource in the cell, due to the greedynature of TCP, the real load based LB will eventually detectoverload and trigger unnecessary actions even in a situationwhen the radio interface capacity is more than enough tosatisfy the throughput requirements of the active bearers.

Due to the shortcoming of real load, TCP based trafficrequires additional measurements for proper overload detec­tion. In [7], it was proposed to scale the number of PRBsassigned to a bearer by the ratio of the guaranteed and receivedthroughput. This solution is a mixture of the virtual and realload based detection techniques and has similar overestimationproblems as the purely virtual load based solution. DEs withexceptionally bad radio conditions and bearers kept alivewithout real traffic may also lead to inaccurate cell loadevaluation, therefore this solution is still not able to properlyhandle TCP based traffic.

B. Transport and user experience impactsIn most of the cases, LTE is regarded as a complementary

technology of the already existing 2G and 3G systems thatoffload the data traffic and (whenever feasible) it is deployedon top of the available transport infrastructure in order to pre­serve the existing infrastructure investments. These transportnetworks are often capacity limited, especially the last milelinks; transient transport congestion might occur, therefore thetransport load should be considered by the LB.

Transport agnostic LB solutions in a system where some ofthe cells are transport resource limited can cause significantuser experience degradation in the target cells (eNBs) withnarrow transport since in these cases, the LB might resolvethe overload in the source cell at the cost of overloadingthe target cell's transport. For these reasons, [5] proposes asolution which, besides the radio virtual load, calculates thevirtual load of the last mile links as well, which is assessed byheuristically solving an analytical model based on the mean

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Figure 2. The main procedures of the LB mechanism: periodic status updates,DE reports, overload detection and HO_offset updates.

detection method that combines the air interface utilisation(Eq. 4) with bearer throughput measurements. The proposedmechanism detects overload when the PRB utilisation exceedsa certain threshold (THoverload) and the measured throughputis less than the cumulative GBR of active bearers in cell c:

(5)A~L > THoverload and2:THPu2: GBR

u< 1.0, U E Nc

where THPu is the measured user throughput of the bearersof UE u. The THoverload should be set close to 1 so thatunnecessary LB actions are avoided but at the same time LBactions can be initiated early enough to prevent user experiencedegradation. A good practical default value for this parameteris 0.95. The real load measurement makes it possible toavoid the overestimation caused by the wideband CQI basedestimation while the per bearer throughput measurement helpsevaluate whether the system is able to provide the minimumrequired service, e.g., the GBR to the active bearers. Whenthe measured cumulative bearer throughput is below the cor­responding total GBR of the active bearers but at the same timethe available PRBs are not utilised, the mechanism concludesthat there is no radio overload. In these cases, it is reasonableto assume that the low throughput is either due to transportcongestion or to the fact that the users have no data to betransferred momentarily; in either case, no LB actions areneeded. In contrast, when the air interface is not able to servethe bearers according to their GBR, it can be considered tobe a strong indication of air interface overload. Additionally,the mechanism considers only those bearers that were activeduring the last decision period; activity can be detected by,e.g., accounting the time since the last packet was sent in thebearer and declaring it inactive if that time exceeds a limit.

Transport aware LB operation requires that the transportresources available at the candidate eNBs are known at thesource eNB. The problem with the standardised TNL IE sentin the Resource Status Update messages is that it providesonly relative load indication; however, the LB should beinformed about the available bandwidth directly to facilitatea more accurate estimation of the transport impact of the LBactions. Therefore, we propose that instead of the TNL, a newIE should be sent in the Resource Status Update messages,referred to as the S1 Available BW (Figure 2). The proposednew IE makes it possible for the source cell to select the

III. IMPROVED LOAD BALANCING MECHANISM

In order to overcome the shortcomings of the available solu­tions, we propose an improved overload detection mechanismand the explicit reporting of the available transport resources.

Existing overload detection mechanisms tend to overesti­mate the radio load as discussed in the previous section. Inorder to overcome their limitations, we propose a new overload

delay and link utilisation. The goal of this solution is toequalise the weighted average of the virtual radio and transportloads between neighbour cells. Since both loads are virtual,this solution also suffers from the problem of overestimationand it does not provide accurate information on the actuallyavailable transport bandwidth.

