Browsing by Author "Yihenew, Wondie (PhD)"
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Item Analysis and Design of an Optimized Automatic Fare Collection System for Addis Ababa Light Rail Transit(Addis Ababa University, 2019-08) Mola, Ayenew; Yihenew, Wondie (PhD)Recently, everything in the world becomes smart and digitalized. Many advances have been made in the transportation sector too. However, railway transport in Ethiopia has been an area where such new advances have turned their faces out. Therefore, this paper, will introduce an Automatic Fare Collection system (AFC) to up bring the railway transportation system in Ethiopia to the best standard. In addition, this paper will focus on different ways of implementing AFC, which will be suitable for AA-LRT. AFC is one of the important technologies in railway transportation around the world. Different countries use different ways of implementation of AFC to their railway transportation. One of the aims of this paper is to study different implementation mechanisms of countries and analyses the best and suitable standard for AA-LRT. The cost analysis should also be considered when such kinds of technologies are implemented. Nowadays, in AA-LRT every train is controlled by a conductor. The conductor will collect money from each passenger and issues tickets and the printed paper or tokens are used as tickets. This process needs man power and the passengers whom are utilizing the transportation services will not be satisfied. Because, they will wait a lot of time on the queuing to get ticket from the cashier. In the proposed system, every AA-LRT stations have one or more RFID (Radio-Frequency Identification) Reader. RFID is a technology whereby digital data encoded in RFID tags or smart labels are captured by a reader through radio waves. The Reader senses the RF signals coming from the passenger identification card and thus recognizes the entry, existence and exit of the passenger. Based on the signals from the card is cut off, the fare of the journey is calculated and is deducted from the passenger’s account, which is linked with the backend system. The RFID card will recharge in different ways, it may recharge from stations, mobile account and/or bank account. The system will deliver an end-to-end solution for fare collection, ticketing, and payments that provides secure and faster transactions, more convenience and smooth passenger flow during peak hours, and efficient collection of fare ensuring no fraud takes place.Item Analysis of Energy Efficient Techniques for 5G Ultra Dense Wireless Communication Networks Using Massive MIMO(Addis Ababa University, 2021-10) Halefom, Tswaslassie; Yihenew, Wondie (PhD)In the modern wireless communication energy consumption becomes critical issue for wireless network operators. With the emergence of 5G wireless communication , the importance of energy efficiency (EE) has been appreciated since it is one of the significant performance analysis metrics of wireless networks. Energy can be saved in the design of wirless network if a proper analysis and design optimization is done. Massive MIMO and cell densfications are the latest encouraging technologies to maximize energy efficiency of 5G wireless communications. This thesis work mainly aims on the analysis of energy efficiency techniques of 5G wireless communication using Massive MIMO technology.The techniques to be analysis are in the precoding , in channel state information and massive MIMOtechnology. The analysis begins from circuit power consumption model using zero forcing precoding schemes with TDD communication protocol. The main design parameters are the number of massive antennas at the base station (M), the number of active user equipment terminals (K) , the system throughput (R) and cell density . Then EE is defined as the number of bits transferred per Joule of energy consumed. MATLAB tool is used to prove the impact of the main design parameters on energy efficiency. The impact of massive number of antenna , user equipments and system throughput on energy efficiency with perfect channel state information and imperfect channel state information is analyze . The simulation result shows that we can design optimal values of (M, K and R) that maximize energy efficiency of the system with perfect channel state information than imperfect channel state at the base station. The final results sows that zerforcing precoding and perfect channel state information at the base station saves more energy as compared to iperfect channel state information.Item Capacity Enhanced-Energy Efficient Base Station Deployment Using Genetic Algorithm(Addis Ababa University, 2020-02) Tabor, Birru; Yihenew, Wondie (PhD)Unparalleled increasing demands for high capacity and consistent service quality on cellular network have been challenging for telecom operators. However, current deployed and existing radio access network is significantly behind the growth. This promotes operators to network upgrade, expansion and base station (BS) densification. Operators are also trying to mix macro and small cell on their radio access network as a potential solution to meet their customer demands by enhancing their network capacity and coverage extension. However, addition of the small cell on existing network increases energy consumption. This thesis study considers energy efficient BS deployment for enhancement of LTE network capacity. For this purpose, small cell deployment underlay to the existing macro BS is used in outdoor scenario in 2x2 square kilometer area located in Addis Ababa. Candidate locations for the small cell first selected mainly based on traffic distributions in the selected area of study. Then radio propagation simulations performed using WinProp radio planning and simulation tool followed by Genetic algorithm based optimization to find out the optimal number and locations of the small cell obtaining enhanced capacity and improved energy efficiency with minimized additional power consumption. The