Elektrik- Elektronik Mühendisliği

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Browsing Elektrik- Elektronik Mühendisliği by Subject "5G mobile communication systems."

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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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    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.