M.S. Theses
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Item A wearable antenna system for structural monitoring of biodegradable magnesium-based suture wires(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Sezgen, Ozan Furkan.; Dumanlı Oktar, Sema.Open-heart surgery is a way of treating various heart problems. It is a challenging operation during which the operating surgeon will cut through the sternum and spread the ribcage to access the heart. After sternotomy, complications such as sternal separation and wound or subcutaneous infections may occur due to the sensitivity of the operation region. The probability of occurrence for these post-operative infections is low; however, the mortality rate is high in case of infection. Such risks make remote monitoring and examining patients’ health more critical in the post-operative period. Computed tomography appears as the traditional way of tracking the sutures surrounding the sternum. Stainless steel and titanium are popular for sutures to close the sternum after open-heart surgery. This thesis proposes an alternative suture material and a novel structural real-time monitoring technique in the post-operative period. Magnesium-based sutures have become significant in medical applications due to their biocompatibility and its ability to degrade without releasing any byproduct. A wearable antenna system is a possible solution to monitor patients who underwent open-heart surgery. Ultra- wideband(UWB) coplanar waveguide(CPW) fed disc monopole antenna is chosen as the on-body reader antenna and is optimized to operate on the human body and is fabricated on 1.27 mm Rogers RO3210 with relative permittivity of 10.2. Next, a series of analyses are made in the numerical model, such as the degradation tracking of magnesium-based sutures, breakage points on the suture, different thicknesses to represent overweight and underweight patients, and antenna position effect. After that, the measurement setup is established, including the tissue-mimicking human average and human bone phantoms. Finally, simulation and measurement results are compared and interpreted.Item An iterative approach to keyword search in sign language(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Yeşilbursa, Mansur.; Saraçlar, Murat.Sign languages are the main medium of communication for the Deaf. However, insufficient retrieval tools for sign languages restrict the Deaf’s access to information. To address this issue, we tackle the problem of keyword search in sign language. Although keyword search is a well-studied task for domains like speech processing, it has not been extensively studied in the context of sign language. To this end, we introduce improvements to an existing keyword search system for sign language and a new iterative training approach. We adapt Graph Attention Networks (GAT) to the sign language domain and extend its capabilities by employing a learnable mask and a separate temporal attention mechanism. Moreover, we investigate the effectiveness of the Pseudo-Relevance Feedback (PRF) technique in improving retrieval accuracy. Additionally, it is demonstrated that the existing model can also be trained with similarity-based methods using cosine and triplet losses, which can later be fused with other models to boost performance. Finally, we introduce an iterative training method similar to Expectation-Maximization (EM) that gradually improves its predictions. This method employs a cross-modal attention mechanism and a query encoder to discover subtle video-query interactions. The experiments are carried out on the RWTH- Phoenix2014T dataset, where the effectiveness of the proposed methods is verified. The results show that the pose models trained with a GAT-based encoder and in an iterative way significantly improve the retrieval performance.Item Resilient distributed algorithms for solving linear algebraic equations in faulty networks(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Çiftçi, Oğuzhan.; Akar, Mehmet.Various methods have been developed to solve linear algebraic equations distributively over multi-agent networks. Most studies consider that all agents are trustworthy and utilize all the received data from their neighbors throughout the process. Nevertheless, cooperation between non-faulty agents is disrupted if faulty agents intrude into the network. This thesis aims to develop algorithms to detect all faulty agents in the network without prior knowledge of the number of faulty agents. We study four fault models: random-state, fixed-state, single-faced, and double-faced and propose fault detection procedures according to the characteristics of these fault models. First, we introduce a method in which each agent can determine its neighbors’ system of equations if it receives sufficient solution estimations from neighboring agents. By utilizing this method, we propose a synchronous discrete-time distributed detection algorithm for the perfectly synchronized agents in terms of their event times. On the other hand, the event time sequences of different agents are not always assumed to be synchronized. Therefore, we also propose an asynchronous discrete-time distributed fault detection algorithm to analyze the effect of the asynchronous event times of agents. Also, we discuss the applicability of our detection algorithm in continuous-time systems. Moreover, complexity analyses for the proposed algorithms are carried out. Theoretical results are also illustrated by numerical examples.Item Deep packet inspection methods for network intrusion detection and application classification(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Ateş, Çağatay.; Anarım, Emin.; Koca, Mutlu.Deep packet inspection methods have become more sophisticated with the rapidly developing technology. To understand the condition of the network, many different packet inspection techniques have been