Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

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

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Access Right: Closed AccessAuthor: search.filters.author.Le Ruyet, Didier

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  • Article
    Citation - WoS: 2
    Citation - Scopus: 2
    Deep Learning Based Adaptive Bit Allocation for Heterogeneous Interference Channels
    (Elsevier, 2021) Aycan, Esra; Özbek, Berna; Le Ruyet, Didier
    This paper proposes an adaptive bit allocation scheme by using a fully connected (FC) deep neural network (DNN) considering imperfect channel state information (CSI) for heterogeneous networks. Achieving an accurate CSI has a crucial role on the system performance of the heterogeneous networks. Different quantization techniques have been employed to reduce the feedback overhead. However, the system performance cannot increase linearly with the number of bits increasing exponentially. Since optimizing the total number of bits is too complex for the entire network, an initial step is performed to distribute the bits to each cell in the conventional method. Then, the distributed bits are further allocated to each channel optimally. In order to enable direct allocation for the entire network, a FC-DNN based method is presented in this study. The optimized number of bits can be directly obtained for a different number of bits and scenarios by the proposed approach. The simulations are performed by using various scenarios with different allocation schemes. The performance results show that the DNN based method achieves a closer performance to the conventional approach. (C) 2021 Elsevier B.V. All rights reserved.
  • Book
    Citation - Scopus: 17
    Feedback Strategies for Wireless Communication
    (Springer, 2014) Özbek, Berna; Le Ruyet, Didier
    This book explores the different strategies regarding limited feedback information. The book analyzes the impact of quantization and the delay of CSI on the performance. The author shows the effect of the reduced feedback information and gives an overview about the feedback strategies in the standards. This volume presents theoretical analysis as well as practical algorithms for the required feedback information at the base stations to perform adaptive resource algorithms efficiently and mitigate interference coming from other cells. © 2014 Springer Science+Business Media New York. All rights are reserved.
  • Article
    Citation - WoS: 16
    Citation - Scopus: 23
    Energy Efficient Resource Allocation for Underlaying Multi-D2d Enabled Multiple-Antennas Communications
    (Institute of Electrical and Electronics Engineers Inc., 2020) Özbek, Berna; Pischella, M.; Le Ruyet, Didier
    Energy efficiency has a significant importance to optimize the wireless communications systems by providing high data rates. In order to develop energy efficient systems, one of the promising methods is to use multiple device-to-device (D2D) underlaying multiple antenna cellular systems. The interference from cellular users to D2D pairs, the interference between D2D pairs and the interference at the base station (BS) caused by D2D pairs occur in these communications systems. In this article, we propose energy efficient resource allocation algorithms for underlaying multi-D2D enabled multiple-antennas communications by employing different multiple antenna processing techniques at the BS. A joint method based on Dinkelbach algorithm and Message Passing Algorithm (MPA) and an approach based on deep learning with multi-layer artificial neural network are proposed to maximize the global energy efficiency (GEE) while satisfying the data rate requirements of both cellular users and D2D pairs. In MPA, the factor graph of the D2D pairs is constructed by taking into account the interference among the D2D pairs and the interference level at the BS to avoid any interruption in the cellular transmission. By relying on the training based on the proposed joint algorithm, a deep neural network approach is presented for off-line implementation. The performance results of the proposed energy efficient resource allocation algorithms show the superiority of multi-D2D communications over conventional single-D2D communications. © 1967-2012 IEEE.