result analysis is observed in MatLab implementation. Finally, aggregate capacity and energy efficiency have been evaluated. The result shows that both the aggregate network capacity and energy efficiency increased with number of small cell. There is 77.94% capacity and 24.7% energy efficiency improvement as compared to the original macro BS only network, which respectively requires 82 and 59 small cells transmitting at 0.5-watt power. At the same time, improvement of capacity requires 18 small cell while it takes 23 and above small cell for energy efficiency to be improved. For small cell more than 59, the energy efficiency start declining which indicates small cell deployment beyond this value has no importance as it declines energy efficiency. The aggregate network capacity has improved by 66.99% when selection of the small cell limited on its impact on energy efficiency. The maximum energy efficiency achieved is 24.7%, 22.32%, 17.88% and 11.12% respectively for small cell transmitting at 0.5watt, 2watt, 5watt and 10watt. This result can possibly be improved further by using different techniques such as sleep mode and cell zooming operations.Item Comparative Analysis of Resource Scheduling Algorithms for LTE(Addis Ababa University, 2021-11) Semir, Kedir; Yihenew, Wondie (PhD)As wireless communication services demand grows, new challenges in the design and operation of cellular networks arise. Despite the fact that LTE cellular wireless network is one of the most well-accepted and fastest-growing technologies in communications, network resources are limited, and they need to be allocated efficiently. As a key design factor in enhancing the performance of LTE systems, managing radio resources is crucial. With the expansion of LTE networks by ethio telecom and their growing usage among all mobile users in the country, the necessity to efficiently manage the available radio resources becomes more and more essential, in order to maintain Quality of Service (QoS) levels. Since the Third Generation Partnership Project (3GPP) does not specify a resource scheduler mechanism, researchers have come up with several approaches either to attain fairness among users or to achieve maximum throughput. This enables wide options in resource allocation, thereby allowing several different scheduling algorithms to flourish, with different aims. Comparing the performance of such algorithms in different scenarios is therefore great interest of this thesis. Henceforth, performance analysis of five existing LTE downlink scheduling schemes; namely Maximum Largest Weighted Delay First (MLWDF), Exponential_Rule (EXP-Rule), Exponential/Proportional Fair (EXP/PF), Logarithmic_Rule (LOG-Rule), and Frame Level Scheduler (FLS) are done in a macro cell with interference environment for both non-real-time and real-time traffic flows. While varying the number of users and user speed, it examines the performance of each scheduling algorithm with respect to throughput, packet loss ratio (PLR), fairness, and energy efficiency. Results show that among the five algorithms considered here, for real-time flow the FLS scheme outperforms the other four schemes in terms of throughput, PLR, and fairness metrics, whereas the rest algorithms perform well for best-effort (BE) flow.Item Comparative Performance Analysis of Free Space Optics as a Backup Link for Fiber Connectivity around the Areas of Bole Medhanialem Using Optisystem 15(Addis Ababa University, 2021-05) Melat, Ambaye; Yihenew, Wondie (PhD)Free space optics (FSO) is a field of curiosity and importance for the scientists because of its numerous applications and advantages like low cost, easy deployment, high data rate, secure links and license free bands. FSO technology utilizes the light propagating in the free space to transmit the data wirelessly for both telecommunications and computer networking domains. In optical communication, we use optical fiber cable as a medium but in the free space optical communication, we use the free space as the medium to propagate the light signal [1]. Even if fiber optics is the most reliable means of providing optical communications, the digging delays and associated costs to lay fiber often makes it economically prohibitive. A telecom service provider in our case Ethiotelecom faced a problem to deliver a quality service because of many technical issues one of them is lack of deploying a redundant link. As we all know unable to deliver a promised service leads to customer dissatisfaction. This thesis paper proposes a design of point to point FSO as a backup link for fiber connectivity around the area of Bole Medhanialem pointing from Bole exchange to three different enterprise buildings (Sapphire Addis Hotel, Best western Addis Hotel, Skylight Hotel) that is capable of transmitting data at 80Mb/s, 60Mb/s and 200Mb/s for a distances of 0.116km, 0.36km and 1.45km respectively. And it’s performance analysis and comparison with fiber optics observed using Optisystem software15 by taking the performance metrics Q factor and BER found from the reading of BER analyzer. From the results it has been understood that FSO link can perform like FO (main link) at a cost of input power. Since FSO link in Ethiotelecom infrastructure has not been studied before we can take this paper as a reference for future deployment of FSO technology in the country.Item Congestion Control with Load Based Inter RAT Handover (3G to 2G): Case of Addis Ababa(Addis Ababa University, 2020-02) Alemu, Yadessa; Yihenew, Wondie (PhD)Telecom operators have to manage their resources efficiently to minimize the congestion in their telecommunication network. In Ethiopia, heterogeneous wireless networking technologies such as GSM, UMTS, CDMA and LTE are being used to provide wireless access for both voice and data services. In big cities, the densely populated areas like town centres, shopping centres and train stations may have coverage of multiple wireless networks. Traditional Radio Access Technology (RAT) selection