CRH AND CRO

© 2004 Bechtel Corporation. All rights reserved. 1

INTRODUCTION

By 1992, many European countries hadoperational second generation (2G) global

system for mobile communication (GSM)systems, and GSM started to attract interestworldwide. GSM proved to be a majorcommercial success for system manufacturersand network operators, many of which enjoyedexponential growth until the end of the decade.

The most valuable and limited resource of GSM isthe available frequency spectrum, which limitsthe system capacity. The successful take-up ofGSM services led to continuous development ofsophisticated algorithms to maximize the systemcapacity. This caused a substantial technologicalevolution of GSM, with annual (and oftenbiannual) releases of new functionality, whichhave increased the complexity of the system. Theevolution of the Ericsson™ “locating” algorithm,which is very capacity-efficient but quitecomplex, with several operators unable to fullyexploit the benefits of this functionality, is an example. Underutilization of availablefunctionality, coupled with an exponentialincrease in subscriber numbers, resulted in manyoperators overdimensioning their base stationsubsystems (BSSs) with continuous aggressivedeployment of new base stations. Thus, constantchange and evolution of GSM networks havenecessitated the continuous optimization of theoffered quality of service (QoS).

Many publications on GSM describe the system, itsarchitecture, and its evolution. However, limitedsources document QoS, network performancemanagement, and optimization. Many Europeanoperators currently enjoy very good network

performance, and the industry has developed GSMoptimization expertise (mainly through trial anderror), but this expertise is not fully documented.There is usually more than one solution to a prob-lem, which (unlike for design or site acquisition)makes it difficult to proceduralize optimizationtechniques and problem solutions. Engineers needto be open-minded, with good analytical skills andgood understanding of the overall system and itsindividual components. Performance managementand QoS optimization are subjects that cannot befully taught. Expertise must be gained through trialand error, in an attempt to maintain optimum andconstant QoS offered by dynamic and ever-changingGSM networks.

This paper focuses on 2G QoS, as well as theadvantages and disadvantages of each mecha-nism available to monitor, analyze, and improveit. The paper also describes the most commonQoS shortfalls and provides improvementrecommendations, which serve as a usefulreference in performance analysis and optimi-zation for specific projects.

WHAT IS QUALITY OF SERVICE?

Overall QoS for 2G, 2.5G, and 3G systemscomprises three important components, all

of which need to be constantly monitored andoptimized as networks change in response toincreasing coverage and capacity demands:

• Accessibility – getting on the system

• Retainability – staying on the system

• Connection quality – having a good serviceexperience while using the system

Michael Pipikakis [email protected]

EVALUATING AND IMPROVING THE QUALITY OF SERVICE OF SECOND-GENERATION CELLULAR SYSTEMS

EVALUATING AND IMPROVING THE QUALITY OF SERVICE OF SECOND- GENERATION CELLULAR SYSTEMS

Abstract—This paper provides an insight into network performance management and quality of service (QoS) of matured secondgeneration (2G) cellular systems (after the pre-/post-launch testing and optimization phase). It identifies the components of QoS and theavailable mechanisms to analyze and evaluate them. The paper also identifies important key performance indicators (KPIs) that need to bemonitored and optimized and provides a way to collect and classify data for analysis. Finally, the most common QoS shortfalls and possiblesolutions are discussed.

Issue Date: September 2004Issue Date: September 2004

Bechtel Telecommunications Technical Journal 2

QUALITY OF SERVICE EVALUATION

The three mechanisms available to monitor,analyze, and evaluate QoS and take corrective

actions are customer complaints, drive tests, andnetwork statistics, all three of which are describedbelow. Each mechanism has certain advantagesand disadvantages, usually with conflictingpriorities for limited optimization resources.

Customer ComplaintsAdvantages

• Real problems experienced by customersusing the service

• Decision-forming/influential

Disadvantages• Subjective

• Often vague with little supporting data

• Often received too late to react to thesituation

• Require filtering by customer service beforebeing handled by the engineeringdepartment

Drive TestsAdvantages

• Real calls

• Cause of failure can be identified

• Good for benchmarking

• Good for network pre-launch tuning(startups and new deployment projects)

Disadvantages• Low volumes/statistically insignificant

• One terminal type

• Only ground level and in-car service

• Predetermined routes, calling patterns only

• Labor-intensive analysis

Network StatisticsAdvantages

• All calls can be monitored

• Trends can be measured, by specificgeographical areas of interest or for theentire network

