Communication Engineering

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Now showing 1 - 20 of 114
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    Performance Comparison of Multi-Mode Modulation Techniques for SDR Using FPGA
    (Addis Ababa University, 2023-11) Sisay Bogale; Yihenew Wondie (PhD)
    Radio devices that were previously built in hardware have been replaced in recent years by reconfigurable software defined radio (SDR) systems. Conventional hardware-based radios have restricted multi-functionality and are physically changeable only. This leads to an increase in production expenses and a reduction in the number of waveform standards that can be supported. A rapid and affordable answer to this issue is provided by software-defined radio technology, which enables software upgrades for multi-mode, multi-band, and multi-functional wireless devices. In SDR, different modulation techniques are used to achieve efficient communication over a radio channel. Multi-mode modulation is an approach that allows the use of multiple modulation schemes in a single system, which can enhance the flexibility and resilience of communication systems. This paper presented a design and implementation of multi-mode modulation techniques for SDR using FPGA and analyze the performance based on the FPGA resource utilization. It combines six modulation schemes: QASK, QPSK, QAM, AM, PM and FM to create multi-mode modulation system. The performance of this multi-mode modulation system is evaluated in terms of FPGA resource utilization such as total computational power, total number of Look Table (LUT) or memory used, Flip Flops (FF) and Input/Output (IO) port usage. Xilinx Vivado system generator for DSP with MATLAB/Simulink is used to design, simulate and verify the multi-mode modulator, which would then be implemented on a Xilinx Zedboard FPGA hardware. A total of 0.225W power, 844 number of LUT and 1 IO port is utilized by the implemented design. The biggest thing we achieved in this research is that we saved computational power. 1.572W and 1.134W amount of power is saved by our design as compared to previous two studies.
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    Design and Performance Evaluation of Power-aware Routing Protocols for Wireless Sensor Networks – GAICH and GCH
    (Addis Ababa University, 2011-10) Seifemichael Bekele; Dereje Hailemariam (PhD)
    In recent years, the advancements in wireless communications and electronics have enabled the development of low-cost, low-power and multifunctional wireless sensor networks (WSNs). As nodes in sensor networks are equipped with a limited power source, efficient utilization of power is a very important issue in order to extend the network lifetime. It is for these reasons that researchers are currently focusing on the design of power-aware protocols and algorithms for sensor networks. In this thesis, two routing protocols that provide efficient energy management for WSNs are proposed. The first protocol, GAICH (Genetic Algorithm Inspired Clustering Hierarchy), makes use of genetic algorithm to create optimum clusters in terms of energy consumption. The other one, GCH (Grid Clustering Hierarchy), creates clusters by forming virtual girds, where nodes share the role of cluster head in a round-robin fashion. These protocols have been implemented in MATLAB using a standard radio energy dissipation model that is used for the simulation of WSNs. Performance comparison has been made with two of the existing routing protocols: LEACH and Direct Transmission, on different performance metrics. Simulation results show that GAICH and GCH are better than LEACH in the total packets sent to the base station and network lifetime. Moreover, different techniques for optimizing energy consumption in WSNs are suggested.
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    Prediction of Base Transceiver Station Power Supply System Failure Indicators using Deep Neural Networks for Multi-Time Variant Time Series
    (Addis Ababa University, 2023-11) Jalene Bekuma; Dereje Hailemariam (PhD)
    The uninterrupted operation of wireless communication services relies heavily on the stability of power supply systems for Base Transceiver Stations (BTS). This study is dedicated to predicting potential failure indicators in BTS power systems using deep neural network architectures, such as recurrent and convolutional neural networks. The study integrates principal component analysis (PCA) for data dimensionality reduction and addresses challenges related to power system failures caused by environmental factors, power fluctuations, and equipment malfunctions within the Ethio telecom BTS system. The dataset utilized in this study spans four weeks of data from multiple sites, with observations sampled at 5-minute intervals, obtained from the ET NetEcho power monitoring system. The study meticulously explores the data preprocessing steps for time series analysis, encompassing consolidation, cleaning, scaling, and dimensionality reduction using PCA. Furthermore, it delves into the detailed implementation of CNN, LSTM, and CNN-LSTM models for time series prediction, thoroughly evaluating their performance and convergence. The experimental results clearly indicate that CNN-LSTM model surpasses both LSTM and CNN models in predicting BTS power system failure indicators, achieving the lowest loss values of 0.036 MSE, 0.189 RMSE and 0.112 MAE using CNN_LSTM model. These findings shows the potential of deep neural network architectures, particularly CNN_LSTM model in accurately predicting BTS power system failure indicators for the next thirty minutes. The significance of accurate prediction models in proactively detecting failures and minimizing their impact is highlighted, contributing to the reliability and stability of BTS power supply systems for wireless communication services.