algorithms are mainly based on the ‘Always Best Connected’ paradigm whereby the mobile nodes are always directed towards the available network which has the strongest signal. Hence a large number of mobile users may be connected to the more common UMTS while the other networks like GSM and CDMA would be underutilised, thereby creating an unbalanced load across these different wireless networks. This high variation among the load across different co-located networks may cause congestion on overloaded network leading to high call blocking and call dropping probabilities. This can be alleviated by moving mobile users from heavily loaded networks to least loaded networks. This thesis presents a load levelling algorithms which is used for load balancing in heterogeneous wireless networks. The technique comprises of load-aware RAT selection techniques and network load balancing mechanism. Different attributes like load distribution in all wireless networks, packet drops, throughput at mobile nodes and network utilization have been observed to evaluate the effects of load balancing using different scenarios. The simulation results indicate that with load balancing the performance efficiency improves as the overloaded situation is avoided by load balancing. The load change value is 11% for the sites in the focus area. This shows that the voice call has been pushed to the neighbour 2G cell and congestion in 3G network has been improved.Item Coverage Prediction Based on Spatial Interpolation Techniques: The Case of UMTS Network in Addis Ababa, Ethiopia(Addis Ababa University, 2020-01) Zeneb, Kassaw; Yihenew, Wondie (PhD)Cellular network coverage prediction is a cornerstone of mobile network operators and service providers in order to provide good services to users. Without coverage provisioning, it is meaningless to talk about service or Quality of service (QoS) provisioning. Coverage planning is a complex task for operators during deploying Radio Access Technology (RAT). This is because it needs to consider multiple and correlated network parameters as well as environmental conditions that are out of their control. It is impossible to completely avoid the existence of coverage holes in cellular networks during the planning phase. Therefore, coverage prediction processes are usually required during the operational phase. Traditionally, the cellular coverage estimation performed through drive tests, which consist of geographically measuring different network coverage metrics with a motor vehicle equipped with mobile radio measurement facilities. The collected coverage measurements through drive test are accurate but limited to roads and other regions accessible by motor vehicles. Drive tests cannot be conducted in the whole region of the network due to many obstacles such as buildings, lakes, and vegetation. Therefore, the drive test is quite inefficient means to solve the coverage problems and cannot offer a complete and reliable picture of the network situation. In this thesis, the performance of two spatial interpolation methods namely, Inverse Distance Weight (IDW) and Ordinary Kriging (OK) were evaluated to select which method is best for Universal Mobile Telecommunication System (UMTS) network coverage prediction using the Common Pilot Channel Received Signal Code Power (CPICH RSCP) collected from drive test. The experimental analysis was performed on a sample data collected from drive test UMTS network in Addis Ababa Ethiopia. Two general interpolation methods were employed with different parameters. The first method is IDW with various powers and number of neighbors and the second method is OK with Gaussian, Spherical and Exponential semivariogram models with different numbers of neighbors. The performance of estimation those algorithms were evaluated through the cross-validation, coefficient of determination (R ), Mean absolute error (MAE) and Root Mean Square Error (RMSE). The test results showed the two coverage prediction methods are able to predict coverage. However, based on the Exponential model of semivariogram with an optimal number of neighbors the OK method estimated with an error of prediction 4.84 RMSE whereas the IDW estimated 5.33 RMSE with a percentage difference of 17%. This shows that OK is more accurate than IDW. The OK method can infer the missing RSCP data and generates a more accurate coverage map than the IDW algorithm. This could probably be OK was able to take into account the spatial structure of data. Therefore, this thesis proposes the OK method as the optimal interpolation model to build a radio coverage map for cellular coverage prediction and hole detection purposes.Item Data-Driven QoE Model for Addis Ababa LTE Video Streaming Using Fuzzy Logic Inference System(Addis Ababa University, 2020-02-21) Aysheshim, Demilie; Yihenew, Wondie (PhD)Nowadays, the video streaming services become the most dominant service as people are more interesting watching online television programs and Video on Demand (VoD). This requires a high speed and high capacity network infrastructure. The Long Term Evolution (LTE) network infrastructure of Addis Ababa has faced this network capacity and data rate demand in order to have a good Quality of Experience (QoE). To takeover this challenge, Ethio Telecom should have appropriate assessment methodology for QoE. This thesis outlines the means of QoE modelling issue to measure QoE objectively. It proposes a QoE model which is used to measure the QoE from Quality of Service (QoS) parameters using Fuzzy Logic Inference System (FIS). This has been done by collecting end-to-end QoS data from network management system which is used as input for the model and the proposed model has been validated using a dataset collected from customer survey. The Model developed is essential for replacing the subjective measurement techniques which are costly and inefficient being influential to user context, terminal characteristics, application software, user capability, etc. In addition, the model developed