The standardised way of collecting information on thetransport load is the use of the S1 TNL IE included in theResource Status Update messages [8] exchanged between theeNBs. This solution provides limited capability for transportload aware LB decisions as the possible discrete values ofthe IE (LowLoad, Mediuml.oad, Highl.oad, Overload) provideonly coarse information about the transport load. Relativemeasures are difficult to interpret when the load balancinghas to evaluate whether the transport bandwidth available atthe target eNB is enough to fit a bearer with a given GBR;e.g., "Highl.oad" may have different meaning depending onthe total guaranteed transport bandwidth at the target eNB.Accurate assessment of the available transport resources in thetarget eNB is necessary not only to avoid transport overloadbut also to ensure the optimal operation of the LB mechanismas erroneously overestimated transport network load statusinformation sent to the source eNB might cause users to beforced to a neighbour cell where the radio conditions are notthat favourable, causing user experience degradation.

Sustained overload in a cell deteriorates the system per­formance, that is, the ratio of user originated connectionterminations increases as the users themselves can act in casethe overload has negative impact on their experience: theycan terminate their connections or applications whenever theirexperience is below the acceptable level. Therefore, efficientLB solutions require prompt overload detection and shortlatency of the corrective actions (LB initiated HOs). The LBcan resolve an air interface overload with a latency dependingon four factors: the time required to detect overload; theRTT of the RRC signalling between the eNB and the UEsin order to update the HO_offset; the mobility of the selectedusers (UEs) as at the time the LB decision is made and theHO_offset is signalled they might not be ready for a HO(i.e., the new HO_offset is still not reached); finally, the timerequired to execute the HOs. After adjusting the HO_offset, theload is reduced only if the UEs have performed successful LBHOs to the target cells/eNBs. In case the users that generateheavy load are not at the cell edge, the HO_offset adjustmentmay not be able to actually trigger their HO to one of thecandidate target cells. This is why the LB mechanism shouldhave accurate overload detection and efficient target eNBselection.

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Figure 3. Simulated radio topology and mobility scenario

UEs that can be handed over to a cell without overloadingits transport connectivity.

Overall, the operation of the proposed LB in an overloadedcell is as follows. Based on the overload detection according to(Eq. 5) and knowing the available bandwidth at the candidatetarget eNBs, a new HO_offset value is calculated and set in thesource cell towards each target celL The new HO_offset valueis signalled over the RRC protocol to the selected DEs onlyso that the handovers of these UEs do not overload either theradio or the transport of the target eNBs. For all other activeUEs, the HO_offset value is not updated, i.e., the HO_offsetadjustment is transparent to them until they leave the cell andcome back or stay in the cell but go to idle mode and thenreconnect later. Due to the HO_offset reconfiguration in thesource cell, UEs arriving from other cells will be configuredwith the modified HO_offset values, therefore the set of DEsto be initially handed over should be determined so that theirbearers do not use up all the free transport capacity of thetarget celL Of course, as the information about the availablebandwidth of the target eNB is an earlier snapshot of itstransport status, one concern is the validity of this information,as meanwhile new bearers can be activated at the target eNBbefore the LB triggered HOs could take place, resulting insituations when despite the amount of available bandwidthindicated by the target eNB, the transport resources are notavailable after all. This can be avoided by the usage of aprohibit timer initiated at the target eNB upon reporting theamount of available bandwidth so that until the timer expires,the resources reported as available are reserved for the usersto be handed over from the source eNB.

The available bandwidth can be defined as the differencebetween the total transport capacity allocated to an eNB andthe sum of the GBRs of the active bearers including theS1 interface protocol overhead. This solution is applicablein case of carrier grade transport services, that is, whenevereNBs are connected to the network through transport tunnels(label switched paths, VLAN tunnels, pseudowires, etc.) withresource allocation, which is a common situation. When thetransport network provides no carrier grade services, i.e.,packets are routed and not carried through tunnels thus thereare no resources allocated to the eNBs, the available transportresources can be calculated only for the last mile links (asthat is directly visible to the eNB). Accordingly, the proposed

Figure 4. Simulated transport topology

solution is applicable only if the last mile links are the narrowresources, which is a reasonable assumption in the majorityof the cases. However, this solution is still superior to theknown mechanisms, which either do not consider the transportstatus at all or are limited in the same way as this solutionwith the additional drawback of not being able to provideenough information for proper operation. In addition, the airinterface load estimation method proposed by this paper hasclear advantages compared to other solutions.

IV. PERFORMANCE EVALUATION

The performance of the enhanced LB mechanism wasevaluated with simulations. The packet level simulator imple­ments the SI-U interface (GTPIUDP/IPv4 with IPv4IEthernettransport layer), the LTE Uu interface (Medium Access Con­trol/Radio Link ControllPacket Data Convergence Protocol)and the X2 interface protocols in detaiL Proportional Fair,Required Activity Detection [10] scheduler is assumed forair interface scheduling; the air interface model was basedon [11] with a 20 MHz bandwidth single input singe outputchanneL The channel quality was simulated separately for eachDE considering distance loss, shadow fading, fast fading andpenetration loss. Downlink inter-cell interference is calculatedfrom the propagation loss, momentary transmit power andresource allocation of the interfering eNBs. Intra- and inter­site handover procedures are implemented in detail; handoverdecisions were based on the reported radio measurements.

