Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

Browse

Filters

2020 - 20234

Settings

Publisher: search.filters.publisher.IEEESubject: search.filters.subject.Massive MIMO

Search Results

Now showing 1 - 4 of 4
  • Article
    Citation - WoS: 15
    Citation - Scopus: 17
    Massive Mimo-Noma Based Mec in Task Offloading for Delay Minimization
    (IEEE, 2023) Yilmaz, Saadet Simay; Özbek, Berna
    Mobile edge computing (MEC) has been considered a promising technology to reduce task offloading and computing delay by enabling mobile devices to offload their computation-intensive tasks. Non-orthogonal multiple access (NOMA) is regarded as a promising method of increasing spectrum efficiency, while Massive multiple-input multiple-output (MIMO) can support a larger number of users for simultaneous offloading. These two technologies can effectively facilitate offloading and further improve the performance of MEC systems. In this work, we propose a NOMA and Massive MIMO assisted MEC system for delay-sensitive applications. Our objective is to minimize the overall computing and transmission delay under users' transmit power and MEC computing capability. Through the pairing scheme for Massive MIMO-NOMA, the users with the higher channel gain can offload all their data, while the users with the lower channel gain can offload a portion of their data to the MEC. Performance results are provided regarding to the sum data rate and overall system delay compared with the orthogonal multiple access (OMA)-MIMO based and Massive MIMO (M-MIMO) based MEC systems.
  • Article
    Citation - WoS: 8
    Citation - Scopus: 11
    Delay Minimization for Massive Mimo Based Cooperative Mobile Edge Computing System With Secure Offloading
    (IEEE, 2022) Mümtaz, Rao; Yılmaz, Simay; Özbek, Berna
    Mobile edge computing (MEC) has been envisioned as a promising technology for enhancing the computational capacities of mobile devices by enabling task offloading. In this paper, we present a novel framework for a cooperative MEC system by employing Massive Multiple-Input Multiple-Output (MIMO) and non-orthogonal multiple access (NOMA) technologies, including security aspects. Specifically, in the proposed cooperative MEC system, there is no strong direct transmission link between the cell-edge user and the MEC server; consequently, the user sends their tasks to the MEC server through the helpers at the cell-centers. In the proposed framework, we minimize the overall delay, including secure offloading under the constraints of computing capability and transmit power. The proposed algorithm minimizes the overall delay in downlink and uplink transmission while satisfying security constraints to solve the formulated problem. The simulation results show that Massive MIMO based NOMA improves the performance of the secure MEC system by employing more than one helper.
  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 2
    Limited Feedback Design for Massive Full Dimension Mimo Systems
    (IEEE, 2022) Özbek, Berna; Arslan, Caner; Demirtaş, Mahmut; Şahan, Hüsne; Kadı, Furkan Kerim; Elçi, Erdem
    Massive Multiple-input Multiple-output (MIMO) systems serve simultaneously multiple users to increase spectral efficiency in wireless communication systems. Using two dimension antenna design for massive MIMO systems namely massive FD-MIMO, the overall system performance is further improved. For the massive FD-MIMO systems, the availability of channel state information (CSI) at the base station is essential to achieve overall performance gain. In this paper, we design limited feedback link for massive FD-MIMO by designing two separate codebooks for horizontal and elevation domains to reduce the feedback load. The simulation results are provided for the proposed scheme by considering 3-dimension wireless channel models.
  • Conference Object
    Citation - Scopus: 7
    Compressive Sensing Based Low Complexity User Selection for Massive MIMO Systems
    (IEEE, 2020) Yllmaz, Saadet Simay; Ozbck, Bcma
    Massive Multiple-input Multiple-output (MIMO) is widely considered as a key enabler of the next-generation networks. In these systems, user selection strategies are important to achieve spatial diversity and maximize spectral efficiency. In this paper, a user selection algorithm is proposed with the reconstruction of the sparse Massive MIMO channel using Compressive Sensing (CS) algorithm. The proposed algorithm eliminates the users based on the channel correlation by employing the CS algorithm which reduces the feedback overhead in the system. The simulation results show that the proposed algorithm outperforms the traditional user selection algorithms in terms of sum data rate and computational complexity. Moreover, the effects of the sparsity level and feedback measurement on the performance are examined.