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Articles 1321 - 1350 of 5273
Full-Text Articles in Computer Sciences
Off-Policy Q-Learning For Anti-Interference Control Of Multi-Player Systems, Jinna Li, Zhenfei Xiao, Tianyou Chai, Frank L. Lewis, Sarangapani Jagannathan
Off-Policy Q-Learning For Anti-Interference Control Of Multi-Player Systems, Jinna Li, Zhenfei Xiao, Tianyou Chai, Frank L. Lewis, Sarangapani Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This paper develops a novel off-policy game Q-learning algorithm to solve the anti-interference control problem for discrete-time linear multi-player systems using only data without requiring system matrices to be known. The primary contribution of this paper lies in that the Q-learning strategy employed in the proposed algorithm is implemented in an off-policy policy iteration approach other than on-policy learning due to the well-known advantages of off-policy Q-learning over on-policy Q-learning. All of the players work hard together for the goal of minimizing their common performance index meanwhile defeating the disturbance that tries to maximize the specific performance index, and finally …
Fault Identification On Electrical Transmission Lines Using Artificial Neural Networks, Christopher W. Asbery
Fault Identification On Electrical Transmission Lines Using Artificial Neural Networks, Christopher W. Asbery
Theses and Dissertations--Electrical and Computer Engineering
Transmission lines are designed to transport large amounts of electrical power from the point of generation to the point of consumption. Since transmission lines are built to span over long distances, they are frequently exposed to many different situations that can cause abnormal conditions known as electrical faults. Electrical faults, when isolated, can cripple the transmission system as power flows are directed around these faults therefore leading to other numerous potential issues such as thermal and voltage violations, customer interruptions, or cascading events. When faults occur, protection systems installed near the faulted transmission lines will isolate these faults from the …
Lung Cancer Subtype Differentiation From Positron Emission Tomography Images, Oğuzhan Ayyildiz, Zafer Aydin, Bülent Yilmaz, Seyhan Karaçavuş, Kübra Şenkaya, Semra İçer, Erdem Arzu Taşdemi̇r, Eser Kaya
Lung Cancer Subtype Differentiation From Positron Emission Tomography Images, Oğuzhan Ayyildiz, Zafer Aydin, Bülent Yilmaz, Seyhan Karaçavuş, Kübra Şenkaya, Semra İçer, Erdem Arzu Taşdemi̇r, Eser Kaya
Turkish Journal of Electrical Engineering and Computer Sciences
Lung cancer is one of the deadly cancer types, and almost 85 % of lung cancers are nonsmall cell lung cancer (NSCLC). In the present study we investigated classification and feature selection methods for the differentiation of two subtypes of NSCLC, namely adenocarcinoma (ADC) and squamous cell carcinoma (SqCC). The major advances in understanding the effects of therapy agents suggest that future targeted therapies will be increasingly subtype specific. We obtained positron emission tomography (PET) images of 93 patients with NSCLC, 39 of which had ADC while the rest had SqCC. Random walk segmentation was applied to delineate three-dimensional tumor …
On The Automorphisms And Isomorphisms Of Mds Matrices And Their Efficient Implementations, Muharrem Tolga Sakalli, Sedat Akleylek, Kemal Akkanat, Vincent Rijmen
On The Automorphisms And Isomorphisms Of Mds Matrices And Their Efficient Implementations, Muharrem Tolga Sakalli, Sedat Akleylek, Kemal Akkanat, Vincent Rijmen
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we explicitly define the automorphisms of MDS matrices over the same binary extension field. By extending this idea, we present the isomorphisms between MDS matrices over $\mathbb{F}_{2^{m}}$ and MDS matrices over $\mathbb{F}_{2^{mt}}$, where $t \ge 1$ and $m>1$, which preserves the software implementation properties in view of XOR operations and table lookups of any given MDS matrix over $\mathbb{F}_{2^{m}}$. Then we propose a novel method to obtain distinct functions related to these automorphisms and isomorphisms to be used in generating isomorphic MDS matrices (new MDS matrices in view of implementation properties) using the existing ones. The …
