7/30/2019 Dr.Ayman

1/12

Dr. Aymen Issa Zreikat

Email 1. aymen@mutah.edu.jo2. siayzrei@yahoo.com

Office Phone +962-03-2372380 ext:3251

Academic Rank Associate Professor

Faculty Science

Department Information Technology

Research Interests

Performance Evaluation of WirelessMobile Networks (uplink, downlink):Capacity bounds and call admission

control algorithms.

Simulation of Queueing theory andWireless Mobile Networks.

QoS and Resource Management ofWireless Mobile Networks (2G, 2.5G,3G and beyond, i.e. Wimax/Wi-FiTechnology).

My published papers: 25 papers.

Submitted for publication: 1 paper.

mailto:aymen@mutah.edu.jomailto:siayzrei@yahoo.commailto:siayzrei@yahoo.commailto:aymen@mutah.edu.jo

7/30/2019 Dr.Ayman

2/12

1. Aymen I. Zreikat, Suleiman Yerima, Khalid Al-Begain: Performance Evaluation and Resource Managemof Heirarchical MACRO-/MICRO Cellular Networks Using MOSEL-2, Published in Wireless PersonalCommunications, Springer (USA) , Vol. 44, No. 2, January, 2008.

Abstract

The paper presents a performance evaluation and resource management of hierarchical MACRO-/MICRO cellular networks using the

new Modeling and Evaluation Language (MOSEL-2). MOSEL-2 with new constructs has the ability to find the performance and

reliability modeling and evaluation of systems with exponential and non-exponential distributions. A MACRO/MICRO cell structure

is solved numerically and mathematically in this paper to handle the handoff calls. Additionally, a simulation program is written to

validate these results. In order to reduce the loss probability, a guard channels are introduced at the MICRO cell and channe

reservation at the MACRO cell. Additionally, the concept of queuing is introduced where there is a possibility for the handoff callsfrom both MACRO and MICRO layers to be queued when all the resources are occupied. MOSEL-2 is used to find the numerical

solution for this problem with both exponential and general exponential (GE) distribution. The performance analysis show the

efficiency of the proposed scheme to manage the handoff calls and the ability of the suggested scheme to reduce the blocking

probability of handover calls and the loss probability as the main objective is to block the new connection rather than terminating

the ongoing connection as well as balancing the load all over the whole network. It is shown in this paper that there are a set of

important factors that affect the performance, such as: reservation policy, channel allocation, handover ratio, capacity of the

queue and the variation of the inter-arrival times. These factors are discussed via some important performance measures, such as:

new call blocking probability, blocking probability of handover calls, loss probability, utilization and the average delay of the

queue.

2. Aymen I. Zreikat: Performance Evaluation of GSM-Based Networks in Underlay-Overlay Using MaximuEntropy Principle, Published in Al-Manarah Journal, Al-Byt University, Al-Mafraq, Jordan,Vol. 14, No. 3, pp103-121, 2008.

Abstract

The paper presents a performance evaluation for GSM-based cellular mobile networks in intelligent Underlay-Overlay princip(IUO) with Generalized Exponential (GE) distribution and variability in arrival and service time of the calls by the MaximuEntropy (ME) principle. In the IUO principle, the frequency spectrum of the cell is split into two layers (super and regular). One those with good (i.e., better than predefined value) C/I (Carrier-to-Interference) ratio, is called super layer and the other is for thowith low value (i.e., worse than predefined value) of C/I, is called regular layer. According to the above concepts, the analytimodel is presented (which is based on the model in [1]) and the critical performance measures of the system are produced adiscussed such as loss probability and utilization. The numerical results show that the variability of both the inter-arrival and servtimes have major effect on the system performance.

7/30/2019 Dr.Ayman

3/12

3. Ismat Al-Dmour, Khalid-Al-Begain, Aymen I. Zreikat: "Uplink Capacity/Coverage Analysis of WCDMAswitched Beam Smart Antennas in CDMA Systems", Published in Wireless Personal Communications, Spring(USA), pp. 1705-1715, Vol. 43, No. 4, 2007.