is helpful for business decision making, network planning, optimization and operational support activities in manual systems or system based for self-organizing networks according to the infrastructures implemented. The result of correlation, regression, and Four-way ANOVA show that the Stall Frequency (SF) and the Start Delay (SD) plays the major impact on the LTE video streaming QoE by 33% and 25% respectively. The validation result shows the proposed model is an accurate, consistent and linear compared to the existing models.Item Development of Large Scale Path Loss Model for 3 rd Generation Networks: The Case of Eastern Addis Ababa(Addis Ababa University, 2020-06) Ephrem, Berhane; Yihenew, Wondie (PhD)The design of efficient cellular system requires a detail understanding of propagation characteristics of mobile channel. A signal propagation through a channel undergo two kind of variations; large scale and small scale path loss. This thesis focuses on large scale propagation model for Eastern Addis Ababa of Ethio telecom. The results are evaluated based on different parameters such as coverage radius, antenna height, and Eb/No. And network planning, operation, maintenance and upgrade depend on radio channel environment and property. Radio propagation parameters that affect the receive signal level on radio links are analyze the best path loss model for prediction of the receive signal level is determine. This thesis work on the most commonly used path loss models among others, for 3G based cellular systems in Eastern Addis Ababa. It collected two types of data, static and dynamic data. From the static data it get eNodeB and mobile station height in meter and operating frequency in mega Hertz that is 2100 Mhz. And using this data it modeled Hata and COST 231 empirical model. And from drive test it collected dynamics data, distance from transmitter to receiver and receive signal strength in dBm. And from this data it get path loss exponent, reference path loss, standard deviation and MSE for the four eNodeB and its average that are located in Eastern Addis Ababa. Several electronic equipment are used for the measurement for RSS such as Samsung S5 mobile that are installed Nemo software , Global positioning System((BU353 GPS) and Laptop that are installed Actix software and data export to Excel program. The selected sites are Bole Homes, Bole Intentional Stadium, Summit Beverage and Summit Savory. The path loss exponent for the above four Eastern Addis Ababa place are 2.87, 5.38, 4.55 and 2.58 respectively .And standard deviation was evaluated as 6.24dB, 4.78dB, 6.11dB and 7.58dB respectively. And path loss model was developed as ‘PL =114.5 + 45.5 log (d/do)’ for Summit Beverage. For Bole International Stadium the path loss model are ‘PL=95.9+53.8log (d/do)’. For Bole Homes modeling and Summit Savory ‘PL=116.5+28.7 log (d/do)’ and ‘PL=109.17+25.8 log (d/do)’respectively. And MATLAB R2015a was used for simulation.Item Fine-tuning of Cost-231 Hata Path Loss Model for LTE Network: The Case of 4 Kilo Area(AAU, 2018-06) Noah, Fesseha; Yihenew, Wondie (PhD)The demand for increased mobile phone subscribers requires an efficient radio network planning that involves an accurate prediction of path loss. For Long Term Evolution (LTE) mobile network, empirical path loss models such as Cost-231 Hata model are used to predict the loss in a propagation environment. These models depend on frequency of operation, terrain profile of an environment, transmitter and receiver heights and distance from a base station. As the propagation environments continuously changes, these models need to be fine-tune continuously. In this thesis, LTE 1800 MHz mobile signals that are recorded experimentally, for four eNodeB in Addis Ababa 4Kilo area, are considered for path loss analysis. A drive test methodology was adopted for data collection and the measuring tools used for the test was a hand phone installed with Nemo Handy software. The received signal strength and path loss were recorded in the form of logs which can later be extracted with ACTIX software analyzer in to a suitable form of Excel sheet. The measured path loss is determined from the collected data. Cost-231 Hata model was optimized because it is the existing model in Ethio telecom. In order to improve the prediction accuracy, this model is statistically optimized using Least Square algorithm. The initial offset parameter and slope of the model curve in Cost-231 Hata model are considered and new model parameters are estimated. The optimized path loss predicting model is compared with the original Cost-231 Hata model and MATLAB R2016a Simulation software was used for this purpose. The performance of the optimized model is evaluated using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The optimized model gives a RMSE = 0.039 dB and MAPE = 0.037% as compared to Cost-231 Hata model with a RMSE = 0.49 dB and MAPE = 0.47%. The results show that the errors are least for the optimized Cost-231 Hata model, compared to the original Cost-231 Hata model. Hence, the optimized model is recommended for better deployment and gives an accurate path loss prediction in the urban area of 4Kilo.Item Inter-Cell Interference Mitigation in LTE-Advanced Network by Using Coordinated Multipoint Transmission Technique: The Case of Addis Ababa, Ethiopia(Addis Ababa University, 2021-10) Getaneh, Molla; Yihenew, Wondie (PhD)The number of mobile broadband subscribers is increasing along with mobile data traffic on the Ethiopian mobile network. Mobile customers are facing dissatisfied service quality as the number of subscribers is increasing due to resource sharing as well as increasing interference. To improve service quality, network optimization and expansion work has been continuously performed. In order to maximize network capacity and coverage, ethio telecom upgrading the cellular network by using Long Term Evolution Advanced (LTE-A), an indoor building solution system, and adding base stations/transmitters. In