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    Optimization of Millimeter Wave Microstrip Antenna for Wireless Application Using Genetic Algorithm
    (Addis Ababa University, 2023-12) Arebu Dejene
    In the telecommunications industry, wireless communications have progressed very rapidly in the last two decades. The requirement for high data rates and the paucity of spectrum in existing wireless communication drive next-generation communication technology to mm-wave frequencies, which also require adequate and efficient antenna technology for successful operation. These signals, however, have a high path loss and are susceptible to blocking. These mm-wave signal propagation challenges can be overcome by using high-directivity, wide-band, and multi-band antennas. Nonetheless, creating such a high-performance antenna in every way is a challenging endeavor. This dissertation discourses on the modeling, optimizing, and synthesizing of a rectangular microstrip patch antenna with dual-band and multi-band service for mm-wave communication using a binary-coded genetic algorithm to improve the directivity and bandwidth. The algorithm iteratively creates new models of patch surfaces by employing an iterative combination of HFSS and MATLAB software, and then returns the best antenna model. Accordingly, the dissertation exhibits improvements in the directivity, bandwidth, and multi-functionality of a single microstrip antenna. With patch geometry optimization, a dual-band antenna was optimized and resonated at 28.0 GHz and 46.6 GHz with acceptable performance. Another optimization was carried out on a single microstrip antenna for triple band operation and directivity improvement. The optimized antenna resonated at three distinct frequency bands centered at 28.0 GHz, 40.0 GHz, and 47.0 GHz, and demonstrates broadside radiation patterns with peak directivities of 7.7 dB, 12.1 dB, and 8.2 dB, respectively. On the other hand, bandwidth melioration was achieved by a genetically optimized quad-band antenna, which was resonated at four frequencies centered at 28.3 GHz, 38.1 GHz, 46.6 GHz, and 60.0 GHz, and a total operating bandwidth of 11.5 GHz. The dissertation also presents a penta-band mm-wave antenna for wearable applications. The proposed antenna designed on PTFE fabric substrate and resonates at five distinct frequencies: 27.8 GHz, 30.3 GHz, 40.1 GHz, 47.2 GHz, and 56.7 GHz. In free space, the antenna achieves a wide bandwidth of 0.69, 2.32, 2.22, 1.76, and 8.11 GHz and an improved broadside directivity of 10.3, 8.5, 7.8, 9.6, and 8.9 dB, respectively. Overall, the optimized antennas performances were suitable for multi-functional mm-wave applications.
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    Comparative Study of Machine Learning Techniques for Path Loss Prediction
    (Addis Ababa University, 2023-11) Ademe Wondimneh; Dereje Hailemariam (PhD)
    Path loss is the term used to describe the difference in signal strength between transmitted and received. Predicting this loss is a crucial task in wireless and mobile communication to gather data for resource allocation and network planning. Deterministic and empirical models are the two fundamental propagation models that are used to calculate path loss. There is a trade-off between accuracy and computing complexity between these models. Machine learning models reflect a classic conflict between accuracy and complexity and have significant potential in path loss prediction because they can learn complicated non-linear correlations between input properties and target values. This study investigates the application of machine learning techniques for path loss prediction in Addis Ababa LTE networks. Artificial neural networks (ANNs), random forest regression (RFR), and multiple linear regressions (MLR) are employed as machine learning models and compared with the widely used COST 231 empirical model. Data for training and testing is obtained through measurements from Addis Ababa LTE networks. The performance of the proposed models is evaluated using statistical metrics such as root mean squared error (RMSE), mean absolute error (MAE), and R-squared (R2). The results demonstrate that the RFR model outperforms the other models in terms of prediction accuracy, achieving an MAE of 3.48, an RMSE of 5.35, and an R2 of 0.77. The ANN model also exhibits satisfactory performance with an MAE of 4.19, an RMSE of 5.78, and an R2 of 0.71. The Cost 231 model, on the other hand, exhibits lower prediction accuracy. In terms of computational complexity, ANNs are found to be the most computationally intensive, while MLR is the simplest model among the evaluated machine learning models. RFR falls between ANNs and MLR in terms of computational complexity.