evolved. Newly developing machine learning methods have been used recently on these systems. The aim is to know which type of traffic is running through the network. In this thesis, different deep packet inspection methods are proposed to detect malicious traffic and find the applications running on the network. Time–series and flow–based methods are proposed to accomplish these tasks. Novel feature sets are constructed to execute these methods. Greedy algorithm which finds an upper bound for the distance between the probability distributions with different sizes is utilized in feature extraction process. The extracted features can be divided into two categories which are statistical features and payload–based features. Packet header values such as IP addresses are used to derive statistical features. Also, payload portion of packets are used to extract novel payload–based features. The fea ture sets are used with decision tree models in supervised learning to execute detection procedures. Proposed approaches are used in network intrusion detection and network application classification tasks. For network intrusion detection, performance evalua tion is given by using different publicly available well–known intrusion detection data sets consisting of different types of attacks. For network application classification, a data set consisting of real–world network traces from popular applications is used. Sim ulation results show that the proposed flow–based approaches have good performance in fulfilling these tasks.Item The suitability of active inductors for a wide range of CMOS implementations(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Kızmaz, Muhammed Mustafa.; Çiçekoğlu, Oğuzhan.Integrated circuits (ICs) form the heart of today's technology thanks to their prominent features such as minimal size, reduced cost, high reliability, and low power consumption. Then, inductors have found a wide range of uses in modern IC implementations. These application areas can be exemplified by impedance matching, bandwidth enhancement, gain boosting, frequency selection, phase shifters, and LC oscillators. The frequently preferred method for the required inductances is using CMOS spiral inductors. However, spiral inductors have significant shortcomings that limit their use in CMOS realization. For example, spiral inductors consume a large chip area, and it is impossible to tune their inductance values. Moreover, these inductors have low quality factors (Q) and low self-resonant frequencies. Due to the drawbacks of spiral inductors, researchers have been looking for alternatives. One of these approaches is active inductors (AIs), which use active circuit components to synthesize required inductance. Numerous AI topologies have been presented in the literature. Each architecture may be selected depending on the inductance needs of the application. Thus, AIs have a broad variety of applications in CMOS implementations due to their diversity of topologies. This thesis demonstrates that employing AIs is feasible for a range of CMOS implementations. Its feasibility is proven by designing an AI-based wide-tunable LC voltage- controlled oscillator (LC-VCO), a lattice-based allpass filter, and an autonomous chaotic oscillator.Item Design and implementation of a response retrieval and reranking system(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Deveci, Mustafa Can.; Saraçlar, Murat.In this master’s thesis, we started with a baseline response retrieval and re ranking system that is composed of two steps: BM25 retrieval and BERT re-ranking. After investigating the effects of several parameters and BERT model size on the base line approach, a novel retrieval and re-ranking system with TF- IDF retrieval and Cross Encoder re-ranking steps was designed and implemented. With the application of Deep Learning models to the re-ranking step, consistent ranking performance improvements have been observed. The research focus of this thesis is a comparative performance study of different Transformer models. In the experiments carried on in this thesis, we showed that smaller transformer models can out- perform larger models. Additionally, this designed re-ranking system was re-purposed for a Question Answering task where the answer for a given question is searched as a subset of a passage. Even though the re-ranking system was directly used without undergoing any modifications regarding the QA task, promising results that are worth further research have been attained.Item Advanced techniques for cooperation and physical layer security in visible light communications(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Su, Nuğman.; Koca, MutluVisible light communications (VLC), enabling high-rate data transfer over the idle visible light spectrum, can contribute to alleviating the congestion problem ac cumulating in the radio-frequency spectrum. This thesis deals with two important aspects of VLC: i) efficient cooperation techniques adapted to the intensity-modulated light-emitting-diode (LED) transmitters, ii) secure multi-user communication schemes based on the multiple-input-multiple-output (MIMO) framework. Firstly, 3-terminal full-duplex (FD) cooperative VLC systems are considered where both transmitters (source and relay) are subject to the LED clipping distortion effects. Transmission rate maximizing optimum power allocation (OPA) strategies are proposed for both the amplify-and-forward (AF) and decode-and- forward (DF) relaying capabilities. Next, the physical layer security (PLS) problem is considered for the multi-user MIMO- VLC systems with an eavesdropper (Eve). To ensure PLS, two transmit precoding schemes are proposed, based on generalized space shift keying and receive spatial modulation, respectively. The received signals of the legitimate users are optimized jointly, such that their bit error rates (BERs) are minimized and Eve’s