such networks, Inter-Cell Interference (ICI) becomes more challenging, which mainly affects network performance. So, to overcome the aforementioned problem, operators are required to develop an effective approach that adopts different interference mitigation techniques. This thesis study presents a Coordinated MultiPoint (CoMP) transmission technique that can be considered as an effective way to improve spectral efficiency and system throughput performance. The thesis focused on downlink ICI mitigation in the LTE-A network within Addis Ababa. Comparative analyses and evaluations were performed for various CoMP and non- CoMP schemes. Taking into account performance metrics such as Signal to Interference plus Noise Ratio (SINR), spectral efficiency, and system throughput by performing radio propagation using WinProp and system-level simulation using the static simulator Matlab. The performance evaluation of the simulation study results obtained that the SINR gain improves 1.2dB and 1.4dB for the intra-site CoMP system, the Dynamic Point Blanking (DPB) CoMP system improves up to 3dB and 1.9dB, and the Joint Transmission (JT) CoMP system improves 3.7dB and 2.8dB for the cell edge and average users respectively. Spectral efficiency gain improved by 1.4bps/Hz, 2.4bps/Hz, and 3.2bps/Hz for intra-site CoMP, DPB CoMP, and JT CoMP scenarios, respectively. In addition, the throughput gain was achieved at 33% and 15% for intra-site CoMP, 70%, and 45% for DPB CoMP, and 97% and 70% for JT CoMP for the cell edge and average users, respectively. Therefore, the proposed interference mitigation solutions have been proven to provide a significant performance improvement for the LTE-A network and are worthy of deployment on the existing Addis Ababa LTE-A networks.Item LTE Radio Access Network Dimensioning by Particle Swarm Optimization(Addis Ababa University, 2020-02) Woretaw, Chanie; Yihenew, Wondie (PhD)In this research, Long Term Evolution Radio Access Network Dimensioning by Particle Swarm Optimization (PSO) in the case of Addis Ababa, Ethiopia has been introduced. Currently, mobile network service provision demand is increasing, especially customers’ data demand increases time to time. To accommodate this demand, LTE is in hand solution. Preparing nominal plan after dimensioning is tiresome and error prone. The motive of this research is to use PSO for addition of new sites to the existing e-NodeBs in order to simplify LTE planning by considering traffic distribution. Using PSO has good result in order to find optimal position of new site. There are many researches done on LTE radio network dimensioning. However, they did not consider actual customer distribution or traffic density, which will cause inefficient use of the network resource. With this research, PSO has been checked for LTE dimensioning in the case of Addis Ababa for LTE RAN planning and congestion optimization that it will assist to put new sites on high traffic density area. LTE coverage dimensioning have been done by two ways: by empirical way using Cost231 propagation model and by outdoor planning tool, Mentum planet. LTE capacity dimensioning was also done by two scenarios: from traffic history prediction and expectation of the coming big data demand of Internet of Things, Machine to Machine and e-commerce. Live network traffic history and Time Advance measurement of Global Solution for Mobile communication have been taken and average traffic probability distribution function (PDF) and optimal traffic probability density function(pdf) have been developed. From which, inter-site traffic share models have been formulated. Finally, model for PSO has been developed. For each new site; searching radius, minimum inter-site distance and required point by searching optimal points within searching area as well as total number of sites were determined. This research shows that number of sites found based on numerical calculation for capacity is not enough to support expected traffic due to uneven traffic distribution. It confirmed that using single type of LTE site is both inefficient and insufficient.Item Machine Learning Based QoE Estimation Model for Video Streaming over UMTS Network(Addis Ababa University, 2020-02) Digis, Weldu; Yihenew, Wondie (PhD)The advent of data-intensive services needs quality Internet services. This in turn, makes Quality of Experience (QoE) gain prominent recognition in the telecommunications industry. Ethio telecom uses network Quality of Service (QoS) monitoring data obtained from Network Management Systems (NMS) tools to comprehend its network performances. However, as QoS measurement refers to network performances, this method does not generally give QoE data as perceived by the user. Therefore, QoE estimation models are proposed as solutions in the literature, recently. This study focuses on developing QoE estimation models using QoS features of round-trip time (RTT), jitter, loss rate (LR) and throughput, and QoE scores collected using Application for prediCting QUality of experience at Interne Access (ACQUA)-based crowdsourcing in Universal Mobile Telecommunication Systems (UMTS) networks in a real-time basis. Data preparations techniques such as data cleaning and dataset imbalance corrections have been applied to the collected datasets. Machine Learning (ML) algorithms of Arti cial Neural Network (ANN), KNearest Neighbor (KNN) and Random Forest (RF) are selected based on their suitability for multilabel problems. After training these models developed, they are evaluated using commonly used performance metrics such as accuracy, Root Mean Square Error (RMSE) and Receiver Operating Characteristics (ROC). Experimentation results exhibit that RF with an accuracy of 98.39%, is the best model while KNN and ANN achieve 87.47% and 77.59% overall accuracy, respectively. As a conclusion, all three models achieve acceptable performances. As a conclusion, our QoE estimation models if implemented can help Telecommunications Service Providers (TSP) in estimating