Wideband Patch Array Antenna Using Superstrate Configuration For Future 5gapplications, Sidra Farhat, Farzana Arshad, Yasar Amin, Jonathan Loo
Wideband Patch Array Antenna Using Superstrate Configuration For Future 5gapplications, Sidra Farhat, Farzana Arshad, Yasar Amin, Jonathan Loo
Turkish Journal of Electrical Engineering and Computer Sciences
In this work, four distinct antenna configurations for future-centric 5G applications are proposed. Initially, a single rectangular patch is designed to operate at the frequency of 28 GHz while maintaining a wide operational band. Performance of the antenna is improved by incorporating an array of identical rectangular elements resulting in a higher gain and wider bandwidth. The proposed arrangement consists of three rectangular elements realized using 0.508-mm thick Rogers RT/Duroid 5880 laminate. The bandwidth is further enhanced by increasing the number of radiating elements in the array from three to five. Evolution of the proposed design is concluded by stacking …
Revised Polyhedral Conic Functions Algorithm For Supervised Classification, Gürhan Ceylan, Gürkan Öztürk
Revised Polyhedral Conic Functions Algorithm For Supervised Classification, Gürhan Ceylan, Gürkan Öztürk
Turkish Journal of Electrical Engineering and Computer Sciences
In supervised classification, obtaining nonlinear separating functions from an algorithm is crucial for prediction accuracy. This paper analyzes the polyhedral conic functions (PCF) algorithm that generates nonlinear separating functions by only solving simple subproblems. Then, a revised version of the algorithm is developed that achieves better generalization and fast training while maintaining the simplicity and high prediction accuracy of the original PCF algorithm. This is accomplished by making the following modifications to the subproblem: extension of the objective function with a regularization term, relaxation of a hard constraint set and introduction of a new error term. Experimental results show that …
Power-Over-Tether Uas Leveraged For Nearly Indefinite Meteorological Data Acquisition In The Platte River Basin, Daniel Rico, Carrick Detweiler, Francisco Munoz-Arriola
Power-Over-Tether Uas Leveraged For Nearly Indefinite Meteorological Data Acquisition In The Platte River Basin, Daniel Rico, Carrick Detweiler, Francisco Munoz-Arriola
School of Computing: Conference and Workshop Papers
The integration of unmanned aerial systems (UASs) has increased in the field of agriculture. These systems can provide data that was previously difficult to obtain to help increase efficiency and production. Typical commercial off the shelf (COTS) UASs have significant limitations in the form of small payloads, and short flight times which inhibit their ability to provide significant quantities of useful data. We present the development of a novel power-over-tether UAS that leverages the physical presence of the tether to integrate sensors at multiple altitudes along the tether. The UAS can acquire data nearly indefinitely to sense atmospheric conditions and …
Pig Pose Estimation Based On Extracted Data Of Mask R-Cnn With Vgg Neural Network For Classifications, Sang Kwan Lee
Pig Pose Estimation Based On Extracted Data Of Mask R-Cnn With Vgg Neural Network For Classifications, Sang Kwan Lee
Electronic Theses and Dissertations
This paper proposes a pig pose estimation operating with Region Proposal Network (RPN) of Mask Region based Convolutional Neural Network (Mask R-CNN) and Visual Geometry Group (VGG) Neural Network (NN). Object pose estimations generates from the associations of different key points. Key points could be explained as specific location of an object such as different joints of a human body or joints of different object. Hourglass network is one of a NN delivering key points of an object. Associating the different key points with the hourglass network results could be represented as instance-level detection [3]. However, the instance-level detection shows …
Novel Computational Approaches For Multidimensional Brain Image Analysis, Harish Raviprakash
Novel Computational Approaches For Multidimensional Brain Image Analysis, Harish Raviprakash
Electronic Theses and Dissertations, 2020-2023