BER is significantly degraded. To be able to support massive amount users and further degrade Eve’s reception, non orthogonal multiple access (NOMA) and random constellation coding techniques are also utilized. For both cases, the achievable secrecy rates and bounds are derived an alytically. The BER and secrecy performance results obtained by simulations confirm that the proposed frameworks ensure PLS for legitimate users.Item Deep learning based automatic modulation classification in the presence of carrier phase offset and carrier frequency offset(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Yılmaz, Ramazan.; Pusane, Ali Emre.Automatic Modulation Classification (AMC) has emerged after the efforts of making the modulation classification process autonomous. Since then, various meth ods, algorithms, and tools have been used in the AMC field, such as likelihood-based methods, the goodness of fit tests, feature-based methods, machine learning-based methods, and deep learning-based methods. With the help of these methods, the mod ulation classification operation can be performed automatically without any human input. In this thesis, we survey these methods in detail and propose our methods to contribute to the AMC field. First, we proposed a blind feature-based algorithm that uses K- nearest neighbor (KNN) to perform classification. When the number of sym bols in each signal decreases, the classification process may encounter an error floor. The main goal of the proposed feature-based algorithm is to combat this error floor. Then, we proposed a novel polar coordinate approach in deep learning to classify the signals that are affected by carrier phase offset (CPO). The polar coordinate approach converts the rotational effect of CPO into the translational effect, which makes the classification easier. Finally, we propose a 2-staged deep learning-based classification algorithm under the presence of carrier frequency offset (CFO). In the first stage, the algorithm estimates the CFO amount and in the second stage, it classifies the CFO affected signals. Finally, we conclude the thesis by discussing the future works and possible improvements.Item Model-based and model-free control algorithms for textile processes(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Çom, Mustafa.; Akar, Mehmet.Textile processes consist of several control loops that require accurate reference tracking. One of the most crucial control loops is the temperature control where the temperature of the corresponding medium must track the reference value with sufficient accuracy to obtain a high-quality textile product. Even though several studies can be found on designing control algorithms for industrial processes in the literature, none of them focus particularly on the aforementioned textile processes. In this study, in order to achieve successful control, several adaptive control algorithms are developed. In addition, corresponding processes are modelled, and a simulation environment is built to increase the speed and safety of development works. Modelling is realized by dividing the corresponding process into several regions of operation, preparing sub-models for each region and building a composite model by combining these sub-models. A simulation environment is created by examining currently used control algorithms and process dynamics. The simulations of designed models result in significant accuracies. A model-based control algorithm, based on the Model Predictive Control (MPC) approach that utilises previously designed pro cess models, is developed and verified in the simulation environment. Two model-free control algorithms, referred to as Adaptive PI Control and Error Predictive Control (EPC), are developed and verified not only in the simulation environment but also in the field.Item Novel positive and negative active inductor circuit designs(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Özaydın, Ahmet Mustafa.; Çiçekoğlu, Oğuzhan.Inductor is one of the main passive elements in electronics. It has a significant role in designs and are being used in electrical circuits widely. However, physical inductors have considerable drawbacks which limit their usage in low scale such as on-chip large die area consumption and magnetic filed creation. As an alternative solution, circuits that partly shows inductive behavior have been started to be proposed over the last decades. This types of proposed circuits could be seperated in two categories: grounded and floating active inductor circuits. Grounded active inductors are not as desirable as floating type of active inductors due to the fact that one the input ports should be grounded. Therefore, usage of the grounded active inductors is severely limited. On the other hand, floating inductors could possibly replace a passive inductor in any application, which makes them appealing. In this work, floating type positive and negative active inductor circuits are pre sented and their mathematical and simulation results are shared. In addition, the effect of the parasitic components of the devices on the behavior of the circuit is examined. In order to show the circuits’ usability, application instances and their results are shared and they are compared to a situation where an ideal inductor is employed. Overall, it could be said that the proposed circuits partly show inductive behavior over a limited frequency band.Item Design of negative group delay circuits with MOS-only applications(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Baloğlu, Onat.; Çiçekoğlu, Oğuzhan.Physical size, design flexibility, noise, signal attenuation, and distortion are a few of the issues that arise in the design of analog electrical circuits. Additionally, a major difficulty with electronic systems is their time delay, particularly when high order filters are present. The literature, especially in the last 10 