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    Power Control and Resource Allocation for Performance Optimization in D2D Underlaid Massive MIMO System
    (Addis Ababa University, 2022-09) Abi Abate; Anna Förster (Prof.); Yihenew Wondie (PhD)
    The desire to support the ever-increasing demand for wireless broadband service and a broad range of Internet of Things (IoT) applications, where fourth-generation (4G) wireless networks are struggling to deliver, necessitates new fifth-generation (5G) network architecture. The emerging 5G network should employ multiple advanced networking solutions to overcome the challenges posed by dynamic service quality requirements. As a single technology cannot achieve the diverse set of 5G requirements, the challenges and benefits of integrating multiple technologies in one system are worth investigating. On the other hand, the need to communicate with low latency requires a fundamental shift from centralized resource management and interference coordination toward distributed approaches, where intelligent devices can rapidly make resource management decisions. In this thesis, we proposed a distributed resource management and interference coordination scheme to optimize network performance for the coexistence of two technologies that have been identified as competent candidates for achieving the challenging 5G system performance criteria, namely, massive multiple-input multiple-output (MIMO) and network-assisted device-to-device (D2D) communications. First, we formulated a two-tier heterogeneous network with two different user types. The first tier serves the cellular users in the uplink by a multi-antenna Base Station (BS). The second layer serves D2D users exploiting their proximity and transmitting simultaneously, with the uplink cellular user bypassing the multi-antenna BS. Then, we formulated the throughput and energy efficiency optimization problem as a nonlinear optimization problem. To realize a distributed solution, we modelled each optimization problem into a matching game and proposed a resource allocation scheme based on the concept of matching theory. The analysis reveals that the implementation of the proposed distributed resource assignment and interference coordination scheme can achieve more than 88% of the ASR and 85% of the EE performance of optimal result. Next, we proposed a three-stage distributed solution to enhance the sum rate and analyze the impact of joint channel assignment and power control. We model the channel assignment problem in the first stage as a matching game. During this stage, each D2D pair sends its preferred channel request to the BS; and the BS accept the most preferred request. In the second stage, we model the power allocation problem as a non-cooperative game. Each D2D pair optimizes its utility value according to its side link quality and interference channel gain to limit the D2D-to-cellular interference. Finally, in the third stage, the algorithm considers the peer effect, searching for blocking pairs until stable matching is established. The performances of proposed schemes are investigated as a function of the number of BS antennas and cellular and D2D users and compared with the random and optimal counterparts. The numerical results show that the joint optimization of channel assignment and power control can enhance the sum rate performance of channel assignment with binary power allocation scheme where D2D pairs are either turned on with full power or turned off completely by 16%. In general, the extra degrees of freedom resulting from having multiple antennas at BS is highly desirable in the design of future D2D-enabled massive MIMO networks, as many side link users can be multiplexed, and inter-user interference can be controlled.
