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Now showing 1 - 3 of 3
  • Article
    Citation - WoS: 5
    Citation - Scopus: 10
    Quality of Service Assessment: a Case Study on Performance Benchmarking of Cellular Network Operators in Turkey
    (Tubitak Scientific & Technological Research Council Turkey, 2015) Kadioglu, Rana; Dalveren, Yaser; Dalveren, Yaser; Kara, Ali; Kara, Ali; Dalveren, Yaser; Kara, Ali; Department of Electrical & Electronics Engineering; Department of Electrical & Electronics Engineering
    This paper presents findings on performance benchmarking of cellular network operators in Turkey. Benchmarking is based on measurements of standard key performance indicators (KPIs) in one of the metropolitan cities of Turkey, Ankara. Performance benchmarking is formulated by incorporating customer perception by conducting surveys on how important KPIs are from the user's point of view. KPIs are measured, with standard test equipment, by drive test method on specified routes. According to the performance benchmarking results, the GSM and UMTS network operators achieving the best performance were determined in Ankara. Speech qualities of network operators, as the most popular service, were also evaluated by several statistical methods including pdf/cdf analysis and chi-square and Fisher's exact tests. The network operator providing the highest speech quality in Ankara was determined with the methods applied. Overall, the results and approaches on benchmarking of cellular networks in Turkey are reported for the first time in this paper. The approaches proposed in this paper could be adapted to wide-scale benchmarking of services in cellular networks.
  • Article
    Citation - WoS: 27
    Citation - Scopus: 35
    A Wavelet-Based Feature Set for Recognizing Pulse Repetition Interval Modulation Patterns
    (Tubitak Scientific & Technological Research Council Turkey, 2016) Gencol, Kenan; At, Nuray; Kara, Ali
    This paper presents a new feature set for the problem of recognizing pulse repetition interval (PRI) modulation patterns. The recognition is based upon the features extracted from the multiresolution decomposition of different types of PRI modulated sequences. Special emphasis is placed on the recognition of jittered and stagger type PRI sequences due to the fact that these types of PRI sequences appear predominantly in modern electronic warfare environments for some specific mission requirements and recognition of them is heavily based on histogram features. We test our method with a broad range of PRI modulation parameters. Simulation results show that the proposed feature set is highly robust and separates jittered, stagger, and other modulation patterns very well. Especially for the stagger type of PRI sequences, wavelet-based features outperform conventional histogram-based features. Advantages of the proposed feature set along with its robustness criteria are analyzed in detail.
  • Article
    ISAR Imaging of Drone Swarms at 77 GHz
    (Tubitak Scientific & Technological Research Council Turkey, 2025) Coruk, Remziye Busra; Kara, Ali; Aydin, Elif
    The proliferation of easily available, internet-purchased drones, coupled with the emergence of coordinated drone swarms, poses a significant security threat for airspace. Detecting these swarms is crucial to prevent potential accidents, criminal misuse, and airspace disruptions. This paper proposes a novel inverse synthetic aperture radar (ISAR) imaging technique for high-resolution reconstruction of drone swarms at 77 GHz millimeter wave (mmWave) frequency, offering a valuable tool for military and defense antidrone systems. The key parameters affecting down-range and cross-range resolution (0.05 m), ultimately enabling the generation of detailed ISAR images are discussed. Here, we create diverse scenarios encompassing various swarm formations, sizes, and payload configurations by employing ANSYS simulations. To enhance image quality, different window functions are evaluated, and the Hamming window is selected due to its highest peak signal-to-noise ratio (PSNR) (16.3645) and structural similarity (SSIM) (0.9067) values, ensuring superior noise reduction and structural preservation. The results demonstrate that the effectiveness of high-resolution ISAR imaging in accurately detecting and characterizing drone swarms pave the way for enhanced airspace security measures.