Researcher:
Altun, Ufuk

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Ufuk

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Altun

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Altun, Ufuk

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2021 - 20225

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    Reactive jammer detection in OFDM with index modulation
    (Elsevier B.V., 2022) Kaplan, Ahmet; Kurt, Gunes Karabulut; Altunbas, Ibrahim; Kucukyavuz, Defne; Kesal, Mustafa; Department of Electrical and Electronics Engineering; Başar, Ertuğrul; Altun, Ufuk; Faculty Member; PhD Student; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 149116; N/A
    Detection of jamming attacks is an important tool to improve the resource efficiency of jammer resilient communication networks. Detecting reactive jammers is especially difficult since the attacker is cognitive and focuses only on the used channels. Orthogonal frequency division multiplexing with index modulation (OFDM-IM) consists of active and passive subcarriers. Only active subcarriers carry modulated signals while passive subcarriers are left unused. In OFDM-IM systems, information bits are also dynamically embedded in the indices of these active subcarriers. As a result, remaining passive subcarriers cause instantaneously changing and unused holes in the spectrum that a reactive jammer cannot escape from attacking. In this paper, we propose an OFDM-IM-based detection scheme to improve the detection performance against reactive jammers. The proposed method exploits the dynamically changing empty OFDM-IM subcarriers to improve detection performance. A detection mechanism that is based on the variance of received signals is considered to identify the jammed subcarriers reliably and with low complexity. We assumed a destructive and elusive reactive jammer model that applies a zero-mean Gaussian jamming signal to the occupied channels. The performance of the variance detector is investigated analytically for OFDM-IM and OFDM-based systems under the given jammer model. The results showed that passive subcarriers of OFDM-IM inherently provide a better detection performance compared to the classical OFDM. Lastly, the analytical results are verified via simulations against both full-band and partial-band reactive jammers. Also, the effect of noise and the jamming power on the detection performance is investigated via extensive simulations. © 2022 Elsevier B.V.
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    Scalable secret key generation for wireless sensor networks
    (IEEE-Inst Electrical Electronics Engineers Inc, 2022) Başaran, Semiha T.; Kurt, Güneş Karabulut; Özdemir, Enver; Department of Electrical and Electronics Engineering; Altun, Ufuk; PhD Student; Department of Electrical and Electronics Engineering; College of Engineering; N/A
    Future sensor networks require energy and bandwidth efficient designs to support the growing number of nodes. The security aspect is often neglected due to the extra computational burden imposed on the sensor nodes. In this article, we propose a secret key generation method for wireless sensor networks by using the physical layer features. This key generation method is based on the superposition property of wireless channels. The proposed method exploits the multiple access property of the wireless channel with simultaneous transmissions as in the analog function computation technique to solve the latency and scarce bandwidth problems of highly populated dense networks. All nodes use the same time and frequency block to provide scalability that is linearly proportional to the number of nodes. The proposed method also benefits from the network density to provide security against eavesdroppers that aim to sniff the secret key from the channel. The security of the proposed method against eavesdroppers is analytically studied. Moreover, their application in multiple layers is investigated. The presented results have shown that there is a tradeoff between the total power consumption and total used bandwidth for secret key generation. Lastly, the error probability of the generated keys due to thermal noise and channel estimation error is investigated with computer simulations and compared with broadcasting-based benchmark model.
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    The magic of superposition: a survey on simultaneous transmission based wireless systems
    (2022) Kurt, Güneş Karabulut; Özdemir, Enver; Department of Electrical and Electronics Engineering; Altun, Ufuk; PhD Student; Department of Electrical and Electronics Engineering; College of Engineering; N/A
    In conventional communication systems, any interference between two communicating points is regarded as unwanted noise since it distorts the received signals. On the other hand, allowing simultaneous transmission and intentionally accepting the superposition of signals and even benefiting from it have been considered for a range of wireless applications. As prominent examples, non-orthogonal multiple access (NOMA), joint source-channel coding, and the computation codes are designed to exploit this scenario. They also inspired many other fundamental works from network coding to consensus algorithms. Especially, federated learning is an emerging technology that can be applied to distributed machine learning networks by allowing simultaneous transmission. Although various simultaneous transmission applications exist independently in the literature, their main contributions are all based on the same principle; the superposition property. In this survey, we aim to emphasize the connections between these studies and provide a guide for the readers on the wireless communication techniques that benefit from the superposition of signals. We classify the existing literature depending on their purpose and application area and present their contributions. The survey shows that simultaneous transmission can bring scalability, security, lowlatency, low-complexity and energy efficiency for certain distributed wireless scenarios which are inevitable with the emerging wireless technologies.
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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
    RIS enabled secure communication with covert constraint
    (Institute of Electrical and Electronics Engineers (IEEE), 2021) Department of Electrical and Electronics Engineering; Başar, Ertuğrul; Altun, Ufuk; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 149116; N/A
    Reconfigurable intelligent surface (RIS)-empowered communication is an emerging technology that is able to effectively reshape the wireless environment into the desired form. This promising technology appears as a remedy for a wide range of wireless applications including physical layer (PHY) security. In this paper, we consider the use of RISs for a challenging PHY security scenario with two kinds of adversaries, where a warden aims to detect and an eavesdropper aims to sniff the legitimate communication. Our objective is to maximize the secrecy rate under a covert constraint. For this purpose, a sub-optimal optimization algorithm is proposed where transmit beamforming and the RIS phase shift vectors are alternately optimized. The secrecy rate performance of the proposed algorithm is investigated with computer simulations for Rician fading channels. Our results indicate that the use of RISs significantly improves the secure communication rate of a wireless system without waking the warden.