Abstract

Capacity and coverage represent, in addition to QoS, the three main requirements for W-CDMA based 3G mobile communication systems. These

conflicting requirements; i.e. optimizing one will be on the account of the other two. All three, however, depend largely on the interference levels

the system. Improvements on interference are thought to have a decisive effect on the performance of the 3G system and one important interferereduction technique is the utilization of smart antennae. In this paper, we analyze capacity/coverage on the uplink in W-CDMA system utiliz

switched beam smart antennae, SBSA, using a simple model of the antenna, while satisfying a certain minimum level of QoS. Limits imposed by b

interference from others and the limited uplink power available to any user in the cell are considered. Results of this paper are analytical formulae

capacity/coverage that take into consideration many of the important parameters of either the antennae or the WCDMA system. A sectional view

improvement gains, if any, of either capacity or coverage upon antenna upgrading/downgrading is provided. It is shown that improvements by

directional SBSA of either capacity or coverage, are only attained at high interference conditions; i.e. higher number of users when consideri

coverage improvement or smaller coverage areas when considering capacity. The higher the interference conditions are the higher gain over side lo

or more beams SBSA are needed to attain improvement.

4. Aymen I. Zreikat: Numerical solution of one GSM cell using MOSEL-2 language, in International ArabJournal of Information Technology, published inIAJIT, Al- Zarqa University, Vol. 4 , No. 2,pp. 133-140, Apr2007.

Abstract

The paper presents the modeling of one GSM cell using the MOdeling Specification and Evaluation Language, MOSEL2. MOSEL2the new version of MOSEL which is developed at the university of Erlangen, Germany. In this regards, the frequency spectrum GSM cell is divided into two layers (super and regular) according to the underlay-overlay principle. Based on this principle, the supfrequencies have better C/I (carrier-to-interference) ratio than the regular frequencies and usually used near the base station, while

regular frequencies are used for the whole cell. In this paper, and based on the above assumptions, the queueing model of GSsystems is suggested and the numerical solution of this model is presented by MOSEL2. As a result of this, the critical performanmeasures are presented and discussed.

5. Aymen I. Zreikat: "Performance Evaluation of one UMTS cell by the new modelling specification andevaluation language MOSEL-2",published in Abhath Al-Yarmouk Journal, Pure Science and EngineeringSeries, Yarmouk University, Irbid, Jordan, Vol. 16, No. 1, pp. 105-122 2007.

Abstract

In this paper, performance evaluation of one UMTS cell is presented. The UMTS stands for Universal Mobile TelecommunicatiSystems, the third generation of mobile networks. The queuing model of one UMTS cell is suggested and solved for the first time usMOSEL-2 language, which is the new version of MOSEL, developed by the group of MOSEL in the University of Erlangen, GermaThe pre-processor rule of MOSEL-2 is used in this paper, which is useful to solve the model using both exponential and noexponential distributions. The effect of important parameters on UMTS performance is studied in this analysis, such as the variabil

of service time, the availability of the codes and the effect of the arrival rate, . It is shown that the mentioned parameters have a maeffect on UMTS performance and should be taken into consideration by the network designers. Based on the above, critiperformance measures such as blocking probability and utilization are found and discussed.

7/30/2019 Dr.Ayman

4/12

6.Aymen I. Zreikat, Gunter Bolch: Performance Evaluation of Queuing Networks with Finite Capacity andnon-exponential Distribution using MOSEL-2, Published in AMSE (Association for Modelling and Simulatioin the Enterprises), Vol. 12, No. 4, 2007.