The simulated double ring radio topology consisted of sevenactive (shown in Figure 3) and twelve interference generatoreNBs, each of them having a three cell setup. The IPlEthernetbased transport topology connecting the SAE-GW and eNBsis shown in Figure 4. Two transport scenarios, differing inthe bandwidth of the last mile links, have been considered inorder to evaluate the performance of the overload detection andtransport aware mechanisms: in the normal setup, the capacityof the last mile links was 100 Mbps; in the transport limitedscenario, it was set to 15 Mbps.

The number of users in eNB2-eNB7 was six in each cell,whereas the number of users in the central cells (celll­cellj) was 45/50/55 in three different traffic scenarios referredto as low/mid/high, respectively. After the beginning of thesimulation, the users in eNB1 were moving away from theeNB along the path shown in Figure 3 with a velocity of

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3 km/h. Initially, there was no overload in the cells of eNB Ibut as the users got further from the base station, their radiochannel quality degraded and they started to overload the radiointerface. This emulated a situation where the users leave ahotspot on three roads/main exits. The simulated system timewas set to 400 seconds.

Two different traffic mixes have been investigated to assessthe performance of the LB with both UDP and TCP basedapplications. In the UDP scenario, each user was running avariable bitrate streaming application with 500 kbps averagerate over a 600 kbps GBR bearer. In the TCP scenario, eachuser had continuous file downloads via FTP over 512 kbpsGBR bearers. To emulate realistic user behaviour, user expe­rience based activity was implemented where a user terminatedits connection as soon as the received service quality droppedbelow a predefined level. An FTP user terminated its con­nection if the achieved throughput dropped below 75% of theGBR for six seconds whereas users with streaming applicationdid the same whenever the 95th percentile of the e2e packetdelay exceeded 300 ms for six seconds.

In order to evaluate the accuracy of the proposed overloaddetection mechanism, the LB algorithm proposed in [4] wasimplemented with both its original virtual load based over­load detection and with the new overload detection methodproposed in this paper with THoverload == 0.95 according to(Eq. 5). The former is referred to as LB VL, the latter is calledE-LB (Enhanced LB) and the reference case without any LBis denoted by LB OFF in the simulation results. The radioload evaluation period was set to one second and the LB couldadjust the handover offset at most by 12 dB in either direction.The E-LB also implements the proposed transport awareoperation with available transport capacity reporting. Note thatin the transport limited scenario, the evaluation of the relativeload through TNL would not give any meaningful results asthe load of the last mile links of the transport limited cellswas set to approximately 0.7 at the simulation start throughthe traffic mix (considering the 500 or 512 kbps GBR of the18 users including transport overhead); therefore, configuringthe HighLoad threshold to 0.7 or below would prohibit anyLB handovers towards these cells altogether, excluding theotherwise available bandwidth from LB purposes. Of course,a threshold configured to a higher value, e.g., to 0.8 wouldprovide similar results than the one achieved with the proposedavailable bandwidth based method, however this exampleillustrates the problem of setting proper thresholds for the TNLbased approach. On the other hand, the examined availablebandwidth based mechanism can utilise this extra bandwidthfor LB, possibly providing better system performance.

Figure 5 compares the operation of the system having no LB(LB OFF) with LB using either real load (as part of E-LB) orvirtual load (LB VL) in case of cellI was overloaded by FTPusers (high traffic scenario). The overestimation problem of thevirtual load based mechanism is clearly visible; LB VL alreadystarts to shift UEs to neighbour cells when the system is stillable to provide almost twice the GBR throughput to the activebearers. Contrary to that, E-LB starts to react (hand over UEs

Figure 5. Comparison of the virtual and real load based (enhanced) LBoperation under high FTP load in cell. .

to neighbour cells) at the right time, i.e., when the average userthroughput drops below the GBR. At the same time, E-LB isable to maintain good user experience in the overloaded cell asno user closes its connection. The E-LB improves the systemperformance compared to a system without LB, users startto close their connection shortly after the throughput dropsbelow the GBR (LB OFF). This shows that the E-LB detectsthe overload properly, thus it is able to prevent unnecessaryLB actions as opposed to the LB VL.

