Boğaziçi Üniversitesi Tezleri

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Browsing Boğaziçi Üniversitesi Tezleri by Subject "5G mobile communication systems."

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    Achieving ultra-reliable low-latency communication (URLLC) in next-generation cellular networks with programmable data planes
    (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Gökarslan, Kerim.; Tuğcu, Tuna.
    Recent advancements in wireless technologies towards the next- generation cellular networks have brought a new era that made it possible to apply cellular technology on traditionally-wired networks with tighter requirements, such as industrial networks. The next-generation cellular technologies (e.g., 5G and Beyond) introduce the concept of ultra-reliable low-latency communications (URLLC). This thesis presents a Software-Defined Networking (SDN) architecture with programmable data planes for the next-generation cellular networks to achieve URLLC. Our design deploys programmable switches between the cellular core and Radio Access Networks (RAN) to monitor and modify data traffic at the line speed. We introduce the concept of intra- cellular optimization, a relaxation in cellular networks to allow pre-authorized in-network devices to communicate without being required to signal the core network. We also present a control structure, Unified Control Plane (UCP), containing a novel Ethernet Layer control protocol and an adapted version of link-state routing information distribution among the programmable switches. Our implementation uses P4 with an 5G implementation (Open5Gs) and a UE/RAN simulator. We implement a Python simulator to evaluate the performance of our system on multi-switch topologies by simulating the switch behavior. Our evaluation indicates latency reduction up to 2x with intra- cellular optimization compared to the conventional architecture. We show that our design has a ten-millisecond level of control latency, and achieves fine-grained network security and monitoring.
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    Handover with network slicing in 5G networks
    (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2021., 2021.) Sevim, Kübra.; Tuğcu, Tuna.
    5G suggests many advantages but these advantages bring some problems to be solved. Network Slicing is one of the key concepts that 5G introduces. Slicing enables having multiple isolated virtual networks on top of the same physical infrastructure. Thus, each slice can provide di↵erent services with diverse Quality of Service (QoS) requirements. In 5G, Software Defined Networking (SDN) and Network Function Vir tualization (NFV) are critical to support network slicing. In the literature, several problems of network slicing are studied. Two outstanding areas of focus are admission control and resource allocation. Most of the studies are on the Core Network resources although it is essential to investigate radio resource allocation in order to maintain an end-to-end isolation for slices. While there are considerable contributions around Radio Access Network (RAN) resource allocation, optimizing the throughput of the network is not fully achievable via admission control. In this thesis, we mainly focus on handover to maintain the usability and high utilization of the radio resources of the networks. When the number of users within one cell suddenly increases up to the limit of the base station, all of the incoming requests may not be handled and most of the users may su↵er from not being able to use the o↵erings of the slices that they demand. We develop an optimization problem to opti mize the radio resources and propose an heuristic to reach similar results by leveraging handover in considerably low computing times and with the simulation results we show that our heuristic can present solutions close to the optimal within a short time frame.
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    Inter-numerology interference minimization ın 5G : a deep reinforcement learning based approach
    (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2023., 2023) Erk, Tuğrul Can.; Pusane, Ali Emre.
    The use of 5G technologies has become prevalent over the years with the increased use of mobile devices, video services, and more. At the same time, 5G technology brings lower latency, higher reliability, and higher throughput than 4G technology. creation of network slices via software-defined networks and network virtualization functions enables these improvements. A network slice provides flexibility to the network. Each slice can be dynamically configured within itself via SDN/NVF. The network meets diverse requirements of diverse services by creating a network slice. At the higher level, NVF is responsible for creating and managing network slices. The reflection of a network slice on the physical layer is RAN slicing. With the numerology concept merging with 5G, the radio spectrum and corresponding resources become configurative in a manner of bandwidth, sub-carrier spacing, etc. However, the numerology solution has one drawback. Changing sub-carrier spacing in the resource grid destroys the orthogonality principle in the traditional OFDM signals. This leads the network to face new interference, inter-numerology interference. The solutions that enable these improvements have also brought optimization problems that we have not faced In 4G networks. The main problem is about optimization since 5G technology requires heterogeneous signals for heterogeneous services. Therefore, the optimal allocation of limited resources in order to prevent this problem is the essential aim of this paper, with the minimization of inter-numerology interference and maximizing channel capacity.
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    Network data analytics function in 5G networks
    (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Sevgican, Salih.; Tuğcu, Tuna.
    Wireless cellular networking in the world goes through a tremendous structural change where many advances in technology find an opportunity to present themselves for assistance. 5G cellular network, the most recent generation wireless network cur rently undergoing implementation, welcomes artificial intelligence with the novel net work data analytics function (NWDAF). NWDAF is a data analytics mechanism where other components of 5G can request information from in order to utilize their oper ations. In this thesis, the structure and protocols of NWDAF are described. A 5G network data set is generated by using the fields obtained from the technical specifi cation documents provided by 3rd Generation Partnership Project (3GPP). To bring the generated data set closer to reality, randomly created anomalies are added. Sev eral machine learning (ML) algorithms are trained to study two aspects of NWDAF, namely network load prediction and anomaly detection. Linear regression (LR), re current neural network (RNN) and long-short term memory (LSTM) algorithms are implemented and trained using the generated data set and a data set obtained from a real enterprise network for network load prediction [1, 2]. Mean absolute error and mean absolute percentage error performance metrics indicate that RNN and LSTM outperform LR in both generated and real life data sets. LSTM is the best perform ing algorithm for the real life data set. Logistic regression and a tree-based classifier, XGBoost are implemented for anomaly detection, and trained using the generated data set to maximize the area under receiver operating characteristics curve. The re sults indicate that tree-based classifier XGBoost outperforms logistic regression. These predictions are expected to assist 5G service-based architecture through NWDAF to increase its performance.
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    Resource allocation methods for next-generation networks
    (Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2023., 2023) Altın, İlke.; Akar, Mehmet.
    In 5G and beyond systems, the number of connections and data traffic is expected to grow significantly. To support the ever- increasing requirements, new solutions such as Mobile Edge Computing (MEC), Non-Orthogonal Multiple Access (NOMA), and Heterogeneous Networks (HetNets) are studied extensively. This thesis focuses on the resource allocation methods for uplink Hybrid NOMA for MEC offloading, downlink Hybrid NOMA, and downlink HetNets. First, a joint resource allocation that minimizes the total energy consumption of users for uplink Hybrid NOMA MEC Offloading is proposed. By solving the joint optimization problem, we propose a novel optimal Hybrid NOMA scheme referred to as Switched Hybrid NOMA for power and time allocation. Subsequently, we propose an algorithm to solve the sub-channel allocation (SCA) problem. We demonstrate that the proposed methods outperform the results in the literature analytically and by simulations. Then, we switch to the downlink communication, and study a resource allocation scheme that minimizes the total weighted energy consumption in the network. We propose a novel optimal Hybrid NOMA scheme for two users and then extend this idea to multiple users. Via simulations, we demonstrate that the Hybrid NOMA method outperforms Orthogonal Multiple Access (OMA) and NOMA methods. Afterward, we investigate novel distributed sub-channel and power allocation algorithms for HetNets. We introduce an SCA algorithm that minimizes the effective interference experienced by users in the network. Then, a distributed algorithm for power allocation is proposed, and a joint resource allocation method is constructed by combining the proposed algorithms, which outperforms the existing methods in the literature.