Bildiri Koleksiyonu | Elektrik-Elektronik Mühendisliği Bölümü / Department of Electrical-Electronics Engineering
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Öğe Resource allocation in the finite blocklength regime under PAoI and delay violation constraints(IEEE, 2023-08-27) Kartal, Özkan Tuğberk; Kaya, Onur; Uysal, ElifURLLC (Ultra-reliable low-latency communication) is one of the more challenging modes for 5G for resource allocation (RA). Most of the previous studies for RA for wireless access in URLLC assumed known packet arrival processes, and focused on maximizing average rates or throughput. The objective of this paper is to present a formulation of allocating resource blocks, modulation and coding rates to multiple short packet machine-type information flows to provide information age and delay violation guarantees. The scenario is motivated by the scheduling of URLLC flows among users served by a common 5G base station. The problem involves the selections of frequency allocation policy and modulation and coding scheme (MCS) under estimated CSI. Moreover, the sensitivity of the information packet size on the choice of modulation and coding parameters as well as the number of resource blocks and the choice of the number of pilot symbols is demonstrated. The results of this formulation are compared with resource allocation algorithms in the literature.Öğe Optimizing indoor localization accuracy with neural network performance metrics and software-defined IEEE 802.11az Wi-Fi set-up(IEEE, 2023-10-28) Kouhalvandi, Lida; Aygün, Sercan; Matekovits, Ladislau; Miramirkhani, FarshadAccurately classifying regions based on Wi-Fi signals can be a difficult task, especially when considering different frequency values. In this study, we aimed to improve the accuracy of indoor localization by developing a novel approach that does not rely on pre-trained models. To achieve this, fingerprints from the IEEE 802.11az standard were randomly selected, and the data samples were trained using parameterized station characteristics and neural network hyperparameters. The impact of each parameter on the localization accuracy was measured, and performance monitoring metrics such as F1-Measure and confusion matrix-based metrics were evaluated. Furthermore, the Thompson sampling (TS) algorithm was employed to determine the optimal parameters, which helped to achieve the best possible accuracy. The proposed approach demonstrated improved accuracy in region localization compared to conventional heuristic approaches which typically yield an accuracy range of 65% to 77%. The proposed approach achieved up to 80% accuracy in region localization and could be a promising solution for indoor localization in various settings.Öğe Electromagnetic imaging of rough dielectric surface profiles using a single-frequency reverse time migration method(IEEE, 2023-07) Sefer, Ahmet; Yapar, Ali; Bağcı, HakanAn electromagnetic imaging scheme, which makes use of a single-frequency reverse time migration (RTM) technique to reconstruct two-dimensional (2D) rough surface profiles from the scattered field data, is formulated and implemented. The unknown surface profile, which is expressed as a one-dimensional height function, is the interface between two dielectric media. It is assumed that the profile is illuminated from one side and the scattered fields are “measured” along a line on this same side. RTM is used to construct a cross-correlation imaging functional that is numerically evaluated to yield an image of the investigation domain. The maxima of this functional yields an accurate reconstruction of the rough dielectric surface profile.Öğe Optimization of inverse problems involving surface reconstruction: least squares application(Institute of Electrical and Electronics Engineers Inc., 2022) Sefer, AhmetThis article addresses the least-squares method, which is vital in inverse scattering problems involving the reconstruction of inaccessible rough surface profiles from the measured scattered field data. The unknown surface profile is retrieved by a regularized recursive Newton algorithm which is regularized by the Tikhonov method. The importance of the least-squares application reveals at this point, where the unknown surface profile is expressed as a linear combination of some appropriate basis functions. Thus, the problem of obtaining the unknown rough surface is reduced to finding the unknown coefficients of these functions. As an optimization problem, the choice of appropriate basis functions, as well as the number of their expansions for rough surface imaging problems are essential for the iterative solutions. The validation limits and the performances of different basis functions are presented via several numerical examples.
