01. School of Engineering and Digital Sciences

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Browsing 01. School of Engineering and Digital Sciences by Subject "5G"

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    BUTLER MATRIX MINIATURIZATION FOR 5G COMMUNICATIONS AND BEYOND
    (Nazarbayev University School of Engineering and Digital Sciences, 2024-04-19) Amangeldi, Yerassyl
    This capstone project presents a miniaturized implementation of Butler’s beamforming array on microstrip technology. Firstly, the basis of size reduction is obtained by developing a structure that behaves exactly as the quarter-wave transmission line segment at the operation frequency. Secondly, this structure is applied to reduce the area of higher-order components such as 3dB hybrid coupler and crossover. Then, the components are assembled into the layout of Butler Matrix where several components are reduced in size further. The obtained final structure takes up approximately two times less area at the cost of 20% theoretical bandwidth reduction. A 4-by-4 experimental setup is developed for validation at 2.5 GHz which corresponds to the lower 5G frequency band.
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    DESIGN OF 60GHZ ANTENNA FOR 5G COMMUNICATION SYSTEMS
    (Nazarbayev University School of Engineering and Digital Sciences, 2024-04-22) Anwar, Talha
    5G technology was developed to transform mobile communication through fast data rates, reduced latency, and enhanced network capacity. Transitioning to higher frequencies, especially in the millimeter wave region, has presented issues related to signal path and propagation loss. To address these limitations, a systematic examination is being conducted to explore the use of the 60GHz frequency band. This action aims to overcome existing challenges in implementing 5G and prepare the foundation for upcoming generations such as 6G. Utilizing 60GHz frequencies can enhance the capabilities and possibilities of wireless communication, leading to a more efficient and productive network. This study presents a proposal for a microstrip patch array antenna consisting of four components, designed specifically for 5G wireless applications, with a particular emphasis on the utilization of the 60 GHz millimeter-wave spectrum. The emphasis of the design is on the choice of a single microstrip patch antenna as the primary radiating component using Rogger RT 5880, Teflon, and LTCC A6M as a dielectric substrate. The antenna is designed to function exceptionally well in a wide range of weather situations while simultaneously guaranteeing robustness and dependability. This master thesis highlights the notable performance variations across Roggers RT5880, Teflon, and LTCC A6M substrates when designing single, two, and four-element patch antenna arrays for 5G communication systems at 60 GHz. The design approach makes use of Computer Software Technology (CST) Microwave Studio, which integrates different dielectric substrates Roggers RT5880, Teflon, and LTCC A6M characterized by a relative permittivity of 2.2, 2, and 5.9 respectively. LTCC A6M substrate offered high-quality antenna performance results when arranged in an elements array using single layer substrate. And Teflon offered better results when arranged in a single and two-elements array. However, thefinal results emphasize Roggers RT5880 as the best substrate material due to its outstanding characteristics like high gain, high directivity, broad bandwidth, input impedance matching,and compact size. The findings offer useful recommendations for enhancing antenna designs and selecting substrates, ultimately promoting the creation of high-performance antennas customized for modern wireless communication applications.
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    PERFORMANCE ANALYSIS OF EDGE COMPUTING FOR 5G AND INTERNET OF THINGS
    (Nazarbayev University School of Engineering and Digital Sciences, 2022-05) Ospanova, Aigerim
    This thesis aims to explore edge computing paradigm for Internet of Things services and applications in the 5G era. Edge computing, with its processing and storage capabilities near end-users, can become a reasonable alternative to cloud computing. User device with constrained processing and storage capabilities offloads complex task to edge nodes for computing, and then, edge nodes transmit the outcomes back to the user. Though various requirements need to be met while deploying edge computing in smart applications, this work focuses on the most demanding and critical ones, such as latency and system reliability. It is crucial to minimize latency and enhance the reliability of the system in time-critical services, such as smart healthcare or transportation. Current research implements a single user – multiple edge nodes model with Rayleigh and Nakagami-m fading channels. It is worth noting that Nakagami-m fading channels are widely used in the fifth generation and beyond systems. In order to comprehensively investigate the topic of edge computing for Internet of Things, we have developed two different types of schemes. Specifically, selection schemes, in which user device offloads task to one edge node, and combining schemes, in which user device offloads task to several edge nodes concurrently. Concerning selection-based schemes, edge computing with cache-aided relay and cache-free relay are considered. In these schemes, offloading nodes are chosen based on the best computing capability, channel gain between user and edge node, or channel gain between the user device and relay node. Numerical results demonstrate that edge computing model with cache-free relay, where the best channel gain between the relay and edge node is selected, outperforms other models in system performance. At the same time, time-division multiple access, frequency-division multiple access, and capacity achieving schemes are introduced for combining case. Thus, it can be summarized that edge computing model with capacity achieving scheme demonstrates the highest results among the others in terms of the reliability metric. Moreover, performance analysis shows that system efficiency can be affected by various parameters, such as transmit power, channel bandwidth, task size, latency threshold, number of edge nodes, and others. Numerical and simulation results are provided to validate analytical findings.
