Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Subject: search.filters.subject.Electromagnetic waves

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  • Article
    Citation - Scopus: 5
    Event Distortion-Based Clustering Algorithm for Energy Harvesting Wireless Sensor Networks
    (Springer, 2022) Al-Qamaji, A.; Atakan, B.
    Wireless sensor networks (WSNs) consist of compact deployed sensor nodes which collectively report their sensed readings about an event to the Base Station (BS). In WSNs, due to the dense deployment, sensor readings can be spatially correlated and it is nonessential to transmit all their readings to the BS. Therefore, for more energy efficient, it is vital to choose which sensor node should report their sensed readings to the BS. In this paper, the event distortion-based clustering (EDC) algorithm is proposed for the spatially correlated sensor nodes. Here, the sensor nodes are assumed to harvest energy from ambient electromagnetic radiation source. The EDC algorithm allows the energy-harvesting sensor nodes to select and eliminate nonessential nodes while maintain an acceptable level of distortion at the BS. To measure the reliability, a theoretical framework of the distortion function is first derived for both single-hop and two-hop communication scenarios. Then, based on the derived theoretical framework, the EDC algorithm is introduced. Through extensive simulations, the performance of the EDC algorithm is evaluated in terms of achievable distortion level, number of alive nodes and harvested energy levels. As a result, EDC algorithm can successfully exploit both the spatial correlation and energy harvesting to improve the energy efficiency while preserving an acceptable level of distortion. Furthermore, the performance comparisons reveal that the two-hop communication model outperforms the single-hop model in terms of the distortion and energy-efficiency. © 2021, The Author(s).
  • Article
    Citation - WoS: 134
    Citation - Scopus: 136
    Electrically Switchable Metadevices Via Graphene
    (American Association for the Advancement of Science, 2018) Balcı, Osman; Kakenov, Nurbek; Karademir, Ertuğrul; Balcı, Sinan; Çakmakyapan, Semih; Polat, Emre O.; Çağlayan, Hümeyra; Özbay, Ekmel; Kocabaş, Çoşkun
    Metamaterials bring subwavelength resonating structures together to overcome the limitations of conventional materials. The realization of active metadevices has been an outstanding challenge that requires electrically reconfigurable components operating over a broad spectrum with a wide dynamic range. However, the existing capability of metamaterials is not sufficient to realize this goal. By integrating passive metamaterials with active graphene devices, we demonstrate a new class of electrically controlled active metadevices working in microwave frequencies. The fabricated active metadevices enable efficient control of both amplitude (>50 dB) and phase (>90°) of electromagnetic waves. In this hybrid system, graphene operates as a tunable Drude metal that controls the radiation of the passive metamaterials. Furthermore, by integrating individually addressable arrays of metadevices, we demonstrate a new class of spatially varying digital metasurfaces where the local dielectric constant can be reconfigured with applied bias voltages. In addition, we reconfigure resonance frequency of split-ring resonators without changing its amplitude by damping one of the two coupled metasurfaces via graphene. Our approach is general enough to implement various metamaterial systems that could yield new applications ranging from electrically switchable cloaking devices to adaptive camouflage systems.