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    Side Lobe Reduction in Equally Spaced Linear Antenna Arrays using Antenna Thinning Technique
    (Addis Ababa University, 2023-11-22) Yonas Techale; Murad Ridwan (PhD)
    In antenna array design, the radiation pattern is a fundamental performance metric. It is a mathematical or graphical representation of the spatial distribution of radiated energy of an antenna array as a function of directional space coordinates. Array antennas can vary their directivity patterns through amplitude and phase control. One of the most important aspects of an antenna array is reducing interference and radiation power waste. Reduced side lobe level also avoids false target indication. Thinning is a technique for reducing the total number of active elements in an antenna array while maintaining system performance. This study aims to improve antenna performance by lowering the side lobe level using antenna thinning applying GA. A genetic algorithm achieves optimal solution by simulating the natural selection process. It starts with randomly selected candidates as the first generation. In the beginning, we studied radiation patterns of equally spaced and non-equally spaced linear antenna arrays; and radiation patterns for uniformly spaced, non-uniformly spaced, and non-uniformly spaced with rotated elements array for N=20. It is demonstrated in the result that non-uniform spacing and rotated elements can significantly improve the directivity and reduce side lobes compared to uniformly spaced arrays. In addition, it is observed in the beam pattern resulting from one typical first-generation candidate that the sidelobe level is lower in the azimuth direction but higher in the elevation direction compared to the full array. The exact sidelobe level and fill rate of the array is then around 8.7 and 71.75% respectively. This means that 71.75% of the array elements are active and the sidelobe level is approximately 9 dB. It needs to be suppressed further by applying a genetic algorithm with 30 generations. Thus, the result shows the sidelobe level and fill rate of the array after applying GA with 30 generations is around 17.38 and 76.5% respectively. Compared to the first-generation candidate, it uses 5% more active elements while achieving an additional 9 dB sidelobe suppression. Compared to the full array, the resulting thinned array can save the cost of implementing T/R switches behind dummy elements, which in turn leads to a roughly 25% saving on the consumed power. Even though the thinned array uses fewer elements, the beamwidth is close to what could be achieved with a full array.
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    Performance Analysis of Linear Precoding for Multiuser Multiple-Input and Multiple-Output Broadcast Channels
    (Addis Ababa University, 2023-09) Worku, Tamene; Murad, Ridwan (PhD)
    Multiuser Multiple Input and Multiple Output is an antenna technology for wireless communication in which number of users or wireless terminals each with one or more number of antennas communicate with each other. Precoding in multiuser MIMO systems is important to minimize or mitigate the multiuser interference. As a consequence, the design of suitable precoding algorithms with a low computational complexity and a good overall performance is a challenging scenario when system dimensions are high. A linear precoding technique such as regularized channel inversion (minimum mean square error), channel inversion (zero forcing), and Block diagonalization techniques for multi-user multiple input multiple-output broadcast channels are able to eliminate the multiuser interference per antenna or sum power constraint. After conducting this thesis an enhanced performance is measured from this thesis. In case, analysis of the MU-MIMO with fewer number of antennas may reduce the cost of antenna and some complexities in large antenna system. Different researches are conducted in multiuser MIMO with single antenna receivers and conducted mostly in Rayleigh channel conditions. Besides, the performance of multiuser MIMO linear precoding under different channel conditions together with two or more antenna receivers have been investigated in this work. In this research, the performance of linear precoding in multiuser MIMO under Rayleigh, Rician and Deterministic channel conditions are illustrated in different performance metrics like data rate, channel capacity and spectral efficiencies. The performance of linear precoding under multiuser MIMO with two antenna users have a great performance due to the combined effect of the antennas. In addition, the Rican channels achieves minimum bit error rate than Rayleigh and deterministic channels. Furthermore, this study has advantage of detail comparative analysis when the users are more, and this analysis have a direct impact when the congested number of users are involved.