years, provides a variety of applications for negative group delay (NGD) implemented with electronic circuits as well as mathematical models to address that issue. The signal amplification and the group delay linearity are the major design parameters for the NGD that is employed to achieve low distortion at the output. A flexible NGD design and the operation range of the NGD circuit is additionally required to expand the application area. In this thesis, active NGD circuits based on MOSFETs to decrease the physical size of the design using Current Feedback Operational Amplifier (CFOA), Operational Transconductance Amplifier (OTA-C) based voltage mode and transimpedance-mode NGD circuits have been designed. Moreover, a mathematical approach to design such analog electronic circuits have been demonstrated. The relation of the NGD frequency operation range and NGD value is presented and example designs are demonstrated using well-defined parameters. Along with the calculations and simulation results, an experimental verification is presented in a lab setting. The findings demonstrate that a time advance is possible in a specific frequency range without a direct dependence on the system gain value.Item Payload based multi-phase traffic classification with majority voting(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Mert, İlhan Selçuk.; Anarım, Emin.Internet is becoming an essential part of our lives with even simple daily tasks depending on it. This led to an increase in network traffic accompanied with increase in number of applications hosted on internet. In this heavy traffic environment, classifying network flows in a fast and accurate manner, has great importance for network management. Internet Service Providers try to address this issue by using different approaches from port-based methods to machine learning models but due to widespread usage of dynamic ports and encrypted packets by modern applications, accuracy of these approaches declined. To overcome this challenge, recent studies focus on solutions using deep learning architectures. In this thesis, a multi-phase classification model based on voting and deep learning is proposed for encrypted traffic classification. The proposed model relies on the payload of the transmitted packets to classify flows. In this approach, deep learning based classifiers are trained using different numbers of packets from flows as input and the prediction of multi-phase model is an ensemble of these classifiers calculated by different voting strategies. This approach enables classification of flows starting from the first transmitted packet with payload, and updates the predicted class as the number of transmitted packets in flow increases. This approach has been tested on datasets containing real network flows from various applications. The performance of proposed approach is evaluated by comparing different classification models and different voting strategies. NOTE Keywords : Machine learning, Majority voting, Traffic network, Communication networks.Item An instrument for recording and analysis of heart sounds(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Güvendi, Gözde.; Kahya, Yasemin.According to the data of the WHO, heart diseases are the leading diseases with high level mortality rates. In 2019, 17.9 million individuals died due to CVDs, this number is constituting 32 percent of the death rates. For this reason, early diagnosis of heart diseases still maintains its significance today. While the diagnosis of these diseases is made by traditional auscultation methods, advanced technological digital stethoscopes are also used in today’s technology. Thanks to these devices, the auscultated sound can be interpreted automatically, at the same time recorded and listened to again later, and cardiac dysfunction can be detected with advanced classification algorithms. Thus, these systems may prevent misinterpretations and create a crucial benefit for early diagnosis. This thesis aims to develop a portable heart sound acquisition, recording and automatic analysis device. The purpose is to design a system which has a long life with low cost and low power consumption. Proposed instrument enables recording of the amplified and filtered sound with a user friendly interface. At the same time, heart sounds can be listened to directly on the device at the desired volume level with the headphone output thanks to this instrument. The analog data converted to digital is transmitted to both the mobile phone and the computer using Bluetooth Low Energy technology, and the signal can be monitored and analyzed on computer based GUI. User friendly interface shows people’s heart rate and heart rate variability value. In this way, users can have information about their stress levels and heart related issues.Item Design, analysis, and channel modeling of molecular multiple- receiver communication systems(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Yaylalı, Gökberk.; Pusane, Ali Emre.Molecular communication is a prominent technology that emerged from contem porary needs. Due to its low energy cost and simple system designs, it is an effective approach to communication on the nanoscale. Among the molecular system designs in the literature, although molecular single-input single-output (SISO) systems are one of the primary systems, they cannot match the required data transmission rate de mands. Inspired by the direction of the field, this thesis focuses on molecular multiple receiver networks. Interference is a crucial problem for molecular multiple-receiver systems which needs to be analyzed. To this point, a comprehensive investigation of molecular multiple-input multiple-output (MIMO) systems in terms of communication performance and channel state information is performed. Results exhibit the channel characteristics in detail. As the analysis becomes the backbone of further