• Trends are stable

Disadvantages• Indicate problems but not their causes or

solutions

• Do not differentiate customer value

ABBREVIATIONS, ACRONYMS, AND TERMS

2G second-generation3G third-generationBCCH broadcast control channelBH busy hourBL both linksBLR block error rateBSC base station controllerBSIC base station identity codeBSS base station subsystemBTS base transceiver stationCCSR call completion success rateCFR congestion failure rateCI cell identificationCRH cell reselect hysteresisCRO cell reselect offsetCS circuit switchedCTR cell traffic recordingDCR dropped call rateDL downlinkDTCHR dropped traffic channel rateDXC digital cross connectEIR equipment identity registerGPRS general packet radio serviceGSM global system for mobile

communicationHSN hopping sequence numberHSR handover success rateKPI key performance indicatorLAC location area codeLAPD link access protocol on the

D-channelMHT mean holding timeMSC mobile switching centerOFTEL Office of TelecommunicationsPS packet switchedQoS quality of serviceRF radio frequencyRTT roundtrip timeSDCCH standalone dedicated control

channelSDCCHSR SDCCH success rateSMS short message serviceTA timing advanceTBF temporary block flowTCH traffic channelTMA tower-mounted amplifier

September 2004 • Volume 2, Number 2

Established GSM operators use clearly definednetwork QoS key performance indicators (KPIs)with target thresholds to be achieved. The KPIthresholds are usually revised once a year, andnew goals are set as the business prioritieschange. Network performance management andoptimization activities ensure that QoS targets are met.

For underperforming areas (sections of thenetwork failing the KPI thresholds), optimizationprojects are initiated. Using all available methods,these projects fully analyze the performance ofthe area to understand the problems and takecorrective actions. In such optimization projects, acombination of customer complaints, drive tests,and network statistics is used. Usually, statisticalanalysis and customer complaints are used toidentify problems, while drive tests are used toverify them and/or the solution(s). However,drive tests alone cannot be relied on to provideinsight into the offered service. Drive tests canonly provide an indicator of QoS for traffic that ishighly mobile and at ground level. A largeproportion of traffic offered via mature networksis static and often originates at higher-than-ground levels. In several mature Europeannetworks there is, on average, only one handoverper call, which indicates the static nature oftraffic. This makes statistics the most usefulmechanism for identifying QoS shortfalls.However, experience is required in recognizingproblem trends, identifying the causes, andtaking corrective actions. This, in turn, requiresgood knowledge of the system, analytical skills,and experience in network performancemanagement and optimization. Nevertheless,using statistical analysis properly and to the fullestextent possible can significantly improve QoS.

WHAT NEEDS TO BE MONITORED AND OPTIMIZED?

The trends of several KPIs must be closelymonitored. A summary of the most important

KPIs that can have an impact on the offered QoSfollows.

Circuit Switched (CS) – Voice• DCR: The dropped call rate (DCR) provides

the customer-perceived dropout perfor-mance. It is calculated over an area of theentire network or a geographical area andnot on a per-cell basis, because a call cannotbe statistically related to just one cell, due tohandovers.

• Minute-Erlang/Drop: This KPI indicates theaverage time between dropped calls. It is adivision of traffic expressed in minute-Erlangs divided by the total drops and isinversely proportional to DCR. It is a goodway to evaluate the effectiveness ofoptimization activities because it takes intoaccount the carried traffic and is moresensitive to changes than DCR.

• CFR: The congestion failure rate (CFR)indicates the failure rate of assignments dueto congestion and can be used on a cell basisfor engineering, planning, and trouble-shooting purposes and on an area basis toprovide a measure of the customer-perceivedtraffic congestion. GSM operators havedeveloped sophisticated CFR formulas toaccount for the effects of features such asdirected retry and cell load-sharing when measuring customer-experiencedcongestion.

• CCSR: The call completion success rate(CCSR) can be derived either from networkstatistics or from drive test statistics. It takesinto account the fact that all failures areeither drops or unsuccessful call set-ups. Thetotal number of failures is divided by thetotal number of call attempts. It is a goodmethod to use to evaluate the networkaccessibility and retainability as perceived bythe customers. In the United Kingdom, theOffice of Telecommunications (OFTEL), agoverning body, uses CCSR from drive teststo declare the best network for QoS. Every6 months, all network operators makeapproximately 22,000 calls while driving305 pre-defined routes with clearly definedcall patterns. At the end of the cycle, theoperators submit a summary of the resultsand all drive-test files to OFTEL [1].