The overall goal of this dissertation is focused on addressing challenging problems in 1D, 2D/3D and 4D neuroimaging by developing novel algorithms that combine signal processing and machine learning techniques. One of these challenging tasks is the accurate localization of the eloquent language cortex in brain resection pre-surgery patients. This is especially important since inaccurate localization can lead to diminshed functionalities and thus, a poor quality of life for the patient. The first part of this dissertation addresses this problem in the case of drug-resistant epileptic patients. We propose a novel machine learning based algorithm to establish an alternate electrical …
Quantifying Seagrass Distribution In Coastal Water With Deep Learning Models, Daniel Perez, Kazi Islam, Victoria Hill, Richard Zimmerman, Blake Schaeffer, Yuzhong Shen, Jiang Li
Quantifying Seagrass Distribution In Coastal Water With Deep Learning Models, Daniel Perez, Kazi Islam, Victoria Hill, Richard Zimmerman, Blake Schaeffer, Yuzhong Shen, Jiang Li
OES Faculty Publications
Coastal ecosystems are critically affected by seagrass, both economically and ecologically. However, reliable seagrass distribution information is lacking in nearly all parts of the world because of the excessive costs associated with its assessment. In this paper, we develop two deep learning models for automatic seagrass distribution quantification based on 8-band satellite imagery. Specifically, we implemented a deep capsule network (DCN) and a deep convolutional neural network (CNN) to assess seagrass distribution through regression. The DCN model first determines whether seagrass is presented in the image through classification. Second, if seagrass is presented in the image, it quantifies the seagrass …
Cooperative Communications With Optimal Harvesting Duration For Nakagamifading Channels, Nadhir Ben Halima, Boujemaa Hatem
Cooperative Communications With Optimal Harvesting Duration For Nakagamifading Channels, Nadhir Ben Halima, Boujemaa Hatem
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we analyze the throughput of cooperative communications with wireless energy harvesting. Relay nodes harvest energy from Radio Frequency (RF) signal transmitted by the source. We derive the packet error probability as well as the throughput for Nakagami fading channels. We also suggest to enhance the throughput by choosing the value of harvesting duration. Our results are valid for both Amplify and Forward (AF) and Decode and Forward (DF) relaying.
Two Novel Radar Detectors For Spiky Sea Clutter With The Presence Of Thermal Noise And Interfering Targets, Nouh Guidoum, Faouzi Soltani, Amar Mezache
Two Novel Radar Detectors For Spiky Sea Clutter With The Presence Of Thermal Noise And Interfering Targets, Nouh Guidoum, Faouzi Soltani, Amar Mezache
Turkish Journal of Electrical Engineering and Computer Sciences
In the context of noncoherent detection and high-resolution maritime radar system with low grazing angle, new Constant False Alarm Rate (CFAR) decision rules are suggested for two Compound Gaussian (CG) clutters namely: The K distribution and the Compound Inverse Gaussian (CIG) distribution, which are considered among the most appropriate models for sea clutter. The proposed decision rules are then modified to deal with the presence of thermal noise and interfering targets. The proposed detectors are investigated on the basis of synthetic data as well as real data of the IPIX radar database. The obtained results exhibit a high probability of …
Detection Of Hand Osteoarthritis From Hand Radiographs Using Convolutionalneural Networks With Transfer Learning, Kemal Üreten, Hasan Erbay, Hadi̇ Hakan Maraş
Detection Of Hand Osteoarthritis From Hand Radiographs Using Convolutionalneural Networks With Transfer Learning, Kemal Üreten, Hasan Erbay, Hadi̇ Hakan Maraş
Turkish Journal of Electrical Engineering and Computer Sciences
Osteoarthritis is the most common type of arthritis. Hand osteoarthritis leads to specific structural changes in the joints, such as asymmetric joint space narrowing and osteophytes (bone spurs). Conventional radiography has traditionally been the primary method of visualizing these structural changes and diagnosing osteoarthritis. We aimed to develop a computerized method that is capable of determining the structural changes seen in radiography of the hand and to assist practitioners in interpreting radiographic changes and diagnosing the disease. In this retrospective study, transfer-learning-based convolutional neural networks were trained on a randomly selected dataset containing 332 radiography images of hands from an …