designs, two interference-mitigating methods for molecular SISO systems are applied to molecular MIMO systems. The expectations of the interference at each receiver can be estimated and subtracted from signals to detect the information more accurately. Additionally, a pre-equalization method is employed in molecular MIMO systems. Utilizing different molecule types to remove interference from signals has shown an increase in perfor mance for higher data transmission rates. Furthermore, a novel channel modeling for molecular multiple- receiver systems is proposed, as it is the foundation of developing sophisticated systems and modulation schemes. Computer-based simulations showed that the proposed model offers well channel characterization of such systems, and the model is aimed to be the pioneer of future developments in nanonetworks.Item Network intrusion detection with payload-based approach(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Özdel, Süleyman.; Anarım, Emin.; Koca, MutluRapidly growing network systems become more vulnerable to threats with the improved sophistication of attack techniques. Various types of network attacks af fect networks in different ways and continue to be a serious threat despite developing intrusion detection mechanisms. Early detection of network intrusions is crucial to taking precautions and reducing the damage to the system. In addition, the ability to distinguish attacker flows from legitimate ones ensures that the network continues to provide service safely to the clients. In this thesis, payload- based features that characterize network flows are proposed to provide early detection of network attacks and to identify attacker flows. Besides the features conventionally used in application classification, features based on greedy algorithm- based metrics that allow comparing defined probability distributions over different sample spaces at various lengths are also used. Moreover, features based on spectral domain analysis of payload sequences are extracted to capture the complicated patterns that are not observed in the original domain. Also, features based on discrete cosine transforms are utilized in the charac terization of these network flows. These features are extracted using N-gram analysis for various N values. In the classification stage, SVM models trained with these fea tures are used. Performance evaluation is given for publicly available IDS 2012 and IDS 2017 datasets that contain different kinds of attack traces. Early detection of network intrusions based on features extracted from the first 3 and 5 packets of a flow achieves high detection rates while detecting network intrusions early.Item Low power secure SOC for IOT devices using lightweight cryptography acceleration(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Öztürk, Hikmet Seha.; Başkaya, Faik.In recent years, the proliferation of the Internet of Things (IoT) has led to a major increase in the quantity and type of devices involved in digital communications. Various Lightweight Cryptography (LWC) algorithms have been proposed to answer the need of cryptography in constrained devices. Although using separate algorithms for products with varying capacities is advantageous for optimization, it creates the risk that a single product may need to support multiple cryptographic primitives. This thesis aims to find an efficient way of providing hardware acceleration for multiple cryptography algorithms in lightweight System-on-Chips (SoC). For this pur pose, we present a design methodology that identifies the common portions across LWC algorithms and uses them to increase shared resources in the hardware. We explore two approaches to accelerator design: A fully-hardware approach and a hardware- software approach. Our observations indicate that the second approach, which employs an accelerator with a custom ISA, is more effective when designing for versatility. We leverage the open-source PicoRV32 processor to construct a lightweight SoC which employs various accelerators supporting Ascon, TinyJAMBU, and PHOTON Beetle LWC algorithms. To enable multi-algorithm support, we utilize hardware multi plexing of unshared resources, as well as Dynamic Partial Self-Reconfiguration (DPSR) on FPGA. These implementations are compared with each other and with dedicated ac celerators in terms of energy efficiency, area, and throughput. The associated tradeoffs and the conditions in which each variant is useful are determined.Item Low power Advanced Encryption Standard (AES) implementation robust against side channel attacks(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Unal, Serdar.; Başkaya, Faik.As the people around the globe become increasingly connected to each other, the amount of information that flows becomes huge. Unfortunately, this vast information network is vulnerable to harmful attacks. Encryption is a strong tool that has been used for ages to act as a shield against these attacks. Among many algorithms utilized for encryption, one of the most popular is AES. AES is an approximately 20-year old algorithm that has been adopted by many organizations around the world to protect classified and unclassified data. In line with the trend of low power and secure implementations, the main intent of this thesis is to show a low-power AES implementation that is secure against power side-channel attacks. In the RTL, currently unused registers are kept constant to lower the power consumption. Choosing the LP ASIC process, using clock-gating, and preferring standard cells with higher threshold voltages enable more power saving. For the side-channel attack resistance, obfuscating and pipelining are employed. The obfuscating disguises the relation between the processed bits and the power consumption by modifying the processed information. On the other hand, the pipelining mixes power consumption related to different inputs