• DTCHR: The dropped traffic channel rate(DTCHR) indicates the drops at the cell level.It is used for engineering purposes only (andnot for reporting), to identify cells with highdrops. Optimizing these cells improves DCRand CCSR.

• SDCCHSR: The standalone dedicated controlchannel success rate (SDCCHSR) indicates therate of successful air interface signalingchannel assignments and is used forengineering purposes only, to optimize cellswith high failure rate. Optimizing such cellsimproves CCSR.

• HSR: Handover success rate (HSR) indicatesthe success of handovers. Minimizinghandover failures improves DCR.

3

Performancemanagement andQoS optimization

cannot be fullytaught. Expertisemust be gained

through trial and error.


Packet Switched (PS) – Data (GPRS)• Cell Throughput: Cell throughput is an

end-to-end KPI used at the cell and networklevels to indicate data throughput.

• RTT: Decreasing roundtrip time (RTT)delay increases throughput.

• TBF Multiplexing: Temporary block flow(TBF) multiplexing indicates the number ofusers per time slot usage of general packetradio service (GPRS) resources. A highnumber of users per time slot decreases thedata throughput.

ORGANIZING STATISTICAL DATA PRIOR TOANALYSIS

As shown in Figure 1, performance andconfiguration data are collected in the

switching nodes and usually aggregated into astatistics database and a configuration database,respectively. The statistics database is dividedinto “object types,” which correspond to differentequipment or system function blocks. Each objecttype contains several event counters. The basictime unit for data collection is 15 minutes, i.e., thebase station controller (BSC) uploads the entireobject counter data to the statistics database every15 minutes. Proposed methods for organizingand classifying the available data follow.

Observation Time IntervalsWhen manipulating statistical data, it isimportant to define appropriate time frameswithin which the data will be gathered andprocessed. The following observation timeintervals are suggested for statistical evaluation:

• Hour: Hourly statistics give a detailedpicture of network performance. They areuseful to help spot temporary problems andidentify trends.

• Peak Hour: Peak hour statistics are of greatsignificance, because they correspond to thetime of heavy utilization of networkresources. In a way, they provide the “worst-case” scenario.

• Day: Daily statistics are introduced toprovide a way of averaging temporaryfluctuations of hourly data. Problems can beidentified and corrective actions triggeredwith more confidence. Trends with dailyvalues are also used for reporting andbenchmarking.

• Online: Online statistics provide almostreal-time monitoring of the network, if this isnecessary. Statistics can be obtained directlyfrom the switching node, where outputs areavailable every 15 minutes.

Classification by Network LevelAs shown in Table 1, the monitoring process andstatistical analysis take place at different levels:

• Network-wide: The entire network (toprovide a “global” overview)

• Geographical Area or Region: All cellsbelonging to specified geographical regions(to obtain and compare results forperformance in different areas)

• City: All cells belonging to specified majorcities (to obtain and compare results forperformance in different cities)

• BSC: All cells belonging to certain switchingnodes (to obtain switching node-relatedstatistics and compare performance ofdifferent nodes)

• Cell: Individual cells as well as neighboringcell relationships

Classification by Resource Type or EventStatistics can be classified by resource type or theevents they refer to. Both user-defined formulasand “raw” counters are grouped into one of thefollowing categories:

• Random access channel measurements

• Standalone dedicated control channel(SDCCH) measurements

• TCH measurements

• Idle channel measurements

• Handover measurements

• Subscriber disconnection measurements

• Link access protocol on the D-channel(LAPD) signaling measurements

• BSC measurements

MSC

BSC

MSC

BSC

MSC

BSC

SMS

EIR

Performance Evaluation

X.25 NetworkDXCCrossconnect

PerformanceDatabase

ConfigurationDatabase Voicemail

Figure 1. Collection of Performance and Configuration Data

September 2004 • Volume 2, Number 2 5

CAUSES OF CERTAIN QoS SHORTFALLS ANDPOSSIBLE SOLUTIONS

Although the most common QoS shortfallsand suggested possible higher level

solutions are discussed, a detailed description ofthe functionality to be fine-tuned and parametersettings is beyond the scope of this paper.Because coverage, spectrum utilization, andtraffic load differ from one area to another andfrom one network to another, engineers mustdetermine optimized parameter values for aspecific area of a network.

