Doktora Tezleri

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/7776

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Browsing Doktora Tezleri by Department "Enstitüler, Lisansüstü Eğitim Enstitüsü, Elektronik Mühendisliği Ana Bilim Dalı"

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    Doctoral Thesis
    Low Energy Fixed Clustering Algorithm for Wireless Sensor Networks
    (Kadir Has Üniversitesi, 2016) Cengiz, Korhan; Dağ, Tamer
    Wireless sensor networks (WSNs) have become an important part of our lives as they can be used in vast application areas from disaster relief to health care. As a consequence the life span and the energy consumption of a WSN has become a challenging research area. According to the existing studies instead of using direct transmission or multi-hop routing clustering can significantly reduce the energy consumption of sensor nodes and can prolong the lifetime of a WSN. in this thesis low energy fixed clustering algorithm (LEFCA) and multihop low energy fixed clustering algorithm (M-LEFCA) are proposed for WSNs. With LEFCA the clusters are constructed during the set-up phase. A sensor node which becomes a member of a cluster stays in the same cluster throughout the life span of the network. LEFCA not only improves the lifetime of the network but also decreases the energy dissipation significantly. in addition proposed M-LEFCA uses multi-hop intra cluster communication approach. it selects optimum forward neighbor cluster heads (CHs) as relay nodes (RNs). M-LEFCA aims to reduce energy dissipation and prolong network lifetime of LEFCA by combining clustering and multi-hop routing approaches.
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    Doctoral Thesis
    Multi-sensor indoor positioning
    (Kadir Has Üniversitesi, 2022) AYABAKAN, TARIK; Kerestecioglu, Feza
    In this study, multi-sensor indoor positioning methods, which fuse the tri-laterated position data of the target are considered. The lateration is based on the dis tances that are obtained using the signal strengths received from different Wi-Fi access points. A new method, which is based on federated Kalman filtering (FKF) and makes use of the fingerprint data, namely, federated Kalman filter with skipped covariance updating (FKF-SCU) is proposed for indoor positioning. After that chal lenging issue of FKF, information sharing coefficient assignment is studied and two online adaptation methods based on received signal strength indication (RSSI) and distance information gathered from APs are proposed. Lastly, FKF-SCU structure is combined with adaptive FKF configuration. The data collected on two different test beds are used to compare the performance of the proposed positioning methods to those of the regular federated and centralized filters. It is shown on the test data that these algorithms improve the position accuracy and provide fault tolerance whenever signal reception is interrupted from an access point.
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    Doctoral Thesis
    Performance Analysis of Low Complexity Maximal Ratio Transmission Approaches in Multi-Relay Networks
    (Kadir Has Üniversitesi, 2014) Erdoğan, Eylem; Güçlüoğlu, Tansal; Dağ, Tamer
    Kablosuz ileti sim a ğlarının artan talebi karşılamak için yüksek veri hızına sahip, yüksek güvenilirlikli ve düşük enerji tüketimli olması gerekmektedir. Bu nedenle, bu doktora tezi düşük karmaşıklığa sahip kuvvetlendir-aktar yapısındaki tek yönlü ve iki yönlü çok antenli ve çok röleli sistemlerin uygulama ve analizlerini sunmaktadır. İlk olarak, iki atamalı maksimum oranlı iletim tekniği kullanılan geleneksek ve fırsatçı yapıdaki çok röleli sistemlerin performansı Rayleigh sönümlemeli kanallarda incelenmektedir. Analiz, kümülatif dağılım fonksiyonu ve moment üreten fonksiyon gibi sinyal-gürültü oranına ait istatistiksel fonksiyonların türetimi ile başlamaktadır. Sonrasında, sembol hata oranı, kesinti olasılığı ve ergodik kapasite bulunmaktadır. İkinci çalışmada maksimum oranlı iletim tekniği ve röle seçimini içeren iki yönlü röleli ağ modeli üzerinde durulmaktadır. Bu model için, toplam sembol hata oranı ve sistem kesinti olasılığı Nakagami-m sönümlemeli kanallarda türetilmektedir. Son olarak, iki yönlü röleli ağ modeli anten ve röle seçimiyle beraber Nakagami-m sönümlemeli kanallarda analiz edilmekte ve sistem kesinti olasılığı elde edilmektedir.
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    Doctoral Thesis
    Sparse Channel Estimation and Data Detection Algorithms for Ofdm-Based Underwater Acoustic Communication Systems
    (Kadir Has Üniversitesi, 2018) Altabbaa, Mhd Tahssin; Panayırcı, Erdal
    Communication over acoustic signals in underwater results into a multi-scale multilag channels which occurs due to the multipath propagation. Hence a robust channel estimation technique has to be present at the receiver and the solutions of the terrestrial-based systems are not applicable. in this work using path-based channel model that characterizes underwater channels by a delay a Doppler shift and an attenuation factors three new pilot assisted time domain-based channel estimation algorithms are proposed for single-input single-output communicationbased and diversity communication-based underwater acoustic systems. The multicarrier transmission technique assumed is OFDM. in addition depending on the base stations deployment in underwater the sparse underwater channels undergo Rician or Rayleigh fading where channels in this work are generated using Bellhop software. in the first two proposed approach the overall sparse channel tap delays and constant Doppler shifts are estimated using Matching Pursuit and Orthogonal Matching Pursuit algorithms where the sparse complex channel path gain vector is estimated by maximum a posteriori probability (MAP) technique and the prior densities of the channel gains follow Rician distribution with unknown mean and variance vectors where Maximum Likelihood is proposed for their estimation. The first approach considers a colored noise and uniform Doppler spread and the second approach considers a non-uniform Doppler shifts with white noise. The third proposed approach considers transmitter diversity with Alamouti’s coding where the channel estimator iteratively estimates the complex channel parameters of each subcarrier using the expectation maximization method which in turn converges to a true maximum a posteriori probability estimation of the unknown channel where Karhunen-Loeve expansion and ESPRiT algorithm are assumed for complexity reduction and delay estimation respectively. Finally in ii order to assess the performance of the proposed algorithms the computer simulations show the behavior in terms of mean square error and symbol error rate.