A Quantum Algorithm For Automata Encoding, Edison Tsai, Marek Perkowski
A Quantum Algorithm For Automata Encoding, Edison Tsai, Marek Perkowski
Electrical and Computer Engineering Faculty Publications and Presentations
Encoding of finite automata or state machines is critical to modern digital logic design methods for sequential circuits. Encoding is the process of assigning to every state, input value, and output value of a state machine a binary string, which is used to represent that state, input value, or output value in digital logic. Usually, one wishes to choose an encoding that, when the state machine is implemented as a digital logic circuit, will optimize some aspect of that circuit. For instance, one might wish to encode in such a way as to minimize power dissipation or silicon area. For …
Context-Aware System For Glycemic Control In Diabetic Patients Using Neural Networks, Owais Bhat, Dawood A. Khan
Context-Aware System For Glycemic Control In Diabetic Patients Using Neural Networks, Owais Bhat, Dawood A. Khan
Turkish Journal of Electrical Engineering and Computer Sciences
Diabetic patients are quite hesitant in engaging in normal physiological activities due to difficulties associated with diabetes management. Over the last few decades, there have been advancements in the computational power of embedded systems and glucose sensing technologies. These advancements have attracted the attention of researchers around the globe developing automatic insulin delivery systems. In this paper, a method of closed-loop control of diabetes based on neural networks is proposed. These neural networks are used for making predictions based on the clinical data of a patient. A neural network feedback controller is also designed to provide a glycemic response by …
Automatic Characterization Of Copy Number Polymorphism Using High Throughput Sequencing, Can Alkan
Automatic Characterization Of Copy Number Polymorphism Using High Throughput Sequencing, Can Alkan
Turkish Journal of Electrical Engineering and Computer Sciences
Genome structural variation, broadly defined as alterations longer than 50 bp, are important sources for genetic variation among humans, including those that cause complex diseases such as autism, developmental delay, and schizophrenia. Although there has been considerable progress in characterizing structural variation since the beginnings of the 1000 Genomes Project, one form of structural variation called segmental duplications (SDs) remained largely understudied in large cohorts. This is mostly because SDs cannot be accurately discovered using the alignment files generated with standard read mapping tools. Instead, they can only be found when multiple map locations are considered. There is still a …
A Power And Area Efficient Approximate Carry Skip Adder For Error Resilient Applications, Sujit Patel, Bharat Garg, Shireesh Kumar Rai
A Power And Area Efficient Approximate Carry Skip Adder For Error Resilient Applications, Sujit Patel, Bharat Garg, Shireesh Kumar Rai
Turkish Journal of Electrical Engineering and Computer Sciences
The compute-intensive multimedia applications on portable devices require power and area efficient arithmetic units. The adder is a prime building block of these arithmetic units and limits the overall performance. Therefore, this paper analyzes the logic operations of the state-of-the-art adders and presents a novel low complexity adder segment with new carry prediction logic by removing the redundant logic and sharing the common operations. Further, a new power and area efficient approximate carry skip (PAEA-CSK) adder is proposed using the novel adder segment. The effectiveness of the proposed PAEA-CSK adder is evaluated and compared over the existing adders by implementing …
Rule Extraction And Performance Estimation By Using Variable Neighborhoodsearch For Solar Power Plant In Konya, Yusuf Uzun, Muci̇z Özcan
Rule Extraction And Performance Estimation By Using Variable Neighborhoodsearch For Solar Power Plant In Konya, Yusuf Uzun, Muci̇z Özcan