Accessibility Optimization

SDCCH Congestion• Causes

SDCCH availability, high number of locationupdates, high level of short message service(SMS) traffic, high number of call set-up bids

• Action

– Check historical statistics of SDCCHavailability. In some systems, time slotsmay go into sleep mode. Historical datacan show if certain time slots are constantlyidle. If this occurs over a long period oftime and especially during the busy hour

(BH), a base transceiver station (BTS)restart and retest validation may berequired.

– Check for high number of location updates,call set-ups, and SMS traffic. Increasing thecell reselect hysteresis (CRH) will delayGPRS reselection. It might be wise toexpand SDCCH resources, if possible. Thiscan be done at the expense of one TCH,which can be converted to eight SDCCHs.It is advisable to aim for no SDCCHcongestion at all times.

TCH Congestion• Causes

TCH availability, missing neighbors,missing assignments in neighbor list, trafficdistribution

• Action

– Check TCH availability. TCH time slotsmay go into sleep mode. Real-time datacan show if certain time slots areconstantly idle. If this occurs over a longperiod of time and especially during theBH, a BTS restart and retest validationmay be required.

Level KPI PerformanceTarget Range QoS Attributes

Entire Network

CCSR from Drive Tests 97–99.5% Accessibility/Retainability

CCSR Calculated 98–99.5% Accessibility/Retainability

Minute-Erlang/Drop 100–250 min. Retainability

DCR 0.5–2% Retainability

Half-Rate Traffic 0–30% Speech Quality

Silence/One-Way Transmission 0–1% Speech Quality

SDCCHSR 98–99.9% Accessibility

Area or Region


DCR 0.5–1.8% Retainability


BH CFR 1–4% Accessibility

SDCCHSR 98–99% Accessibility

Major City


Half-Rate Traffic 0–20% Speech Quality



SDCCHSR 98–99.9% Accessibility

DCR 0.5–1.5% Retainability

BH CFR 0.5–2% Accessibility

All BSCs

DCR 0–1.5% Retainability

BH CFR 0.5–1.5% Accessibility/Retainability


SDCCHSR 98.5–99.9% Accessibility

All Cells

% of Cells with Dropped TCH >2% 5–10% Retainability

% of Cells with BH CFR >10% 5–15% Accessibility

% of Cells with HSR <95% 2–10% Accessibility/Retainability

% of Cells with SDCCHSR <95% 1–5% Accessibility

Table 1. Examples of QoS KPIs and Target Thresholds


– Check for cell mean holding time (MHT)and compare it with that of thesurrounding cells in the area. GreaterMHT may be due to missing or incorrectneighbor cell definitions. Check the radioplan for missing neighbor cellassignments.

– Use traffic management (load shedding)techniques that force traffic originatingnear the cell border to the surroundingcells. This can be achieved with optimumuse of capacity-efficient features such asdirected retry, cell load-sharing (trafficreason handover or changing the handoverhysteresis parameters), and handoveroffset between two neighbor cells.

– In a hierarchical cell structure, distributetraffic to lower or higher cell levels asrequired, using layer threshold and layerthreshold hysteresis.

– Redistribute traffic among cells within thesame layer, using early handover from acongested cell to another cell. This can be accomplished by adjusting handoverhysteresis and handover offset.

Note: The traffic distribution actions mentionedabove will improve GPRS performance. They willreduce TBF multiplexing and the number of PSimmediate assignment rejections and will alsoincrease GPRS throughput.

Retainability and Quality Optimization

Deterioration of Performance with SuddenIncrease in the Number of TCH Drops

• Causes

Hardware problem, handover problem

• Action

– Check historical statistics of TCHavailability. Check if there are any alarmson the cell or the transceiver or any of theTCH time slots.

– Check historical handover performancefor the cell. If some external neighbor cells(belonging to a different BSC or mobileswitching center MSC) show no successfulhand-overs, but only attempts, missing orincorrect handover definitions on theparent BSC or MSC could be the reason.

– Check whether any neighbor cells havebeen deleted or whether any are not on theair. If any neighbor cells are not on the air,the serving cell may suffer TCH

congestion and show increased MHT.There will be an increase of immediate PSassignment rejections, TBF multiplexing,and reduction of GPRS throughput.