Abstract

In this paper, we present a performance evaluation of queuing networks with finite capacity queues and non-exponential distributiusing the MOdeling and Evaluation Language (MOSEL-2). MOSEL-2 is a new version of the existing MOSEL. MOSEL-2 has ability to find performance and reliability measures of systems with non-exponential distributions, while the old version of MOSEwhich has the ability to handle exponential distributions only. Most of the research in the literature have studied queuing networks wfinite capacity using only exponential distribution for both the inter-arrival and service times. In this paper, queuing networks wfinite capacity and non-exponential distribution are solved numerically using MOSEL-2. Three types of tandem queuing networks wfinite capacity are introduced: blocking after service (BAS), blocking before service (BBS) and repetitive blocking (RR). Differperformance measures are presented as a result of solving the above models, such as: utilization, blocking probability and the averanumber of jobs in the system. Furthermore, it is shown in this paper that it is possible by MOSEL-2 to approximate non-exponentdistributions by using phase-type distributions.

7. Aymen I. Zreikat : "Performance of Queueing model of One UMTS cell with R virtual zones by theMaximum Entropy Solution", Wireless Personal Communications, Springer (USA), Vol. 39, No. 2, pp. 135-142006.

Abstract

UMTS stands for Universal Mobile Telecommunications System, which is one of the third generation (i.e., 3G) cellular systems, wcome into full commercial phase by year 2005 and the first UMTS services are launched commercially in 2001. Therefore, the researof UMTS is an important and urgent task. In this paper, the performance of UMTS systems is studied through a queueing model whiconsists of one UMTS with many virtual zones to evaluate the system uplink traffic performance. The two performance measureblocking probability and system utilization are obtained by the Maximum Entropy Principle, i.e., ME solutions for SR(GGeo/GGeo/1)/N queue. SRXR (GGeo/GGeo/1)/N system means that arrival time and service time are both GGeo (GeneralizGeometric) distributed, each output port has a single server and the maximum capacity is N. After the theoretical analysis, tnumerical results are found for the idiographic example, S8X8 (GGeo/GGeo/1)/512 queueing model. Additionally, the performancethis queueing model is discussed with the effect of the parameters Ca2 (squared coefficient of variation of the interarrival time), C

(squared coefficient of variation of the service time) and the arrival rate, .

7/30/2019 Dr.Ayman

5/12

8. Ismat Al-Dmour, Khalid-Al-Begain, Aymen I. Zreikat: "Capacity Bounds Analysis of switched Beam SmartAntennas in CDMA Systems", Proceedings of UK simulation (UKSIM2006), Oxford, UK, pp. 91-96, 4-6 April2006.

Abstract

9.Zreikat A. and Al-Begain K., Smith, K. : "Comparative Capacity/Coverage Analysis of CDMA Cell inDifferent Propagation Environments", Wireless Personal Communications, Springer (USA), Vol. 28, No. 3,pp. 205-231, 2004,.

Abstract

Capacity and coverage represent, in addition to QoS, the three main requirements for W-CDMA based 3G mobile communicatsystems. These are conflicting requirements; i.e. optimizing one will be on the account of the other two. All three, however, depelargely on the interference levels in the system. Improvements on interference are thought to have a decisive effect on performance of the 3G system and one important interference reduction technique is the utilization of smart antennae. In this pap

we analyze capacity/coverage on the uplink in W-CDMA system utilizing switched beam smart antennae, SBSA, using a simpmodel of the antenna, while satisfying a certain minimum level of QoS. Limits imposed by both interference from others and limited uplink power available to any user in the cell are considered. Results of this paper are analytical formulae capacity/coverage that take into consideration many of the important parameters of either the antennae or the WCDMA system.sectional view of improvement gains, if any, of either capacity or coverage upon antenna upgrading/downgrading is provided. Itshown that improvements by the directional SBSA of either capacity or coverage, are only attained at high interference conditioi.e. higher number of users when considering coverage improvement or smaller coverage areas when considering capacity. Thigher the interference conditions are the higher gain over side lobes or more beams SBSA are needed to attain improvement.

