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Department: search.filters.department.Department of EconomicsSubject: search.filters.subject.Telecommunications

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    DRX and QoS-aware energy-efficient uplink scheduling for long term evolution
    (IEEE, 2013) Koç, Ali T.; N/A; Department of Economics; Department of Electrical and Electronics Engineering; Ergül, Özgür; Yılmaz, Özgür; Akan, Özgür Barış; PhD Student; Faculty Member; Faculty Member; Department of Economics; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Administrative Sciences and Economics; College of Engineering; 156793; 108638; 6647
    Discontinuous reception (DRX) is supported in 3GPP Long Term Evolution (LTE) to reduce power consumption of user equipments (UEs). Power conservation achieved via DRX can be further increased with a packet scheduler that takes DRX states into consideration. Thus, in addition to quality of service (QoS) and fairness factors, which have been the main focus so far in scheduler design, energy efficiency must also be considered in scheduling. In this paper, we introduce a DRX and QoS-aware uplink packet scheduling algorithm (DQEPS) for LTE networks. One of the main reasons of poor DRX utilization is the continuous uplink packet traffic generated by applications working in the background. Accordingly, we first lay out the cumulative distribution functions (CDF) of interpacket arrival durations constructed by inspecting uplink packet transmission for various applications. Then, we form metrics for each bearer using these CDFs along with the DRX states, QoS parameters, channel conditions, and the buffer status of the bearers. Using these metrics, we develop a scheduling algorithm for the uplink, which aims to maximize power conservation of DRX mechanism by scheduling packets in a way that tries to minimize on duration, while meeting the QoS requirements. Performance evaluations indicate that DQEPS reduces power consumption significantly compared to the previously proposed methods for LTE.
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    Removal of ocular artifacts in EEG signals measured in a neuroeconomics experiment
    (IEEE, 2017) Kazanc, Mehmet Emin; Kahya, Yasemin; Guclu, Burak; Department of Economics; Ertaç, Seda; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; 107102
    In neuroeconomics experiments many ocular artifacts are encountered during long trial durations. In this study, results from algorithms used to remove artifacts in EEG measurements are presented. The study consists of three parts. In the first part, EEG signals were band-pass filtered to remove high frequency noise and low frequency drift. Next, the artifacts were removed by using traditional regression method and independent component analysis (ICA). Finally, the performances of the two artifact removal methods were compared. Although artifacts were suppressed better by ICA than regression, ICA caused decrease in root mean square (RMS) values of the non-artifactual parts of some channels.
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    Removal of ocular artifacts in EEG signals measured in a neuroeconomics experiment
    (Institute of Electrical and Electronics Engineers (IEEE), 2017) Kazanc, Mehmet Emin; Kahya, Yasemin; Guclu, Burak; Department of Economics; Ertaç, Seda; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; 107102
    In neuroeconomics experiments many ocular artifacts are encountered during long trial durations. In this study, results from algorithms used to remove artifacts in EEG measurements are presented. The study consists of three parts. In the first part, EEG signals were band-pass filtered to remove high frequency noise and low frequency drift. Next, the artifacts were removed by using traditional regression method and independent component analysis (ICA). Finally, the performances of the two artifact removal methods were compared. Although artifacts were suppressed better by ICA than regression, ICA caused decrease in root mean square (RMS) values of the non-artifactual parts of some channels. /Öz: Nöroekonomi deneylerinde EEG kayıt süreleri çok uzayabildiğinden işaretlerde ciddi göz artifaktları oluşmaktadır. Bu bildiride EEG ölçümlerinde karşılaşılan göz artifaktlarının giderilmesi amacıyla kullanılan algoritma ve sonuçlardan bahsedilmiştir. Yapılan çalışma üç bölümden oluşmaktadır. Birinci kısımda EEG işaretleri süzgeçten geçirilmiş, sonraki kısımda regresyon ve bağımsız bileşen analizi (BBA) kullanılarak artifakt- lar temizlenmi¸stir. Sonuç kısmında ise iki yöntemin performansları kar¸sıla¸stırılmı¸stır. Artifakt olan kısımlar BBA kullanılarak daha iyi temizlenmiş olmasına rağmen, bazı kanalların artifakt olmayan kısımlarındaki işaretlerin etkin değerlerinde azalma görülmüştür.