user QoE in real-time.Item Mobile Data Offloading using Wi-Fi for the case of Ethio Telecom in Addis Ketema Area(Addis Ababa University, 2018-06) Wudneh, Alebign; Yihenew, Wondie (PhD)One of the most difficult task for any mobile network operator is to efficiently manage an increasing number of mobile data users especially in a congested urban areas. These high number of data users require higher bandwidth and high speed throughput. To overcome these problems, high capital investments are required which are not economically viable. Mobile network operators are forced to see another alternative to solve the problem by using mobile data offloading technologies. Mobile data offloading is one of the technique to efficiently handle the growing mobile data traffic by offloading cellular data traffic to other complementary networks. This will decrease the burden on mobile network operators and increase the capacity of data network. Collected data from ethio telecom shows that there is high number of mobile data traffic usage in 3G network that creates network congestion. Currently in Ethiopia ethio telecom solves the problem by upgrading cellular network to 4G/LTE, using smaller cell/sector method and upgrade cellular network by adding base stations/transmitters and enhance software resources. Since the number of peoples in the urban areas like Addis Ababa are increasing dynamically, it is difficult task for ethio telecom to manage rapid growth of mobile data usage using the above techniques only. Hence offloading cellular network to other complementary network provides ethio telecom an advantage to enhance the data network capacity easily. This thesis also proposes Wi-Fi offloading technique as one of the alternative way to solve mobile network congestion problems in a congested urban areas in Addis Ababa city Addis Ketema area. The thesis also shows how Wi-Fi offloading will improve the capacity of the whole mobile network using Atoll simulation tools and presents options on the technical integration of Wi-Fi and cellular network. And finally the paper shows the challenges and future works of Wi-Fi offloading in Ethiopia. The simulation result shows that after offloading a percentage of 3G data traffic to Wi-Fi network the required grade of service for both voice and data improved.Item Neural Network based 3G Mobile Sites Fault Prediction: A Case Study in Addis Ababa, Ethiopia(AAU, 2018-11) Asmelash, Tesfay; Yihenew, Wondie (PhD)As cellular mobile networks are evolving in technology and service type, the number of mobile network site infrastructure is increasing. Nowadays, faulty cellular mobile network sites per day in ethio telecom are significant in number and have big impact to customers and operator in QoS, revenue and maintenance cost. Fault maintenance techniques commonly applied by ethio telecom is corrective maintenance approach. This only helps to recover services after interruption. However, it is important to implement the proactive maintenance approach to make mobile sites reliable and available. This helps to provide services according to standards and improve the quality of service delivery to customers. To mitigate mobile network site faults before happening, fault occurrence time prediction is an important technique for the implementation of proactive maintenance strategy. This Neural Network based 3G Mobile Fault Occurrence Prediction research work is conducted based on the Nonlinear Auto regressive (NAR) Neural Network time series prediction method using Addis Ababa 3G mobile sites in a case study. To train the neural network 15,950 actual fault occurrence time data are used. The algorithm used to train the neural network is Levenberg-Marquardt which is fast and efficient, and an iterative approach of hidden layer neuron number selection is applied. Finally, the best model is selected with minimum value of mean square error of prediction. Also, the model is tested with actual fault occurrence time which was not used in the training and achieved 90.71% in prediction. Therefore, it is efficient in prediction accuracy, fast and adaptive with future data.Item On the Performances of User Association Enhancements in Dense Wireless Heterogeneous Networks(Addis Ababa University, 2023-03) Dinkisa, Aga; Yihenew; Hamalainen, Jyri (Prof.); Yihenew, Wondie (PhD)User Association (UA) plays a signi cant role in radio resource management of wireless communication systems. Currently, network densi cation and heterogeneity have already been identi ed as a feasible solution for the exponentially expanding data service demand. Hence, UA methods must meet di erent requirements in dense and ultra dense Heterogeneous Networks (HetNets). The load-imbalance due to transmit power di erence between tiers and interference coordination challenges, the e ect of serving node intensity on load sharing and achievable throughputs and the e ort to satisfy certain users with high data rate demands are a few problems. Furthermore, the interconnected and complicated problems of service delivery are posed by the spatio-temporal dynamics in service demand and the mobility of User Equipment (UE). This thesis takes a step-by-step approach to solving UA problems in dense and ultra dense HetNets. This research uses stochastic geometry tools, system level simulations, and realistic test case deployment simulations. Models were created for each scenario based on the load balancing, interference coordination, varied densi cation levels, heterogeneity, and user mobility. The work's rst contribution is a solution to the problem of load imbalance and interference coordination. The proposed method is simple to integrate into an existing HetNets network, and the results demonstrate e ective load-aware association and adaptive interference coordination. A cell clustering-based load-aware o setting and an adaptive Low Power Subframe (LPS) approach was developed. The solution allows the separation of UA functions at the UE and network server such that users can make a