Turkish Journal of Electrical Engineering and Computer Sciences
The use of renewable energy sources in the production of electricity has become inevitable in order to reduce the greenhouse gases left in the atmosphere that cause the Earth to warm up. Although countries on a national basis have implemented a number of policies to support electricity generated from renewable energy sources, investments to produce electricity without a license on a local basis are not desirable. Those who want to invest medium and small scale for the most reason expect that this work will be supported by real data. Although the electricity generated by renewable investments is generated by simulation …
Robust Optimal Operation Of Smart Distribution Grids With Renewable Basedgenerators, Omid Zare, Sadjad Galvani, Murtaza Farsadi
Robust Optimal Operation Of Smart Distribution Grids With Renewable Basedgenerators, Omid Zare, Sadjad Galvani, Murtaza Farsadi
Turkish Journal of Electrical Engineering and Computer Sciences
Modern distribution systems are equipped with various distributed energy resources (DERs) because of the importance of local generation. These distribution systems encounter more and more uncertainties because of the ever-increasing use of renewable energies. Other sources of uncertainty, such as load variation and system components? failure, will intensify the unpredictable nature of modern distribution systems. Integrating energy storage systems into distribution grids can play a role as a flexible bidirectional source to accommodate issues from constantly varying loads and renewable resources. The overall functionality of these modern distribution systems is enhanced using communication and computational abilities in smart grid frameworks. …
Lattice-Reduction Aided Multiple-Symbol Differential Detection In Two-Way Relay Transmission, Chanfei Wang, Minghua Cao
Lattice-Reduction Aided Multiple-Symbol Differential Detection In Two-Way Relay Transmission, Chanfei Wang, Minghua Cao
Turkish Journal of Electrical Engineering and Computer Sciences
Multiple-symbol differential detection (MSDD) algorithms are proposed in two-way relay transmission (TWRT). Firstly, generalized likelihood ratio test based MSDD (GLRT-MSDD) is proposed in TWRT. Unfortunately, as the number of observation windows increases, the computational complexity of GLRT-MSDD increases exponentially. Hence, this detection in TWRT constitutes a challenging problem. Moreover, we find a way to reformulate the GLRTMSDD model and additionally propose a lattice-reduction aided MSDD (LR-MSDD) model. Performance analysis and simulations show that the proposed LR-MSDD provides bit-error rate performance close to that of GLRT-MSDD with lower complexity in TWRT.
Emulation Of Burst-Based Adaptive Link Rates In Netfpga Towards Green Networking, Shahul Hamead H, Mirnalinee Tt, Kavi Priya D
Emulation Of Burst-Based Adaptive Link Rates In Netfpga Towards Green Networking, Shahul Hamead H, Mirnalinee Tt, Kavi Priya D
Turkish Journal of Electrical Engineering and Computer Sciences
In recent times, energy consumption in communication media has been increasing drastically. In the literature, energy-saving techniques that enable network devices to enter sleep state or limit the data rate have been proposed to reduce energy costs. In our earlier work, we proposed an energy-saving technique called burst-based adaptive link rate (BBALR), the simulation of which assures increased energy savings. In this paper, we have emulated the hardware implementation of BBALR and compared its performance with the outputs of other prominent energy-saving policies based on dynamic link rate adaption. The energy savings are mapped from the measured sleep time and …
Assessment Of Environmental Factors Affecting Software Reliability: A Survey Study, Alper Özcan, Çağatay Çatal, Cengi̇z Toğay, Bedi̇r Teki̇nerdoğan, Emrah Dönmez
Assessment Of Environmental Factors Affecting Software Reliability: A Survey Study, Alper Özcan, Çağatay Çatal, Cengi̇z Toğay, Bedi̇r Teki̇nerdoğan, Emrah Dönmez
Turkish Journal of Electrical Engineering and Computer Sciences