7/30/2019 Dr.Ayman

6/12

10. Al-Begain K., Barner J., Bolch G., Zreikat A.: The Performance and reliability modeling language MOSEand its applications, International Journal in Simulation: Systems, Science and technology, Vol. 3, No. 3-4, pp66-80, 2003.

Abstract

The paper aims to demonstrate the applicability of the new and powerful performance and reliability modelling language MOS(MOdeling, Specification and Evaluation Language) through examples from queueing networks with finite capacity, retrial systems amobile networks. MOSEL is a high level modelling language that allows the modeling and performance evaluation of systems ivery intuitive and simple way. The core of MOSEL consists of constructs to specify the possible states and state transitions of t

underlying Continuous-Time Markov Chain (CTMC) of the system under consideration. This specification is very compact and easyunderstand. With additional constructs the interesting performance or reliability measures and also the graphical presentation of thcan be specified. It is specially easy to do experiments with different sets of parameters of the system. The examples choseddemonstrate the modelling power of MOSEL come from three application areas. First, models of queueuing networks with fincapacity are presented which are very important for the performance modelling of computer and manufacturing systems. The fincapacities of the nodes of the network generates blocking at previous nodes. In the second example a retrial system is medelled. Iretrial system an arriving customer, if he finds the server idle, is served immediately. If the server is busy the customer leaves and trhis luck again after a randomly distributed amount of time independent of any other events. This happens for example in telephosystems, in supermarkets or at airports when aircrafts are waiting for landing permission. The third example presents a model a rsystem from wireless communications. In this example, the call admission control protocol in a Third Generation (3G)wireless mobnetwork is studied. In all examples, results on blocking probabilities, utilization, and response times are shown. The graphirepresentation of these results is done using IGL (Intermediate Graphical Language) which a complementary package to MOSEL.

11.A. I. Zreikat, G. Bolch, J. Sztrik: Performance Modeling ofNon-Homogeneous Unreliable Multi-Server systems using MOSEL, InternationalJournal in Computers andMathematics with Applications, Elsivier, Vol. 46, pp. 293-312, 2003.

Abstract

In this paper, we introduce a non-homogeneous unreliable multi-server system with Markovian arrival, service, breakdown and rep

processes. First we consider the case with only one queue and different servers and the job assigns to one server. Then we extend tmodel to more than one queue in which the jobs are assigned to different queues. We assume that our system has different servers wdifferent service times and a job is assigned to a server using the following strategies: FFS (Fastest Free Server) or random selectiFFS strategy means that the job is served by the fastest available server, and if this server is busy then the job goes to the next availaserver and so on. In the random strategy, the job served by one of the free servers which is chosen randomly. In our problem, wconsider a general queuing system (M/M/n) with a finite number of jobs K in the whole system. Our system is unreliable; this meathat we need to specify the parameters,mtbfandmttr (mean time between failures and mean time to repair), and we need to considthe possibility that a server might be up or down at some point of time. The performance modeling of this type of system is done usithe programming languageMOSEL (MOdeling Specification and Evaluation Language), which contains several constructs to descrthe system, the results (performance parameters) and the graphical representation.

7/30/2019 Dr.Ayman

7/12

12. A. I. Zreikat, Khalid Al-Begain: Simulation of 3G Networks in RealisticPropagation Environments. ,International Journal on Simulation: Systems, Science and Technology, SpecialIssue by G. K. Theodoropoulos: Modeling and simulation of Computer Systems, Vol. 4, No. 3-4, September,2003.