simple cell-selection decision similar to that in the Maximum Received Signal Strength (max-RSS) based UA scheme, where the network server computes the load-aware o setting and required LPS periods based on the load conditions of the system. The proposed solution was evaluated using system level simulations wherein the results correspond to performance changes in di erent service regions. Results show that the method e ectively solves the o oading and interference coordination problems in dense HetNets. The second contribution of the research is on the coupled and decoupled User Association. It can be used as a guide for network operators to select the appropriate UA scheme for their network. The concepts of Poisson random networks were used to analytiv ically obtain the relative densi cation levels for which we need the o oading, decoupled or coupled UA and validate the analysis with numerical and system level simulation of realistic network. The association window, where users choose to use decoupled association in terms of the relative intensity, transmit powers at each tiers and the Path Loss Exponent (PLE) of the propagation environment, is derived. Further, the ergodic rate expressions in order to study throughput performances in di erent densi cation regions, which can be computed numerically, are formulated . To validate the theoretical analysis, numerical, system level simulation and realistic network analysis were used. The analytical, simulation, and realistic test case results provide insights for the operators about the densi cation ranges, where to use coupled or decoupled association. Finally, the research work focused on solutions for UEs with high data rate demands and mobility management. With Multiple Association (MA), user-centric clustering, control, and user-plane split usages were designed and investigated. Mobility management approaches in Long Term Evolution Advanced (LTE-A)/Fifth Generation (5G) and MA were used. The scheme attempts to separately treat UEs based on their speed by setting some prede ned thresholds. In addition, a clustering approach, which produce virtual cells with which UEs gets associated was developed. Combining of MA with clustering enhances cooperation between most appropriate cells to serve a given UE. The ndings indicate that the issues were addressed in an e cient and e ective manner.Item Peak Hour Mobile Core Network Data Traffic Analysis to Improve Network Quality Using Flow Based Method: The Case of Ethio-Telecom(Addis Ababa University, 2021-10) Mahlet, Merid; Yihenew, Wondie (PhD)It is known that the telecom industry is one of the core areas in a country's sustainability and growth. So it is important that great emphasis be given to it on deploying necessary infrastructures in different areas, maintaining the existing available resources and also upgrading the already existing networks as necessary. Once the basic layout is done, it is also equally important that the necessary follow up is done for giving solutions to problems that arise from customers from time to time. One of the biggest reason that lead to customer complaints arise from poor quality of service which results in dissatisfaction of customers' needs. In order to give a solution to this, one of the ways is to do a network traffic analysis. In this thesis, a data traffic analysis is done in the Ethio Telecom core network. Data captured from its network is used as an input in order to firstly identify the peak hour during the day because this is the time where there is the most communication and transmission. The peak hours of each day are recoded and then finally the average is taken for the purpose of this study. In general over the sampled data the peak hour is found to be at 21:06hr. For this work identification of the peak hour is necessary because this thesis focuses the traffic analysis during the peak hour and for the work to be thorough and to be confirmed, first identification of the busiest hour of the day is necessary. After that by filtering out the data at the peak hour, the Key Performance Indicators, Packet Loss Ratio in percentage (%) and throughput (packet/sec) are studied from the capture data in order to be able to see how exactly the system is working. In order to do so, two approaches are used. First the cumulative distribution functions of the data are fitted against the different traffic analysis distribution models. Out of the selected distribution models, it is seen that our data best fits with the Normal Distribution and the Gamma Distributions. For better accuracy the RMSE (Root Mean Square Error) is calculated for each one of them. Second, the KPI's for the peak hour and the slow hour are compared. From the sample gathered data, for both PLR and throughputs, the number of packets being lost are higher during the peak hour compared to that of the slow hour by 37%. But despite this, when comparing the Packet Loss Ratio recorded for both peak hour and slow hour they are both less than 1% which is the acceptable threshold range. Similarly the number of packets being received per second that are sent for the downlink and uplink throughputs, during peak hour the minimum downlink and uplink throughputs exceed that of the slow hour by 15.4% and 11.9% respectively and for the uplink throughput by 16% and 12.5% respectively. So finally from the analysis result, it is seen that the network works fine with a very minor glitch which is expected from a real life operating network.Item Performance Analysis of Energy Efficiency Ensuring Techniques In Massive Mimo For 5G Communication Networks(Addis Ababa University, 2023-09) Haile, Araya; Yihenew, Wondie (PhD)Wireless communication technology is increasing to satisfy the needs of customers. With the emergence of new technologies, energy consumption is one of the most important performance metrics. According to the requirements of the 5th generation wireless communication system, energy consumption should not increase from the level of the current networks (4G), even though the amount of data is expected to be significantly higher. Therefore, energy efficiency has been set as one of the major objectives for recent cellular networks. Massive multiple-input-multiple-output (M-MIMO) is the key technology to providing higher energy efficiency (EE) and data throughput in 5G wireless communication systems. This thesis focuses on the performance analysis of energy efficiency higher than energy consumption for 5G networks using massive multiple-input multiple-output (M-MIMO). Minimizing the power consumption per user’s equipment (UE) with increasing throughput. The main design parameters used are the power consumption per user’s equipment (PC), the data rate of the system (R), and the massive number of antennas (M) and users’ equipment (K). Energy efficiency is defined as the system throughput per unit of power consumption as a function of a massive number of antennas and users. The performance analysis and comparison used are pre-coding schemes such as multi-cell minimum means square error (M-MMSE), zero-forcing (ZF/RZF), and maximum ratio combination (MRC). MATLAB tools are used to analyze and demonstrate numerical results. The analyzed results show that energy efficiency (EE) is higher than energy consumption in a massive MIMO for 5G wireless communication systems. The overall simulated result of multi-cell minimum mean square error (M-MMSE) is the best pre-coding technique to maximize energy efficiency (EE) rather than total energy consumption in massive MIMO for 5G wireless networks. However, MRC achieves the lowest performance and energy efficiency as the massive number of antennas increases in massive MIMO for 5G cellular communication networks.Item Performance Analysis of Spectral Efficiency for 5G Enhanced Mobile Broadband Network with Massive MIMO(Addis Ababa University, 2022-01) Kahsay, Nguse; Yihenew, Wondie (PhD)Due to the increase of the number of users and applications, the improvement of technology is also ongoing. Wireless mobile communications need high data rate and capacity at the same time. Future generation wireless communication will have to deal with some basic requirements for serving large number users with high throughput. The fifth generation (5G) network needs to evolve in order to increase the capacity higher than the fourth generation of networks by 2025. In practice, the inter-user interference in multi-cell network has impact when more users access the wireless network and reduces performance of the system. This thesis explains the basic motivations behind Massive MIMO technology in application to 5G enhanced mobile broadband network, and provides analysis for spectral efficiency in different propagation environments. First, Lower bound SE expressions are derived to enable efficient system-level analysis under LoS and NLoS propagation environments under the assumption that channel state information is acquired by using pilot sequences (reused across the network) with densification of BSs so as to improve the SE for UEs. Simulations are used to show what happens to SE for different path loss models, BS antennas M, and different UEs K under these propagation environments. The numerical analysis shows that the SE as a function of BS density achieves its maximum for a relatively small density of BS, irrespective of the processing scheme used. This is different from distance-independent path loss model, in which the SE is a non-decreasing function of BS density. ZF processing is found to be good compensation in complexity and performance in spectral efficiency, which is then used to optimize, for a given BS density, the pilot reuse factor, number of BS antennas and UEs.Item Performance Enhancement of Floodlight Software Defined Networking Controller using Workload Adaptive Packet Batching(Addis Ababa University, 2019-07) Petros, Belachew; Yihenew, Wondie (PhD)The innovation of high tech devices with increasing demand for big data processing, made the networking systems unresponsive to the need of users. The capacity of network technologies such as wired, wireless, and cellular networks has been increasing highly due to the high traffic of the network system. Such traffic nature of today’s network system is very complex which is very hard to be handled by the conventional networks. These conventional network characteristics could not be adapted to the fluctuating requirements. Due to this, it is very hard to manage the different networking devices; inflexibility to increase in size of the networks, and dependability to the specific vendor's software. Software Defined Networking was made by separating the cumbersome network control from data forwarding devices, apart from traditional networking. SDN was aimed at making a networking paradigm that responds quickly to the changing network requirements. SDN controller uses an OpenFlow protocol, which handles rules for the traffic that arrives at the switch. Floodlight controller uses static packet batching for supervising the traffic by OpenFlow protocol. The static batching is sluggish to the rapidly expanding traffic and it takes a high time for processing. In this thesis, the Workload Adaptive Packet Batching, which learns the batch size based on the nature of the workloads, was proposed to optimize the performance of the Floodlight SDN controller. This study implemented and tested on the network that was created by Mininet network emulator. The network consists of the virtual switches and hosts that are managed by the Floodlight controller. After network setup, the performance evaluation was performed using the Cbench tool, which tests for throughput and latency metrics. The proposed Workload Adaptive Packet Batching achieved an enhanced average throughput of 11% and a latency of 10%. The throughput was improved and the latency was reduced with this proposed mechanism. Therefore, enterprise SDN networks can boost their performance and traffic management by applying the Floodlight controller into their networks.