TCH Drops due to Downlink Signal Quality• Causes

Downlink interference, coverage

• Action

– Identify cell pairs that have a high number ofhandover attempts with reasonabledownlink (DL) quality. This will help toidentify the approximate area where mobilesexperience DL interference. Check how andwhere the serving cell frequencies are reusedto identify the interfering frequencies andplan a frequency change. This is valid forbase-band frequency hopping systems. Forsynthesizer hopping systems, change thehopping sequence number (HSN). If theGPRS user is in a high interference area,there will be high value for block error rate(BLR) and poor throughput.

– When statistics show that drops are due todownlink quality, the drops may be due topoor coverage. This is more common inhierarchical cell structures where traffic isforced down to lower layers usingaggressive layer thresholds of –90 dBm orlower. Change the layer threshold toinitiate earlier handovers to higher layers.Also modify the imperative (urgent)handover parameters to initiate earlierurgent handovers to higher layers due tobad quality. For cells on the same layer, usehysteresis and hysteresis offset to initiateearly handover and modify the imperativehandover parameters to also initiate earlierhandover due to bad quality.

TCH Drops due to Uplink Signal Quality• Causes

Uplink interference, antenna feeder system,coverage

• Action

– Use cell traffic recording (CTR) and checkthe uplink quality for certain timingadvance (TA) values. Check the frequencyplan to see what frequencies are used inthese areas and schedule a frequencyretune.

– If the cell serves with a high TA value,make the cell less attractive in idle mode,using cell reselect offset (CRO).

Statisticalanalysis and

customercomplaints areused to identifyproblems, whiledrive tests areused to verify

them and/or thesolution(s).

September 2004 • Volume 2, Number 2 7

– There could be a problem in the antenna orfeeder systems. Investigate for any alarmson the site. Initiate damage assessment oncoaxial and antenna systems.

– Consider increasing antenna downtilt toreduce the service area of the cell. This canbe done if there is coverage overlap so thata coverage hole is not created.

TCH Drops due to Both Links (BL) Signal Strengthand due to Sudden Loss

• Causes

Coverage, hardware faults

• Action

– This type of problem occurs in areaswhere a cell serves a tube or tunnel. Toconfirm this, run CTR for this cell. Checkthe CTR file for both uplink and downlinksignal strength. If any cell is a better serverthan this cell, then initiate early handoverusing hysteresis and hysteresis offset.

– In hierarchical cell structures, if theaffected cell is in a lower layer and if a cellfrom a higher layer is stronger in CTR,make early handover to the higher layerusing layer threshold.

– In a duplexed transmit/receive situation, aproblem could exist in the antenna or feedersystems. Investigate for any alarms on thesite. Check the antenna feeder system.

TCH Drops due to Uplink Signal Strength• Causes

Coverage, hardware faults

• Action

– Check for any missing neighbor cellrelations or to see if any defined neighborsare out of service. Mobiles traveling incertain directions will run out of coverageand drop out.

– Run CTR for the affected cell and check TAvalues. If TA values are high, restrict thecoverage by making the cell less attractive indedicated mode with CRO and in idle modeby initiating early handover with hysteresisand hysteresis offset.

– Consider installing a tower-mountedamplifier (TMA) to boost the uplink and see if there is room for a TMA installation inthe tower.

– Check downtilt and calculate if the existingdowntilt is correct for the intended coveragearea. Increase downtilt if necessary.

– There could be a problem in the antenna orfeeder systems. Investigate for any alarmson the site. Check the feeder and antennasystems for proper operation.

Handover Performance Optimization

Handover due to Degraded Signal Quality• Causes

Downlink interference, uplink interference,coverage, antenna feeder system

• Action

– Identify cell pairs that have a high numberof handover attempts due to degradedsignal quality. Check to see how and wherethe serving cell frequencies are reused toidentify the interfering frequencies and plana frequency change. This is valid for base-band frequency hopping systems. Forsynthesizer hopping systems, change theHSN.

– When statistics show that drops are due todownlink quality, the drops may be due topoor coverage. In such cases, check the layerand layer threshold for the cell. Changinglayer threshold will help when the cells areon different hierarchical layers. If the cellsare on the same layer, change the value ofhysteresis and hysteresis offset to initiateearlier handover.

– Run CTR for the affected cell and check TAvalues. If TA values are high, restrict thecoverage by making the cell less attractive indedicated mode with CRO and in idle modeby initiating early handover with hysteresisand hysteresis offset.