Abstract

The coverage of a mobile system depends significantly on the geographical nature of the covered area. The signal propagation can dramatically different in downtown area with many high buildings than in a building free area. This is particularly critical in thigeneration (3G) mobile systems based on Code-Division Multiple Access (CDMA) air interfaces where the power management i

core part of the call admission control of the system. Therefore, performance studies of such systems based on free space assumptiomay lead to optimistic results. In this paper, the performance of a 3G UMTS mobile network covering an urban area and surroundisuburban areas is considered. For modelling the propagation, the COST-231 extended Hata model has been used which represents morealistic propagation models for urban-suburban environments. Based on this model, closed expressions have been derived for tcapacity bounds in the existence of interference due to non-ideal orthogonality of codes in the used CDMA system and backgrounoise. These expressions are used to develop a network level sophisticated call admission control (CAC) algorithm to achieve neaequal blocking probability and balanced utilization over the whole network area. Detailed simulation is used to study the performanof the network under different traffic and interference conditions. The results show that the proposed CAC algorithm performs vewell in achieving equal blocking probability by releasing the load on the heavily loaded central area and, thus, achieving betbalanced load on the network under different interference conditions. Additionally, some design and environment parameters studied like the height of the base station and the average height of the mobile.

13.A. I. Zreikat and K. Begain: Soft Handover-based CAC in UMTSSystems.International Conference in Telecommunication, In Proceedings of ICT'2003 Conference, Feb. 23 -Mar. 01, Tahiti, French Polynesia, pp. 1307-1312, 2003.

Abstract

Call Admission Control (CAC) is one of the important means to guarantee Quality of Service (QoS) in the telecommunication systemThis is especially true in the mobile networks due to their limited capacity. In the Second Generation (2G) GSM systems, the cell hstatic coverage and capacity and, therefore, the call is rejected if all channels in the given cell are occupied. In the Third Generati(3G) systems, such as UMTS, cells have dynamic coverage and capacity that depend on the interference levels and the number active connections in the cell. In this paper, a new sophisticated multi-cell CAC algorithm is presented that uses the soft handov

feature of the UMTS systems to provide multiple goals: (i) provide efficient utilization of the available capacity, (ii) protect the QoSexisting connections, and (iii) prevent the loss of coverage resulting from the so-called "Cell Breathing". The algorithm works balancing the load over the network by transferring some connections from the overloaded cells to the neighboring cell with lighload. Therefore, it achieves more balanced utilization over the whole network. The algorithm is evaluated on a network cluster of sevcells via a detailed simulation under different traffic and interference conditions.

7/30/2019 Dr.Ayman

8/12

14.A. I. Zreikat, K. Begain: Efficient Network-level Call Admission Control Algorithmfor 3G Networks, Sixth United Kingdom Simulation Society Conference, Emmanuel College, Cambridge,London, UK, April, 2003.

Abstract

Call Admission Control (CAC) is one of the important means to guarantee Quality of Service (QoS) in the telecommunication systemThis is specially true in the mobile networks due to their limited capacity. In the Second Generation (2G) GSM systems, the cell hstatic coverage and capacity and, therefore, the call is rejected if all channels in the given cell are occupied. In the Third Generati(3G) systems, such as UMTS, cells have dynamic coverage and capacity that depend on the interference levels and the number

active connections in the cell. In this paper, a new sophisticated multi-cell CAC algorithm is presented that uses the soft handovfeature of the UMTS systems to provide multiple goals: (i) provide efficient utilization of the available capacity, (ii) protect the QoSexisting connections, and (iii) prevent the loss of coverage resulting from the so-called ``Cell Breathing''. The algorithm works balancing the load over the network by transferring some connections from the overloaded cells to the neighboring cell with lighload. Therefore, it achieves more balanced utilization over the whole network. The algorithm is evaluated on a network cluster of sevcells via a detailed simulation under different traffic and interference conditions. The obtained multi-cell UMTS cell results have becompared with the previous results of a single UMTS cell. The comparative results show that the performance of the cell is cleaimproved as the blocking probability and the utilization are improved dramatically.

15.A. I. Zreikat, K. Begain: A multi-cell Call Admission ControlAlgorithm for 3G Networks. PREP2003 (Book of Abstracts), University of Exeter, UK, 14-16 April, 2003.

