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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6
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Publication Open Access Large-scale computational screening of MOF membranes and MOF-based polymer membranes for H2/N2 separations(American Chemical Society (ACS), 2019) Department of Chemical and Biological Engineering; Azar, Ayda Nemati Vesali; Velioğlu, Sadiye; Keskin, Seda; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; N/A; 200650; 40548Several thousands of metal organic frameworks (MOFs) have been reported to date, but the information on H-2/N-2 separation performances of MOF membranes is currently very limited in the literature. We report the first large-scale computational screening study that combines state-of-the-art molecular simulations, grand canonical Monte Carlo (GCMC) and molecular dynamics (MD), to predict H-2 permeability and H-2/N-2 selectivity of 3765 different types of MOF membranes. Results showed that MOF membranes offer very high H-2 permeabilities, 2.5 x 10(3) to 1.7 x 10(6) Barrer, and moderate H-2/N-2 membrane selectivities up to 7. The top 20 MOF membranes that exceed the polymeric membranes' upper bound for H-2/N-2 separation were identified based on the results of initial screening performed at infinite dilution condition. Molecular simulations were then carried out considering binary H-2/N-2 and quaternary H-2/N-2/CO2/CO mixtures to evaluate the separation performance of MOF membranes under industrial operating conditions. Lower H-2 permeabilities and higher N-2 permeabilities were obtained at binary mixture conditions compared to the ones obtained at infinite dilution due to the absence of multicomponent mixture effects in the latter. Structure performance relations of MOFs were also explored to provide molecular-level insights into the development of new MOF membranes that can offer both high H-2 permeability and high H-2/N-2 selectivity. Results showed that the most promising MOF membranes generally have large pore sizes (>6 A) as well as high surface areas (>3500 m(2)/g) and high pore volumes (>1 cm(3)/g). We finally examined H-2/N-2 separation potentials of the mixed matrix membranes (MMMs) in which the best MOF materials identified from our high-throughput screening were used as fillers in various polymers. Results showed that incorporation of MOFs into polymers almost doubles H-2 permeabilities and slightly enhances H-2/N-2 selectivities of polymer membranes, which can advance the current membrane technology for efficient H-2 purification.Publication Open Access Uplink achievable rate maximization for reconfigurable intelligent surface aided millimeter wave systems with resolution-adaptive ADCs(Institute of Electrical and Electronics Engineers (IEEE), 2021) Xiu, Yue; Zhao, Jun; Di Renzo, Marco; Sun, Wei; Gui, Guan; Wei, Ning; Department of Electrical and Electronics Engineering; Başar, Ertuğrul; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 149116In this letter, we investigate the uplink of a reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) multi-user system. In the considered system, however, problems with hardware cost and power consumption arise when massive antenna arrays coupled with power-demanding analog-todigital converters (ADCs) are employed. To account for practical hardware complexity, we consider that the access point (AP) is equipped with resolution-adaptive analog-to-digital converters (RADCs). We maximize the achievable rate under hardware constraints by jointly optimizing the ADC quantization bits, the RIS phase shifts, and the beam selection matrix. The formulated problem is non-convex. To efficiently tackle this problem, a block coordinated descent (BCD)-based algorithm is proposed. Simulations demonstrate that an RIS can mitigate the hardware loss due to the use of RADCs, and that the proposed BCD-based algorithm outperforms state-of-the-art algorithms.Publication Open Access On the maximum coverage area of wireless networked control systems with maximum cost-efficiency under convergence constraint(Institute of Electrical and Electronics Engineers (IEEE), 2015) Kılınç, Deniz; Özger, Mustafa; Akan, Özgür Barış; PhD Student; College of EngineeringThe integration of wireless communication and control systems revealed wireless networked control systems (WNCSs). One fundamental problem in WNCSs is to have a wide coverage area. For the first time in the literature, we address this problem and we obtain the maximum coverage area by solving an optimization problem. In this technical note, we consider a WNCS where the output sensor measurements are transmitted over separate heterogeneous multi-hop wireless ad-hoc subnetworks. The observation process is divided into N parts and the system state is estimated using the Kalman filter. We present the critical arrival probability for a sensor measurement packet such that if the packet arrival probability is larger than the critical value, it is guaranteed that the estimator of the WNCS converges. We derive the maximum total coverage area of the heterogeneous wireless subnetworks having maximum cost-efficiency under the constraint of the convergence of the WNCS estimator.Publication Open Access Adaptive and cognitive communication architecture for next-generation PPDR systems(Institute of Electrical and Electronics Engineers (IEEE), 2016) Shah, Ghalib A.; Canberk, Berk; Ergül, Özgür; Akan, Özgür Barış; PhD Student; Faculty Member; College of EngineeringIn the light of the recent natural catastrophes and terrorist activities it has become evident that new architectural approaches are needed for the next generation Public Protection and Disaster Relief (PPDR) networks. These architectures should be adaptable to the conditions at the event site, resilient enough to operate under adverse conditions of the emergency. Furthermore, they should enable timely gathering of crucial event data and its delivery to the responder units at the site as well as the command and control centre that are off-site. In this paper, we first examine the state-of-the-art for areas related to communication in PPDR systems, and discuss the open research issues for each topic. Then, we propose a novel architecture that meets the aforementioned requirements which relies on a novel device called Intelligent Cognitive Gateway (ICG). ICG enables flexible use of the spectrum and facilitates data gathering from all lower tier devices and relays this data to the relevant units through the higher tier public or commercial backhaul networks. Finally, we provide some results