Figure 6 shows the number of FTP and streaming usersterminating their connections due to poor user experiencecaused by the radio overload. At each load and traffic mix, theuser retention capability of the E-LB is the best as it is ableto minimise the user originated connection terminations. Theresults show that the LB brings significant improvement to thesystem: the number of terminated connections is significantlylower compared to LB OFF; in case of high load, E-LB caneven halve the connection terminations. The overestimationof LB VL causes such an aggressive HO_offset setting that itleads to a high number of HOs, which have significant negativeimpact on the user experience; thus, instead of improving thesystem performance, LB VL even deteriorates it.

Figure 7 shows the total number of connections terminateddue to poor user experience in case of the transport limitedscenario for the investigated traffic mixes. In these cases too,the retention capability of the E-LB is the best; at high load,it can decrease the amount of connection terminations by 20­30%. The transport agnostic operation of LB VL deterioratesthe user experience significantly, which is visible by the highnumber of user terminated connections.

Figure 8 compares the operation of the system having noLB (LB OFF) with the enhanced (E-LB) and virtual load (LBVL) based LB mechanisms in the transport limited scenarioat high FTP load. Due to overestimating the load, LB VLstarts to react too early by decreasing the HO_offset towardseNB4 , which is one of the eNBs with a limited last mile link.Although LB VL is able to prevent user originated connectionterminations in the overloaded cell, by shifting users to eNB4 ,

the transport of the target eNB becomes heavily congested dueto its transport limitation. Eventually, the user experience ofall users served by eNB4 deteriorates, forcing many of them toterminate their connections. The reason for this is the transport

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Figure 6. Connections closed due to poor user experience (normal scenario).

Figure 7. Connections closed due to poor user experience (transport limitedscenario).

Figure 8. Comparison of the virtual load based and the enhanced LBoperation in transport limited system under high FTP load.

agnostic operation of LB VL which, upon detecting that theradio of the cells of eNB4 is not overloaded, considers it as asuitable LB target regardless of its limited transport. Contraryto that, E-LB starts to shift users significantly later but stillin time to avoid connection termination in the overloadedcell-, Moreover, based on the information provided by the S1Available BW IE, it is able to determine the accurate numberof users to be shifted to eNB4 without overloading its last milelink; thus, it keeps the user experience acceptable both in ce1l2and eNB4.

V. CONCLUSION

Mobility Load Balancing Optimisation is a SON use casewith the scope of detecting and resolving radio overloadby handing over UEs from overloaded cells to less loaded

adjacent cells. Typical drawbacks of the available LB mech­anisms are the overestimation of the radio load, resulting inunnecessary handovers and no or limited capability of con­sidering the status of the transport network, possibly causingtransport congestion in case the overload is shifted to cells withsufficient radio resources but limited transport capacity. Thispaper has proposed an enhanced load balancing that improvesthe existing solutions via an accurate radio load evaluationmechanism based on radio interface utilisation and throughputmeasurements and a transport load aware LB decision mech­anism. Additionally, instead of resorting to relative or virtualmetrics as in existing solutions, the proposed LB considersthe available transport capacity when selecting the users to behanded over to the neighbour cells.

Simulation results show that in systems with no transportlimitation, the proposed LB is able to maintain better systemlevel user experience due to its enhanced radio overload detec­tion compared to either the virtual load based LB or the casewhen LB was disabled. Additionally, in the examined transportlimited system, the enhanced LB can not only alleviate theradio overload but due to its transport aware mechanism, itsuccessfully prevents the transport limited cells from becomingcongested by the users handed over from overloaded cells.

ACKNOWLEDGEMENT

The work was performed in the context of the MEVICO(CP7-011) project of the EUREKA CELTIC cluster and theMEVICO.HU project that is partially funded by the HungarianNational Development Agency.

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[7] R. Kwan, R. Arnott, R. Paterson, R. Trivisonno, and M. Kubota, "OnMobility Load Balancing for LTE Systems," in Vehicular TechnologyConference Fall (VTC 2010-Fall), 2010 IEEE 72nd, Sep. 2010, pp. 1-5.

[8] 3GPP, "Evolved Universal Terrestrial Radio Access Network (E­UTRAN); X2 application protocol (X2AP)," 3rd Generation PartnershipProject (3GPP), TS 36.423, Mar. 2012.

[9] --, "Evolved Universal Terrestrial Radio Access (E-UTRA); RadioResource Control (RRC); Protocol specification," 3rd Generation Part­nership Project (3GPP), TS 36.331, Mar. 2012.

[10] H. Holma and A. Toskala, Eds., LTE for UMTS. John Wiley & Sons,2009.

[11] 3GPP, "Physical layer aspect for evolved Universal Terrestrial Radio Ac­cess (UTRA):' 300 Generation Partnership Project (3GPP), TR 25.814,Oct. 2006.

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