– There could be a problem in the antenna orfeeder systems. Investigate for any alarmson the site. Check the feeder system.

Handover Attempts but no Successful HandoverAssignments

• Causes

Co-base station identity code/broadcastcontrol channel (co-BSIC/BCCH) planningerror, missing neighbor definition on the BSCand/or MSC

• Action

– Co-BSIC/BCCH planning errors occurwhen a cell has two neighbors with thesame BSIC and the same BCCH. Mobilesreport measurements of the surroundingcells with their BSICs and BCCHs; the BSCuses this combination to identify the cell

Although drivetests can only

provide anindicator of QoSfor traffic that is

highly mobile andat ground level,

they are good forbenchmarking and ideal for

verifying appliedoptimization

solutions.


identification (CI) of these cells and mightdirect the handover to the wrong cell. Thiscan result in many dropped calls in the area.This can be identified from many handoverattempts with no successful assignments.Change the BSIC of one of the neighborcells.

– Check handover performance if there areattempts but no successful assignments for some external neighbor definitions(neighbors on a different BSC and/or MSC).This is due to incorrectly defined externalcells, i.e., the external neighbor cell has beenincorrectly defined as a neighbor to theserving cell’s BSC with either wronglocation area code (LAC) or BSIC or BCCH.

CONCLUSIONS

Operator competency in managingperformance and optimizing QoS is not

easily taught; it is developed, rather, mainlythrough trial and error. There are three mainmechanisms for evaluating and optimizingQoS—customer complaints, drive test analysis,and statistical analysis. These mechanisms haveadvantages and disadvantages and can beutilized in parallel in large optimization projects.

Customer complaints can be objective but are alsomisleading, and this mechanism is reactive. Drive tests are good for benchmarking and moreideal for verifying applied optimizationsolutions. Statistical analysis can identify trendsbut does not provide solutions. However, it canbe a powerful tool for an experienced engineerwith good analytical skills to use to identifyproblems and apply optimization solutions. Theplethora of statistics generated in the networkswitches data must be organized before analysis.For effective network performance andevaluation, the monitoring process and statisticalanalysis must take place at different levels:network-wide, by geographical area or region, bycity, at the BSC level, and at the cell level.

Optimization solutions vary in different areasand networks but, as discussed in this paper, ageneric approach can be developed to monitorand optimize the QoS as networks continuouslychange in response to changes in offered trafficand business priorities.

TRADEMARK

Ericsson is a trademark or registered trademarkof Telefonaktiebolaget LM Ericsson.

REFERENCES

[1] Office of Telecommunications (OFTEL), “MobileNetwork Operators’ Call Success Rate Surveys –May 2003”(http://www.ofcom.org.uk/static/archive/oftel/publications/research/2003/call_survey/).

ADDITIONAL READING

• “Radio Network Parameters and Cell DesignData”– Ericsson CME20 Documentation.

• “Counters in the Measurement Database for Trafficand Event Measurements in Radio Network” –Ericsson Function Specification.

• Nokia BSS S9.• “BSC STS User Formulas” – Ericsson CME201 R9.

BIOGRAPHYMichael Pipikakis is a networkplanning and wireless tech-nology manager for Bechtel’sEurope, Africa, Middle East,and Southwest Asia Region. Hesupports ongoing and newprojects and new businessdevelopment; writes guidelinesand procedures for mobilenetwork design, planning, and

optimization; and participates in technology forums.

Michael is a mobile networks specialist with 17 years of experience in the telecommunications industry,including more than 11 years in RF planning, design,optimization, and management of the end-to-endperformance of cellular networks.

Before joining Bechtel, Michael held variousmanagement positions in the Vodafone Group’s radiosystem design and optimization department anddevelopment department over a 10-year period;worked for Cellnet UK and GEC Marconi UK; and wasa telecommunications operator in the Greek Navy.From 1999 to 2003, he was a member of the VodafoneGlobal Forum for UMTS design harmonization.

Michael has a BEng Honors in Electronics Engineeringwith Computing and Business from KingstonUniversity in Surrey, England, and an HND in RadioCommunications Systems Design from the PolytechnicSchool of Athens, Greece. He is a member of theInstitution of Electrical Engineers.

A genericapproach can be

developed tomonitor and

optimize the QoSas networkscontinuously

change.

Documents

CRH AND CRO