Researcher:
Özpoyraz, Burak

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Master Student

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Burak

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Özpoyraz

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Özpoyraz, Burak

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2021 - 20222

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Researcher Of Publications: search.filters.isAuthorOfPublication.dd3211d9-c0a5-47d3-9cbd-6b88d23d1a6c

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    PublicationOpen Access
    Deep learning-aided 6G wireless networks: a comprehensive survey of revolutionary PHY architectures
    (Institute of Electrical and Electronics Engineers (IEEE), 2022) Department of Electrical and Electronics Engineering; Başar, Ertuğrul; Özpoyraz, Burak; Doğukan, Ali Tuğberk; Gevez, Yarkın; Altun, Ufuk; Faculty Member; Master Student; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; 149116; N/A; N/A; N/A; N/A
    Deep learning (DL) has proven its unprecedented success in diverse fields such as computer vision, natural language processing, and speech recognition by its strong representation ability and ease of computation. As we move forward to a thoroughly intelligent society with 6G wireless networks, new applications and use cases have been emerging with stringent requirements for next-generation wireless communications. Therefore, recent studies have focused on the potential of DL approaches in satisfying these rigorous needs and overcoming the deficiencies of existing model-based techniques. The main objective of this article is to unveil the state-of-the-art advancements in the field of DL-based physical layer methods to pave the way for fascinating applications of 6G. In particular, we have focused our attention on four promising physical layer concepts foreseen to dominate next-generation communications, namely massive multiple-input multiple-output systems, sophisticated multi-carrier waveform designs, reconfigurable intelligent surface-empowered communications, and physical layer security. We examine up-to-date developments in DL-based techniques, provide comparisons with state-of-the-art methods, and introduce a comprehensive guide for future directions. We also present an overview of the underlying concepts of DL, along with the theoretical background of well-known DL techniques. Furthermore, this article provides programming examples for a number of DL techniques and the implementation of a DL-based multiple-input multiple-output by sharing user-friendly code snippets, which might be useful for interested readers.
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    PublicationOpen Access
    Index modulation based coordinate interleaved orthogonal design for secure communications
    (Institute of Electrical and Electronics Engineers (IEEE), 2021) Yıldırım, İbrahim; Department of Electrical and Electronics Engineering; Başar, Ertuğrul; Özpoyraz, Burak; Faculty Member; Master Student; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 149116; N/A
    In this paper, we propose a physical layer security scheme that exploits a novel index modulation (IM) technique for coordinate interleaved orthogonal designs (CIOD). Utilizing the diversity gain of CIOD transmission, the proposed scheme, named CIOD-IM, provides an improved spectral efficiency by means of IM. In order to provide a satisfactory secrecy rate, we design a particular artificial noise matrix, which does not affect the performance of the legitimate receiver, while deteriorating the performance of the eavesdropper. We derive expressions of the ergodic secrecy rate and the theoretical bit error rate upper bound. In addition, we analyze the case of imperfect channel estimation by taking practical concerns into consideration. It is shown via computer simulations that the proposed scheme outperforms the existing IM-based schemes and might be a candidate for future secure communication systems.