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    Techno-economic Comparison of Mid-band 5G Fixed Wireless Access and GPON-based Optical Distribution Networks
    (Addis Ababa University, 2023-06) Tujuma, Bayisa; Dereje, Hailemariam (PhD)
    The popularity of broadband Internet services has increased significantly over the past few years. Similarly, the development of mobile network technologies has seen rapid growth. Due to these trends, Fifth Generation (5G) Fixed Wireless Access (FWA) networks have been proposed as a potential competitor to other broadband access technologies, such as Optical Distribution Network (ODN). However, technological advancement itself cannot show the performance, acceptance, or economic viability of an investment without a detailed technical and economic feasibility assessment of possible broadband deployment alternatives. This thesis conducts a techno-economic comparison between 5G FWA at mid-band frequency range and Gigabit Passive Optical Network (GPON) based ODN to provide broadband services for residential users. It presents a techno-economic analysis of four possible deployment scenarios: namely, two scenarios (Sc-1) and scenario (Sc-2) based on 5G FWA using new and existing infrastructure, respectively. The other two scenarios (Sc-3) and scenario (Sc-4) are GPON-based ODN using new and existing infrastructure, respectively. These scenarios are evaluated in the context of the capital city of Ethiopia, Addis Ababa, around an area called Tulu Dimtu. Data collected from the operator, ethio telecom, serves as main source of information. For the evaluation, the most popular and widely used techno-economic tool, called Techno-economic Results from the Advanced Communications Technology and Services (TERA), is modified and implemented including network dimensioning, revenue modeling, cost modeling, and economic analysis. For all analyses, 10-years study period and 10% discount rate are considered. The analyses were evaluated using standard economic indicators such as Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PBP). MATLAB and Microsoft Excel are used for the implementation. Achieved result shows that the PBP of the scenarios are: 4.48, 3.75, 4.63 and 4.37 years for Sc-1, Sc-2, Sc-3, and Sc-4, respectively. Based on NPV results, all scenarios have positive NPV for the study period and greater IRR value than the defined discounted rate. Sensitivity analysis shows that revenue is the most sensitive parameter over the other parameters. The findings indicate that all scenarios are deployable, but they should be deployed based on requirements.
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    Hybrid Microwave and Free Space Optics Network for Mobile Backhaul Capacity and Availability Improvement
    (Addis Ababa University, 2023-06) Mulugeta, Semu; Dereje, Hailemariam (PhD)
    With the growing demand for high speed mobile data and the increasing use of smart devices, the existing microwave (MW) or radio frequency (RF) backhaul network is going to be a bottleneck for end users data volume requirements. Additionally, the performance of the MW link is significantly degraded by bad weather conditions, such as rain. To mitigate these limitations, free space optics (FSO) becomes a promising backhaul technology due to its large bandwidth and use of a different carrier frequency that is not impacted by rain. However, FSO is exposed to link loss or failure under foggy weather conditions, whereas MW links are prone to fog. Having this complementary advantage of FSO and RF, using hybrid FSO/RF networks is a preferred solution to improve the availability of the link and the capacity of backhaul networks. In this paper, an adaptive switching hybrid FSO/RF system is used to improve the performance of the hard switching scheme, which is exposed to link flapping due to short-term changes in weather conditions. The switching threshold of the FSO and RF links and multi-rate switching on each link are determined, and the availability and capacity performance of the hybrid system are investigated based on received signal-to-noise ratio (SNR) values. To meet the objective, the methodology followed includes data collection, system and channel modeling, and RF, FSO, and hybrid performance comparison. The system used gamma gamma distribution for the FSO channel and the Rician model for the RF channel model. Simulation results are obtained using the Matlab tool. The effects of rain and fog on the RF and FSO links are simulated and discussed, respectively. The availability of the system in terms of outage probability shows that the hybrid system significantly reduces the SNR value to 14 dB to achieve 99.99% link availability, which is not achieved by an RF-only or FSO-only link. The result also shows that adaptive switching mode has a better bit error rate (BER) than hard switching mode since the switching of links between FSO and RF and switching between multi rates on each link is based on maintaining target BER. To maintain good quality of service (QoS), the target BER of the system is set, and the system gradually lowers its modulation order to the maximum possible data rate based on received SNR values.
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    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.
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    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.
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    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.
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    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.