Currently, many systems depend on software, and software reliability as such has become one of the key challenges. Several studies have been carried out that focus on the impact of external environmental factors that impact software reliability. These studies, however, were all carried out in the same geographical context. Given the rapid developments in software engineering, this study aims to identify and reinvestigate the environmental factors that impact software reliability by also considering a different context. The environmental factors that have an impact on software reliability as reported in earlier studies have been analyzed and synthesized. Subsequently, a survey study …
Improving Performance Of Indoor Localization Using Compressive Sensing Andnormal Hedge Algorithm, Saeid Hassanhosseini, Mohammad Reza Taban, Jamshid Abouei, Arash Mohammadi
Improving Performance Of Indoor Localization Using Compressive Sensing Andnormal Hedge Algorithm, Saeid Hassanhosseini, Mohammad Reza Taban, Jamshid Abouei, Arash Mohammadi
Turkish Journal of Electrical Engineering and Computer Sciences
Accurate indoor localization technologies are currently in high demand in wireless sensor networks, which strongly drive the development of various wireless applications including healthcare monitoring, patient tracking and endoscopic capsule localization. The precise position determination requires exact estimation of the time varying characteristics of wireless channels. In this paper, we address this issue and propose a three-phased scheme, which employs an optimal single stage TDOA/FDOA/AOA indoor localization based on spatial sparsity. The first contribution is to formulate the received unknown signals from the emitter as a compressive sensing problem. Then, we solve an $\ell_1$ minimization problem to localize the emitter's …
Optimal Svc Allocation In Power Systems Using Lightning Attachment Procedureoptimization, Ayman Awad, Salah Kamel, Heba Youssef, Francisco Jurado
Optimal Svc Allocation In Power Systems Using Lightning Attachment Procedureoptimization, Ayman Awad, Salah Kamel, Heba Youssef, Francisco Jurado
Turkish Journal of Electrical Engineering and Computer Sciences
Flexible AC transmission systems (FACTS) technology is widely adopted and utilized to maintain the performance of power systems. However, the improvements of power system performance achieved by FACTS devices depend on the right sizing and allocation of such devices. For technical and economic considerations, a FACTS device's location and size should be selected very carefully in order to maximize its benefits to the power system. In this paper, the sizing and location of a static VAR compensator (SVC) are optimally determined using a new optimization technique called lightning attachment procedure optimization (LAPO). The optimal allocation of the SVC is determined …
Fiber Optic Chemical Sensors For Water Testing By Using Fiber Loop Ringdown Spectroscopy Technique, Mali̇k Kaya
Fiber Optic Chemical Sensors For Water Testing By Using Fiber Loop Ringdown Spectroscopy Technique, Mali̇k Kaya
Turkish Journal of Electrical Engineering and Computer Sciences
Real-time response, low cost, sensitive and easy setup fiber optic chemical sensors were fabricated by etching a part of single mode fiber in hydrofluoric (HF) acid solution and tested in different water samples such as tap water, DI water, salty and sugar water with different concentrations to record ringdown time (RDT) differences between media due to refractive index differences by employing the fiber loop ringdown (FLRD) spectroscopy technique. Baseline stability of 0.63 % and the minimum detectable RDT of $5.05$ $\mu$s for this kind of fiber optic chemical sensors were obtained. Fabricated sensors were coated with N,N-Diethyl-p-phenylenediamine for the first …
Prominent Quality Attributes Of Crisis Software Systems: A Literature Review, Ahmet Ari̇f Aydin
Prominent Quality Attributes Of Crisis Software Systems: A Literature Review, Ahmet Ari̇f Aydin
Turkish Journal of Electrical Engineering and Computer Sciences
Developing software systems to meet user-demanded functionality is critical. Achieving the design goals by providing the needed functionality is a necessary task, and it is about figuring out a proper set of quality attributes and implementing each one by reflecting a complete set of quality attributes. This study presents popular quality attributes of crisis software systems by conducting a literature review. Each crisis software system has been studied by concentrating on crisis management phases where the system is used, design purposes, and the data processing style. The findings of this research shed light on the crisis software development process by …