Abstract

Call Admission Control (CAC) is one of the important means to guarantee Quality of Service (QoS) in the telecommunication systemThis is especially true in the mobile networks due to their limited capacity. In the Second Generation (2G) GSM systems, the cell hstatic coverage and capacity and, therefore, the call is rejected if all channels in the given cell are occupied. In the Third Generati(3G) systems, such as UMTS, cells have dynamic coverage and capacity that depend on the interference levels and the number active connections in the cell. In this paper, a new sophisticated multi-cell CAC algorithm is presented that uses the soft handovfeature of the UMTS systems to provide multiple goals: (i) provide efficient utilization of the available capacity, (ii) protect the QoSexisting connections, and (iii) prevent the loss of coverage resulting from the so-called ``Cell Breathing''. The algorithm works balancing the load over the network by transferring some connections from the overloaded cells to the neighboring cell with lighload. Therefore, it achieves more balanced utilization over the whole network. The algorithm is evaluated on a network cluster of sevcells via a detailed simulation under different traffic and interference conditions.

7/30/2019 Dr.Ayman

9/12

16. K. Begain andA. I. Zreikat: Interference Based CAC for up-link traffic in UMTS Networks.In Proceedinof World Wireless Congress, San Francisco, USA, pp. 298-303, June, 2002.Abstract

Performance analysis of multi service UMTS networks is of major interest for mobile network providers. Because of the W-CDMtechnique used in UMTS, which leads to an interference limited system with a dynamic cell capacity and load dependent cell coverathe service mix has a big influence on the system performance. The paper provides a detailed description of the performance relevmechanisms for the uplink of a single UMTS cell and extracts capacity bounds due to interference and power limitations for singservice operation. Based on these expressions, a sophisticated Call admission Control algorithm is proposed. Finally, an analyti

model is proposed for the system based on multi-class multiple queues system. In our paper, the model is validated against simulatiand used to derive an important performance measures like : blocking probability and system utilization.

17.A. I. Zreikat, K. Begain: Power and Interference Based CAC for up-link

Traffic in UMTS Networks. East Midlands Conference Center,Prep2002 (Book of Abstracts, University ofNottingham, UK, pp. 1-2, 17-19 April, 2002.

Abstract

Performance analysis of multi service UMTS networks is of major interest for mobile network providers. Because of the W-CDMtechnique used in UMTS, which leads to an interference limited system with a dynamic cell capacity and load dependent cell coverathe service mix has a big influence on the system performance. The aim of this paper is to provide a detailed description of tperformance relevant mechanisms for the uplink of a single UMTS cell and to extract capacity bounds for single and multi servoperation. We propose a simplified calculation model for the multi service case, based on the number of users of different radio liservices. CAC (Call Admission Control) algorithm was defined along with the extraction of the most important performance measurlike : blocking probability, average data rate, and utilization. The results and the visualized graphical representations were producusing the modeling language MOSEL (Modelling Specification and Evaluation Language).

18.A. I. Zreikat, K. Begain: Capacity Analysis and Call AdmissionControl Algorithms for UMTS Systems.Proceedings of the 3nd Annual Postgraduate Symposium on theConvergence of Telecommunications, Networking and Broadcasting, Liverpool, John Moores University, UK,17th-19th, pp. 74-79, June, 2002.

Abstract

CDMA is the main technology which provides an integrated services for the third generation of mobile networks. In UMTS (UniverMobile Telecommunication Systems), the transmission power is the main share resource among the users. However, the number users entering the cell is limited by the total interference received at each base station and will vary with time. When the systemcongested, admitting a new call can only make the link quality worse for ongoing calls. Therefore, the system needs a call admissipolicy for new call requests in order to maintain an acceptable QoS connection for existing users. In this paper, the capacity bounds dto interference and power limitations for single service operation have been extracted. Based on these capacity bounds expressionsCall Admission Control (CAC) algorithm is studied and developed.