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    Performance Evaluation of Precoding Techniques for 5G Massive MIMO Downlink System
    (Addis Ababa University, 2021-06) Beza Shewanega; Yihenew, Wondie (PhD)
    Massive multiple-input-multiple-output (MIMO) systems use a few hundred antennas to simultaneously serve many wireless broadband terminals, using sophisticated coding at the transmitter and substantial signal processing at the receiver, the MIMO channel can be provisioned for higher data rates, resistance to multipath fading, lower delays, and support for multiple users. In multi-user MIMO, a multi-antenna transmitter communicates simultaneously with multiple receivers (each having one or multiple antennas). This is known as space-division multiple access (SDMA) and here Precoding algorithms will be very essential for supporting multi-stream (or multi-layer) transmission in multi-antenna wireless communications, since the research aim is to find the key options to increase the performance of the upcoming 5G wireless system, this research work will focus on one of this options which are downlink distribution Precoding techniques for massive MIMO system, by assuming that both the base station and the user terminals are equipped with an antenna array. Precoding algorithms for SDMA systems can be sub-divided into linear and nonlinear Precoding types. The capacity-achieving algorithms are nonlinear, but linear Precoding approaches usually achieve reasonable performance with much lower complexity. This research work will present a comparative study of different linear Precoding techniques for massive MIMO wireless systems. The performance of the Precoding scheme is evaluated and compared with an iterative Precoding scheme designed to provide a maximum achievable rate gain by exploiting the expanded spatial degrees of freedom.
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    Feasibility Study on Aircraft Location Accuracy Using Multilateration System in the Case of Addis Ababa Bole international Airport
    (Addis Ababa University, 2021-12) Kibreab, Kibebew; Murad, Ridwan (PhD)
    The aviation sector must be safe. Information errors which are provided from ground aids Communication, Navigation and Surveillance (CNS) systems can put the aircraft at risk. Therefore, all ground-based flight aids should always be accurately calibrated. In addition, flight delays can lead to unnecessary fuel consumption and air pollution. Accordingly, in order to provide an efficient air transport system, it is important to have modern, fast and accurate ground based flight aids that provide real and timely information. Air Navigation Aeronautical multilateration systems enable the localization of an aircraft based on the Time Difference of Arrival (TDoA) of its signal to three or more strategically placed receiving ground station antennas, located around an area of interest, providing continuous air traffic surveillance. The main objective of this thesis is to show how to install an optimized multilateration system that can provide an aircraft information (position & identification) and to study the performance analysis of approach type multilateration systems in Ethiopia, specifically in Addis Ababa Bole international airport approach and terminal maneuvering area concerning radio coverage and aircraft location accuracy by considering ground stations’ location, their antennas radiation patterns, transmitted power, receiver sensitivity, and the corresponding parameters for the aircraft. Line of Sight situation is assessed by taking into considerationof Digital Elevation, Fresnel’s Ellipsoid, and the Effective Earth’s Radius Models. The Free-Space Path Loss Model is likewise used, with fading margins being set to model power oscillations due to multipath and the airplane orientation uncertainty. The position accuracy of the aircraftis estimated from the system’s Geometric Dilution of Precision, taking into considerationof error components due to troposphere delay, multipath, receiver noise, quantization, and clock bias. The model will be implemented in a simulator with results in agreement with data from the literature and previously implemented systems.
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    Entropy Estimation and Entropy Based Encoding of Written Afaan Oromo for its Efficient Digital Transmission and Storage
    (Addis Ababa University, 2021-02) Kalkidan, Dejene; Dereje, Hailemariam (PhD)
    According to Ethiopian population census, Oromo Language is estimated to be spoken by 36.4% of the local population. Furthermore, in addition to the local population the language is spoken outside of Ethiopia, for instance in small portion of Kenya. Thus, taking this into account the language is estimated to be spoken by around fty million people. In addition to the spoken form, a considerable portion of the language's speaker are capable of understanding its written form known as Qubee. The introduction of Qubee, in the mid-nineties has opened doors for its utilization in modern day communication systems. Leaving this argument aside, in the eyes of information theory and communication channels both symbol utilization schemes are found to be ine cient. This is because, Latin or Amharic symbols are represented by ASCII8 and UTF 16 xed length encoding mechanisms poorly model written natural language. With the expected increasing demand of the language in telecom services in mind, in this thesis we mainly aim at estimating the Oromo Language Language's entropy. The estimation will set the optimum number of bits per symbol needed to e ciently trans- mit written Oromo Language in communication systems. To achieve our objective, we have modeled the sources, i.e., written Oromo Language, as Nth order Markovian chain random process. Based on the modeling scheme we have studied the distribution of symbols in ten literature written in Oromo Language. The study reveals the Language can be transmitted using 4.31 bits/symbol when modeled as rst order Markovian Chain source. Whereas, the zero crossing entropy of the source was estimated to be in average at N=19.5; which gave an entropy estimation of 0.85 bits/symbol with a re- dundancy of 89.36%. Additionally, we have conducted two entropy-based compression algorithms, namely, Hu man and Arithmetic coding, to test the validity of our estima- tion. The Hu man algorithm was able to compress our sample corpora in average from 42:17% �� 64:88% for N = 1 �� 5. These compression results con rm the results of our Nth order estimation of the Language's entropy by approaching their theoretical limits.