A Mechanism Of Qos Differentiation Based On Offset Time And Adjusted Burstlength In Obs Networks, Viet Minh Nhat Vo, Trung Duc Pham, Thanh Chuong Dang, Van Hoa Le
A Mechanism Of Qos Differentiation Based On Offset Time And Adjusted Burstlength In Obs Networks, Viet Minh Nhat Vo, Trung Duc Pham, Thanh Chuong Dang, Van Hoa Le
Turkish Journal of Electrical Engineering and Computer Sciences
Quality of service (QoS) differentiation is an integral component of any networking system, particularly, with the current and future great diversity of users? applications and their manifold requirements. In optical burst switching (OBS) networks, there are two approaches for QoS differentiation: one is based on offset time and the other is based on burst length. This paper presents a mechanism of QoS differentiation based on both offset time and burst length, in which the offset times are calculated to achieve a complete isolation of data loss between priority classes and the burst length is adaptively adjusted according to the feedbacked …
Diagnosis Of Speed Sensor Faults In An Induction Machine Based On A Robustadaptive Super-Twisting Observer, Mohammed Zakaria Kari, Abdelkader Mechernene, Sidi Mohammed Meliani, Ibrahim Guenoune
Diagnosis Of Speed Sensor Faults In An Induction Machine Based On A Robustadaptive Super-Twisting Observer, Mohammed Zakaria Kari, Abdelkader Mechernene, Sidi Mohammed Meliani, Ibrahim Guenoune
Turkish Journal of Electrical Engineering and Computer Sciences
The present paper aims to determine a robust sensor fault-tolerant controller based on fuzzy logic using a robust adaptive super-twisting observer for the control of an induction machine and an inverter set by a state estimation method. The speed sensor is considered in the present case. The modular structure of the fault-tolerant control (FTC) scheme allows integrating this sensor within the existing closed-loop system, and the observer can therefore be designed independently. This article presents a new method to develop a fuzzy decision system that provides faulttolerant control. This paper also aims at detecting the mechanical speed sensor faults. The …
Sdma-Based Distributed Device Discovery For D2d Communication, Muddasir Rahim, Muhammad Awais Javed, Ahmad Naseem Alvi
Sdma-Based Distributed Device Discovery For D2d Communication, Muddasir Rahim, Muhammad Awais Javed, Ahmad Naseem Alvi
Turkish Journal of Electrical Engineering and Computer Sciences
Device-to-device (D2D) communication is an important technique to improve capacity of future wireless networks. Cellular communications, internet of things and intelligent transport systems are key areas that could benefit from reduced end-to-end delay provided by D2D communication. Efficient device discovery is an important precondition to enable D2D communication. In this paper, we propose a space division multiple access (SDMA)-based distributed device discovery protocol in which user equipments (UEs) periodically transmit discovery beacons to each other. The proposed protocol reduces contention in the discovery beacons by allocating resource blocks to the UEs based on their location. Simulations results show that the …
A New Grid Partitioning Technology For Location Privacy Protection, Yue Sun, Lei Zhang, Jing Li, Zhen Zhang
A New Grid Partitioning Technology For Location Privacy Protection, Yue Sun, Lei Zhang, Jing Li, Zhen Zhang
Turkish Journal of Electrical Engineering and Computer Sciences
Nowadays, the location-based service (LBS) has become an essential part of convenient service in people's daily life. However, the untrusted LBS servers can store lots of information about the user, such as the user's identity, location, and destination. Then the information can be used as background knowledge and combined with the query frequency of the user to launch the inference attack to obtain user's privacy. In most of the existing schemes, the author considers the algorithm of virtual location selection from the historical location of the user. However, the LBS server can infer the user's location information on the historical …