that justify the need for these devices in emergency scenarios.Publication Open Access Super-mode OFDM with index modulation(Institute of Electrical and Electronics Engineers (IEEE), 2020) Department of Electrical and Electronics Engineering; Doğukan, Ali Tuğberk; Başar, Ertuğrul; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 149116Orthogonal frequency division multiplexing (OFDM) with index modulation (OFDM-IM) appears as a promising multi-carrier waveform candidate for beyond 5G due to its attractive advantages such as operational flexibility and ease of implementation. However, OFDM-IM may not be a proper choice for 5G services such as enhanced mobile broadband (eMBB) since achieving high data rates is challenging because of its null subcarriers. One solution to enhance the spectral efficiency of OFDM-IM is the employment of multiple distinguishable constellations (modes) by also exploiting its null subcarriers for data transmission. This article proposes a novel IM technique called super-mode OFDM-IM (SuM-OFDM-IM), where mode activation patterns (MAPs) and subcarrier activation patterns (SAPs) are jointly selected and conventional data symbols are repetition coded over multiple subcarriers to achieve a diversity gain. For the proposed scheme, a low-complexity detector is designed, theoretical analyses are performed and a bit error rate (BER) upper bound is derived. The performance of the proposed system is also investigated through real-time experiments using a software-defined radio (SDR) based prototype. We show that SuM-OFDM-IM exhibits promising results in terms of spectral efficiency and error performance; thus, appears as a potential candidate for 5G and beyond communication systems.Publication Open Access Fading correlation analysis in MIMO-OFDM troposcatter communications: space, frequency, angle and space-frequency diversity(Institute of Electrical and Electronics Engineers (IEEE), 2015) Dinç, Ergin; Akan, Özgür Barış; PhD Student; Faculty Member; College of EngineeringThe capacity gain of MIMO systems significantly depends on the fading correlation between antennas, and there is no analytical study which considers the fading correlation in the troposcatter communications. In this paper, we develop an analytical model, ring scatter model (RSM), to derive the fading correlation in the troposcatter systems as a function of spatial, frequency and angular separations for the first time in the literature. In addition, we compare the effects of the diversity techniques that are suitable for troposcatter communications: space, frequency, angle and space-frequency diversity techniques by deriving the distribution of their achievable data rates with transmit beam-forming. To this end, we extend our previously introduced troposcatter channel model [1] for the implementation of MIMO-OFDM and the diversity techniques.Publication Open Access Clustering in multi-channel cognitive radio ad hoc and sensor networks(Institute of Electrical and Electronics Engineers (IEEE), 2018) Alagöz, Fatih; Department of Electrical and Electronics Engineering; Özger, Mustafa; Akan, Özgür Barış; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and EngineeringCR enables dynamic spectrum access to utilize licensed spectrum when it is idle. CR technology is applied to wireless ad hoc and sensor networks to form CRAHNs and CRSNs, respectively. Clustering is an efficient topology management technique to regulate communication and allocate spectrum resources by CR capabilities of nodes in CRAHNs and CRSNs. In this article, we thoroughly investigate the benefits and functionalities of clustering such as topology, spectrum, and energy management in these networks. We also overview motivations for and challenges of clustering in CRAHNs and CRSNs. Existing clustering schemes are reviewed and compared. We conclude by revealing key considerations and possible solutions for spectrum-aware clustering in multi-channel CRAHNs and CRSNs.Publication Open Access A ray-based channel modeling approach for MIMO troposcatter beyond-line-of-sight (b-LoS) communications(Institute of Electrical and Electronics Engineers (IEEE), 2015) Dinç, Ergin; Akan, Özgür Barış; PhD Student; Faculty Member; College of EngineeringTroposcatter can be used as a communication medium for beyond-Line-of-Sight (b-LoS) links. However, available troposcatter channel models do not provide comprehensive channel modeling especially at high frequencies. Therefore, the main motivation of this study is to develop a ray-based MIMO troposcatter channel model to analyze transmission-loss characteristics, coherence bandwidth and correlation between antennas for the first time in the literature for troposcatter communications. In addition, the link budget calculations and the distribution of capacity in troposcatter links are provided by using real world water vapor mixing ratio measurements.Publication Open Access A fast, accurate, and separable method for fitting a Gaussian function(Institute of Electrical and Electronics Engineers (IEEE), 2019) Al-Nahhal Ibrahim; Dobre Octavia A.; Moloney Cecilia; Ikki Salama; Department of Electrical and Electronics Engineering; Başar, Ertuğrul; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 149116Publication Open Access Editorial: introduction to the issue on deep learning for image/video restoration and compression(Institute of Electrical and Electronics Engineers (IEEE), 2021) Covell, Michele; Timofte, Radu; Dong, Chao; Department of Electrical and Electronics Engineering; Tekalp, Ahmet Murat; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 26207The papers in this special issue focus on deep learning for image/video restoration and compression. The huge success of deep-learning-based approaches in computer vision has inspired research in learned solutions to classic image/video processing problems, such as denoising, deblurring, dehazing, deraining, super-resolution (SR), and compression. Hence, learning-based methods have emerged as a promising nonlinear signal-processing framework for image/ video restoration and compression. Recent works have shown that learned models can achieve significant performance gains, especially in terms of perceptual quality measures, over traditional methods. Hence, the state of the art in image restoration and compression is getting redefined. This special issue covers the state of the art in learned image/video restoration and compression to promote further progress in innovative architectures and training methods for effective and efficient networks for image/video restoration and compression.