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    Ultrasonic Sensor Probe to Detect Early Signs of Lumbar Disk Herniation
    (Addis Ababa University, 2017) Hanna, Merid; Mohammed, Abdo (PhD)
    Medical imaging has advanced in remarkable ways since the discovery of X-rays 120 years ago. Today's radiologists can image the human body in intricate detail using computed tomography, magnetic resonance imaging, positron emission tomography, ultrasound, and various other modalities. Such technology allows for improved screening, diagnosis, and monitoring of disease, but it also comes with risks. Many imaging modalities expose patients to ionizing radiation, which potentially increases their risk of developing cancer in the future, and imaging may also be associated with possible allergic reactions or risks related to the use of intravenous contrast agents. In addition, the financial costs of imaging are taxing our health care system, and incidental findings can trigger anxiety and further testing. In this thesis, the problem of lack of reachable alternatives for spinal imaging is addressed, to narrow the gap created between the potential victims of this disease and the imaging equipment which could only be accessed through a physician’s order, and is expensive enough for people to dismiss their back pain and/or their neck pain. Therefore another way to diagnose a lumbar disc herniation is required to make the best decisions when it comes to the better option a patient with a lower back pain comes along, which is, a makeshift Ultrasonic Sensor Probe (USP). This thesis depicts the overall design of the kit, which is an ensemble of a sensor, a microprocessor and the other components incased in one, simulation models of the components included in the probe, and the necessary methodologies used to make the modelling of the filters.
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    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.
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    Radio Spectrum Sensing Comparative Analysis for Multiple Primary User Transmitter Detection
    (Addis Ababa University, 2021-07) Ngist, Fentie; Mohammed, Abdo
    A radio spectrum is a particular range of frequencies used to communicate information in a wireless communication system. It is naturally available and scarce resource. Besides to, the dramatically increase of the wireless communication system is a critical issue and the studies show that a certain licensed spectrum are underutilized. To solve this problem the cognitive radio is a key technology when there is a free spectrum band of the licensed users then the cognitive radio system permits that band for unlicensed or secondary users. In addition to that the cognitive radio system continuously monitors at the range of primary user transmission to minimize the interference by the secondary user’s whole opportunistically occupies on the licensed bands. For this task the cognitive radio uses different spectrum sensing methods to avoid the undesirable interfering and recognize the accessible radio spectrum band for secondary users (SUs). In this thesis, the performance of the Spherical and John’s detector spectrum sensing methods in the presence of one and two primary users by implementing it over the typical Rayleigh fading channel is investigated. The performance of probability of detection and Receiver Operating Characteristics (ROC) curves within low signal-to-noise ratio (SNR) range is compared. Using the MATLAB software with the Monte Carlo techniques are used to evaluate and analysis of the performance of this work. The implementation part shows a detailed comparison between the Spherical detector (SD) using General Likelihood Ratio Test (GLRT) estimator and John’s detector (JD) using Locally Best Invariant Test (LBIT) estimator including a single and two primary user (PU) transmitted signals of detection. The specific, result shows the performance efficiency of detection for both schemes with a tolerable interference level under the fading channel. The proposed system uses GLRT estimator for SD and LBIT estimator for JD. After doing the experiment, the result showed that JD provided the better detection performance over SD. To illustrate this, when two PUs are detected by four SUs in cooperative scheme using SD method at SNR range of [-2, -1] dB, the result is found to be incremented from 99.7% to 99.8%. The same experiment is done using JD method and the result shows that the detection performance is in the range of 99.9% and 100%.