7/30/2019 Dr.Ayman

10/12

19.A. I. Zreikat , K. Begain: Power and Interference Based CAC for Up-link Traffic in UMTS Networks.Proceedings of the Third Informatics Workshop for Research Students, University of Bradford, Bradford, UKpp. 15-20, Friday, 25 January, 2002.

Abstract

Performance analysis of multi service UMTS networks is of major interest for mobile network providers. Because of the W-CDMtechnique used in UMTS, which leads to an interference limited system with a dynamic cell capacity and load dependent cell coverathe service mix has a big influence on the system performance. The paper provides a detailed description of the performance relevmechanisms for the uplink of a single UMTS cell and extracts capacity bounds due to interference and power limitations for single amulti service operation. Based on these, a sophisticated Call admission Control algorithm is proposed. Finally, an analytical modebuilt for the system based on multi-class multiple queues system.

20.A. I. Zreikat , K. Begain: A new Call Admission Control Algorithm in UMTS Systems. Proceedings of the4th Informatics Workshop for Research Students, University of Bradford, Bradford, UK, Wednesday, pp. 17-220 November, 2002.

Abstract

Call Admission Control (CAC) is one of the important means to guarantee Quality of Service (QoS) in the telecommunication systemThis is especially true in the mobile networks due to their limited capacity. In the Second Generation (2G) GSM systems, the cell hstatic coverage and capacity and, therefore, the call is rejected if all channels in the given cell are occupied. In the Third Generati(3G) systems, such as UMTS, cells have dynamic coverage and capacity that depend on the interference levels and the number active connections in the cell. In this paper, a new sophisticated multi-cell CAC algorithm is presented that uses the soft handovfeature of the UMTS systems to provide multiple goals: (i) provide efficient utilization of the available capacity, (ii) protect the QoSexisting connections, and (iii) prevent the loss of coverage resulting from the so-called Cell Breathing. The algorithm works balancing the load over the network by transferring some connections from the overloaded cells to the neighboring cell with lighload. Therefore, it achieves more balanced utilization over the whole network. The algorithm is evaluated on a network cluster of sevcells via a detailed simulation under different traffic and interference conditions.

21.A. I. Zreikat , K. Begain: Resource Management in Mobile Networks.proceedings of the SecondInformatics Workshop for Research Students, University of Bradford, Bradford, UK, Wednesday, 30 May,2001.

Abstract

The idea of this paper is to study the resource management allocation techniques in GSM and the 3rd generation mobile networkThe main objective is to improve the spectral efficiency in GSM and 3rd generation (UMTS). Re-use partitioning is seen to be oof the best solutions to improve the spectral efficiency. Some of the results about the work that we have been already done in GSto improve the utilization of spectral efficiency will be introduced in this paper. Also we outline the literature survey for sosuggested algorithms in GSM, GSM 2+ (GPRS), UMTS. The transition from GSM to GPRS. Then the limitations and the futuwork of UMTS will be briefly discussed.

7/30/2019 Dr.Ayman

11/12

22. K. Begain, A. I.Zreikat, Y. Li: Optimizing Capacity in GSM. Proceedings of 12thEuropean Simulation Multi-conference (ESM2001) , Prague, czech Republic, pp. 846-850, June, 2001.

Abstract

The capacity of GSM networks is running into its physical limits and the 3G networks are not expected to be widely operationalthe very near future. Therefore, methods of increasing spectrum efficiency with low cost implication can be very welcomed network operators. The re-use partitioning is one of the well-known such methods. In this paper, we provide a numeri

methodology for the design of re-use partitioning to achieve maximum efficiency gain. The numerical results give exact value on coverage of each layer in order to achieve this maximum gain.

23.A. I. Zreikat, K. Begain: Resource Management in Mobile Networks. Proceedings of the2nd AnnualPostgraduate Symposium on the Convergence of Telecommunications, Networking and Broadcasting,Liverpool, John Moores University, UK, 17th-19th , pp. 201-205, June, 2001.