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    PHYSICAL LAYER SECURITY USING MASSIVE MIMO AND RIS TECHNOLOGY
    (Nazarbayev University School of Engineering and Digital Sciences, 2024-04-19) Abdrakhmanov, Rakhat
    Massive Multiple-Input-Multiple-Output (MIMO) systems and Reconfigurable Intellegent Surfaces (RIS) are considered to be the key technologies for next generations wireless communication, which are aimed to achieve higher data rates, massive connectivity and more secure data transmission. Combined use of these technologies together with artificial noise (AN) gives high hopes for strengthening Physical Layer Security (PLS) in wireless networks. This capstone work considers configuring phase shifts of RIS such that the impact of AN is maximized for illegitimate user, while its impact on legitimate user is not significant compared to the actual signal received from base station. In the proposed system model, some antennas is dedicated for AN and the rest are transmitting the actual data. The main objective of this model is to maximize Secrecy Capacity (SC) of the communication link, while satisfying the users’ quality of service (QoS). To achieve that, we optimize the phase shifts of RIS and find the optimal number of base station antennas transmitting AN. Obtained results validate theoretical concepts and show that proposed RIS-assisted Massive MIMO incorporated with AN transmission can be an effecting tool for establishing and improving PLS in wireless communication.
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    RECEIVER ARCHITECTURES AND ALGORITHMS FOR NON-ORTHOGONAL MULTIPLE ACCESS
    (Nazarbayev University School of Engineering and Digital Sciences, 2020-05) Manglayev, Talgat
    Multiple access (MA) schemes in cellular systems aim to provide high throughput to multiple users simultaneously while utilising the network resources efficiently. Traditionally, each user in the network is assigned a fraction of resources (such as slots in time or frequency) to operate so that multi-user interference is avoided. These schemes are named as ‘orthogonal multiple access’ (OMA) and are the basis of most cellular standards – from the earliest first generation up to the current fourth-generation systems. Non-orthogonal multiple access (NOMA) on the other hand is a novel method that allows all the users in the network to operate in the entire available spectrum at the same time which enables significant improvement in the system throughput. While providing increased throughput, NOMA requires high computational power in order to implement sophisticated interference cancellation algorithms at each user terminal, as well as power allocation schemes at the base station. As a potential candidate for the fifth-generation networks (5G), NOMA must meet certain requirements, and computational efficiency is essential for reduced latency. Recently graphics processing units (GPUs), which were initially intended for outputting images to display, appeared as an alternative to multi-core central processing units (CPUs) for general-purpose computing. GPUs have thousands of cores with approximately three times less frequency than a CPU core. With their numerous advantages in executing heavy and time-consuming computations in parallel, GPUs have become attractive platforms in a variety of fields. The overall aim of this research is to significantly increase the scientific understanding and technical knowledge on NOMA. This is achieved by exploring and developing novel methods, models, designs and techniques that will facilitate the implementation of NOMA for future generation networks. First, the achievable data rates for individual users are demonstrated in a successful interference cancellation (SIC) based NOMA network. These results were compared against the conventional orthogonal MA schemes with optimum power allocation and varying fairness. In addition, a further investigation was carried out into the deficiency of SIC receivers which can occur when a user in the networks attempts to decode other users’ signal. Presented in the analysis is the findings from the experimental process where the decoding order of a user with a mismatched signal was observed as well as the significant impact on the computation time. The decoding time-difference between correct and mismatched decoding order as a detection method of deficiency or fraudulence in the network is then discussed. Next, a comparison is presented between the computational times of the SIC receiver with another popular interference cancellation scheme named ‘parallel interference cancellation’ (PIC). This was done using different platforms specifically for an uplink NOMA system. The results showed that the computation time of PIC scheme is significantly lower than SIC on the GPU platform even for a very large number of available users in the network. Then, the execution time of NOMA with SIC in the uplink of a cellular network with user clustering was examined. User clustering is a popular method in NOMA networks that eases the sophisticated resource allocation and network management issues. While most works found in the literature review concentrate on the joint optimisation of user grouping and resources, this research project focused on processing the signal detection of each cluster in parallel on the GPU platform at the base station. Following this, parallel interference cancellation (PIC) was implemented and compared with the existing SIC on both CPU and GPU platforms for uplink NOMAOFDM. Architectures of the receivers were modified to fit into parallel processing. GPU was found applicable to speed up computations in NOMA based next-generation cellular networks outperforming up to 220 times SIC on CPU. Finally, the research presents the power allocation problem from artificial intelligence (AI) perspective and propose a method to predict the power allocation coefficients in a downlink NOMA system. The results of the research show a close-to-optimal sum rate with about 120 times reduced computation time. The achieved results decreases the network latency and assist NOMA to meet 5G requirements.