with each other. The different versions of AES implementations are processed through FPGA and TSMC 65 nm ASIC flow to compare with each other. After the power traces are collected and analyzed by ChipWhisperer the side-channel attack resistance is evaluated. The effects of the obfuscating and pipelining in increasing attack resistance are proven after predicting key bytes from power traces stemming from thousands of random inputs. The area, power overheads in return for increased attack resistance are detected.Item Reduced-complexity reinforcement learning-based polar code construction(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Oral, Ezgi.; Pusane, Ali Emre.; Altunbaş, İbrahim.Due to the increasing number of users in the communication systems, efficient spectrum usage, high-speed data transfer, and better error performance became a ne cessity. Therefore, it is aimed to design error control codes that have low error rates and have a capacity close to the Shannon’s limit. As a consequence of Erdal Arıkan’s work, polar codes, a coding technique that is theoretically proven to achieve Shan non’s limit, are introduced. After polar codes are used in fifth- generation new radio (5G NR) technology, more studies are done about the decoding of polar codes and the polar code construction. The scope of the thesis is on reinforcement learning-based polar code construction. Initially, the preliminaries of polar codes and reinforcement learning are given. Then, several reinforcement learning-based polar code construction methods are introduced. It is shown that a reinforcement learning-based method found in the literature performs weakly for long block lengths due to high complexity and therefore, two new methods are introduced to reduce the complexity. First, a method that groups the channels into clusters and predetermines some channels as frozen or information is proposed. For long block lengths, it had a better performance than the one proposed in the literature, but its performance was unsatisfactory for much longer block lengths. To further reduce the complexity, neighbor dependency is introduced to the first method. It is shown that the performance of the neighbor dependent method is better than both methods and its performance is satisfactory for longer block lengths.Item Radar data acquisition and processing system for UAV positioning applications(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Başpınar, Ömer Oğuzhan.; Öncü, Ahmet.Small drones have started to be utilized by researchers for applications such as object tracking, imaging and remote sensing as they become more available, inexpen sive and capable with the advancements in sensor and UAV technologies. Drones can be equipped with sensors such as cameras and radars. Radars can be used onboard for navigation aid by detecting range and velocity, as well as for radar imaging applica tions. Although the latter is common, they can be useful in navigation since they are barely affected by weather conditions or smoke. FMCW radars are fitting devices for drones since they are relatively simple and can be lightweight. Therefore, following a broad FMCW radar survey, a custom drone system and a radar system are designed and implemented for UAV positioning applications. A postprocessing algorithm for detecting the altitude above ground level and ground reflection is developed, and a range compensation method is proposed to improve the performance of the algorithm. Results of a field experiment showed that the radar system can be used for air borne positioning applications. Detected altitudes show similarity to the flight video. Reflections coming from the metal objects are distinguished from those coming from the ground. Range compensation method enabled detecting much lower altitudes, and magnitude of ground reflections obtained from different altitudes became similar. The system can be used in landing aid applications with a proper autopilot software and in SAR imaging with a position sensor more accurate than GPS.Item An adaptive GM-C filter based post-equalizer for wide-band visible light communication systems(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Haydar, Emrah.; Yalçınkaya, Arda Deniz.Visible Light Communication (VLC), more commonly known as Li-Fi (Light Fidelity), has been a buzzword since it was first introduced by Harald Haas in 2011. The idea is that a light source can be used as both illumination and communication means. By switching the current of an LED at high speed, data transmission can be performed and the human eye is not disturbed by the flickering. With the recent research in this field, benefits, challenges, and proven solutions have been addressed. One of the big challenges is the limited modulation bandwidth of the transmitter LED which predominantly determines the achievable maximum data rate. Literature review shows that for the white LEDs, the modulation bandwidth is in the range of hundreds of kHz and a few MHz. Methods to extend the modulation bandwidth includes using: coding/modulation schemes, pre- equalizer, lenses/filters, and post equalizers. Among them, a post equalizer is most easily implemented as it deals with small signals at the receiver side. It can be realized with basic or active RC networks and as well as with ANNs as recent works show. In this work, a Gm-C filter-based post equalizer topology has been proposed. By employing 3-bit capacitors, the equalizer can provide eight distinct edge frequencies which correspond to modulation bandwidths of LEDs in the range of 0.7MHz to 5MHz and at least tenfold equalization is achieved. The circuit is realized by using 130nm low threshold MOSFETs and consumes only 240µW. The overall chip area is 340×340µm2 . Post layout simulations, with eye diagrams, show that data rate up to 200MBits is achievable given that a 5MHz modulation bandwidth is available at the receiver side.