Abstract

The idea of this paper is to study the resource management allocation techniques in GSM and the 3rd generation mobile networks. Tmain objective is to improve the spectral efficiency in GSM and 3rd generation (UMTS). Re-use partitioning is seen to be one of best solutions to improve the spectral efficiency. Some of the results about the work that we have been already done in GSMimprove the utilization of spectral efficiency will be introduced in this paper. Also we outline the literature survey for some suggestalgorithms in GSM, GSM 2+ (GPRS), UMTS. The transition from GSM to GPRS. Then the limitations and the future work of UMTwill be briefly discussed.

24.A. I. Zreikat: Performance Evaluation of Non-Homogeneous Multi-Serversystems using MOSEL, Master Thesis, Operating System Department, University of Erlangen, Nurmberg,Germany, July, 2000.

Abstract

..\My Documents\Master_Thesis\Thesis\Master_Thesis_ABSTRACT.doc

http://../My%20Documents/Master_Thesis/Thesis/Master_Thesis_ABSTRACT.dochttp://../My%20Documents/Master_Thesis/Thesis/Master_Thesis_ABSTRACT.doc

7/30/2019 Dr.Ayman

12/12

25.A. I. Zreikat, G. Bolch: Performance Modeling ofNon- Homogeneous Multi-server systems using MOSEL,ESS2000 Conference, Hamburg, Germany, pp. 570-574, September, 28-30, 2000.

Abstract

We introduce in this papera Non-homogeneous multi-server system with Markovian arrival and service processes. First we considthe case with only one queue and different servers and the job assigns to one server. Then we extend this model to more than one quein which the jobs are assigned to different queues. We assume that our system has different servers with different service times NoHomogeneous Multi-Server System and a job is assigned to a server using the strategies: FFS (fastest free server) or random selectioIn our problem, we consider a general queuing system (M/M/n) with K is a finite number of jobs in the whole system. In which have different queues with different jobs and the jobs are served by different number of servers. The performance modeling of this tyof system is done by using the programming language MOSEL (MOdeling Specification and Evaluation Language), which contaseveralconstructs to describe the system, the results (performance parameters) and the graphicalrepresentation.

26. Aymen. I. Zreikat: Performance and Resource Management of Concentric Cells by means of Nomiload space in GSM Systems, submitted toWireless Personal Communications, Springer (USA), Nov., 2009.

Abstract

We present in this paper a concentric cell approach which is suggested by Motorola to improve GSM capacity by 20-40 % in additi

to the 80 % provided by the Synthesizer Frequency Hopping (SFH) approach. This work is an extension of the well-known UnderlOverlay scheme to any number of layers/zones. The blocking/loss probability of the network is derived and calculated such that tblocking/loss probability meets at least the operators' demands at all locations in the cellular network (< 2%). Hence, the netwpartitioning is optimized in terms of the nominal load for a standard channel assignment scheme and a new channel assignment schewith reservation policy is presented. To improve the efficiency of the model, the mobility is introduced in different places of tdowntown. The numerical results are given to show that the blocking/loss probability of the outer zones is more critical than the innzone, however, the blocking/loss probability of the inner zone is always below the limit while the resources of the network are not usvery effectively. This problem is solved in this paper by suggesting the reservation policy where all resources of the network are usvery effectively while maintaining the blocking/loss probability within the limit to all zones. On the other hand, when the mobilityintroduced, the system behavior becomes more realistic. When the load becomes high, we approximately reach a balanced load ovthe cell zones as well as the whole network. Different parameters that affect the performance are presented and discussed in this papsuch as; the reservation policy, the ratio of moving mobiles, the coverage and the speed of the mobile in different downtown areas. Tcurves for the loss probability and the utilization are shown to demonstrate this effect. Some of these curves are validated against r

data taken from Ericsson AB, Jordan Branch.