arXiv subjects

Fatih Erden

Publications and source records attributed to Fatih Erden.

At least 19 recordsLinked to original sources

arXiv2024

A Survey on Detection, Classification, and Tracking of UAVs using Radar and Communications Systems

The use of unmanned aerial vehicles (UAVs) for a variety of commercial, civilian, and defense applications has increased many folds in recent years. While UAVs are expected to transform future air operations, there are instances where they can be used for malicious purposes. In this context, the detection, classification, and tracking (DCT) of UAVs (DCT-U) for safety and surveillance of national air space is a challenging task when compared to DCT of manned aerial vehicles. In this survey, we discuss the threats and challenges from malicious UAVs and we subsequently study three radio frequency (RF)-based systems for DCT-U. These RF-based systems include radars, communication systems, and RF analyzers. Radar systems are further divided into conventional and modern radar systems, while communication systems can be used for joint communications and sensing (JC&S) in active mode and act as a source of illumination to passive radars for DCT-U. The limitations of the three RF-based systems are also provided. The survey briefly discusses non-RF systems for DCT-U and their limitations. Future directions based on the lessons learned are provided at the end of the survey.

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arXiv2022

A Survey on Detection, Tracking, and Classification of Aerial Threats using Radars and Communications Systems

The use of unmanned aerial vehicles (UAVs) for different applications has increased many folds in recent years. The UAVs are expected to change the future air operations. However, there are instances where the UAVs can be used for malicious purposes. The detection, tracking, and classification of UAVs is challenging compared to manned aerial vehicles (MAVs) mainly due to small size, complex shapes, and ability to fly close to the terrain and in autonomous flight patterns in swarms. In this survey, we will discuss current and future aerial threats, and provide an overview of radar systems to counter such threats. We also study the performance parameters of radar systems for the detection, tracking, and classification of UAVs compared to MAVs. In addition to dedicated radar systems, we review the use of joint communication-radar (JCR) systems, as well as passive monitoring of changes in the common communication signals, e.g., FM, LTE, and any transmissions that may radiate from a UAV, for the detection, tracking, and classification of UAVs are provided. Finally, limitations of radar systems and comparison with other techniques that do not rely on radars for detection, tracking, and classification of aerial threats are provided.

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arXiv2021

A Framework for Developing Algorithms for Estimating Propagation Parameters from Measurements

A framework is proposed for developing and evaluating algorithms for extracting multipath propagation components (MPCs) from measurements collected by sounders at millimeter-wave (mmW) frequencies. To focus on algorithmic performance, an idealized model is proposed for the spatial frequency response of the propagation environment measured by a sounder. The input to the sounder model is a pre-determined set of MPC parameters that serve as the "ground truth." A three-dimensional angle-delay (beamspace) representation of the measured spatial frequency response serves as a natural domain for implementing and analyzing MPC extraction algorithms. Metrics for quantifying the error in estimated MPC parameters are introduced. Initial results are presented for a greedy matching pursuit algorithm that performs a least-squares (LS) reconstruction of the MPC path gains within the iterations. The results indicate that the simple greedy-LS algorithm has the ability to extract MPCs over a large dynamic range, and suggest several avenues for further performance improvement through extensions of the greedy-LS algorithm as well as by incorporating features of other algorithms, such as SAGE and RIMAX.

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arXiv2021

Channel Rank Improvement in Urban Drone Corridors Using Passive Intelligent Reflectors

Multiple-input multiple-output (MIMO) techniques can help in scaling the achievable air-to-ground (A2G) channel capacity while communicating with drones. However, spatial multiplexing with drones suffers from rank deficient channels due to the unobstructed line-of-sight (LoS), especially in millimeter-wave (mmWave) frequencies that use narrow beams. One possible solution is utilizing low-cost and low-complexity metamaterial-based intelligent reflecting surfaces (IRS) to enrich the multipath environment, taking into account that the drones are restricted to fly only within well-defined drone corridors. A hurdle with this solution is placing the IRSs optimally. In this study, we propose an approach for IRS placement with a goal to improve the spatial multiplexing gains, and hence to maximize the average channel capacity in a predefined drone corridor. Our results at 6 GHz, 28 GHz and 60 GHz show that the proposed approach increases the average rates for all frequency bands for a given drone corridor, when compared with the environment where there are no IRSs present, and IRS-aided channels perform close to each other at sub-6 and mmWave bands.

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arXiv2021

Sub-Terahertz and mmWave Penetration Loss Measurements for Indoor Environments

Millimeter-wave (mmWave) and terahertz (THz) spectrum can support significantly higher data rates compared to lower frequency bands and hence are being actively considered for 5G wireless networks and beyond. These bands have high free-space path loss (FSPL) in line-of-sight (LOS) propagation due to their shorter wavelength. Moreover, in non-line-of-sight (NLOS) scenario, these two bands suffer higher penetration loss than lower frequency bands which could seriously affect the network coverage. It is therefore critical to study the NLOS penetration loss introduced by different building materials at mmWave and THz bands, to help establish link budgets for an accurate performance analysis in indoor environments. In this work, we measured the penetration loss and the attenuation of several common constructional materials at mmWave (28 and 39 GHz) and sub-THz (120 and 144 GHz) bands. Measurements were conducted using a channel sounder based on NI PXI platforms. Results show that the penetration loss changes extensively based on the frequency and the material properties, ranging from 0.401 dB for ceiling tile at 28 GHz, to 16.608 dB for plywood at 144 GHz. Ceiling tile has the lowest measured attenuation at 28 GHz, while clear glass has the highest attenuation of 27.633 dB/cm at 144 GHz. As expected, the penetration loss and attenuation increased with frequency for all the tested materials.

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arXiv2021

28 GHz Indoor and Outdoor Propagation Analysis at a Regional Airport

In the upcoming 5G communication, the millimeter-wave (mmWave) technology will play an important role due to its large bandwidth and high data rate. However, mmWave frequencies have higher free-space path loss (FSPL) in line-of-sight (LOS) propagation compared to the currently used sub-6 GHz frequencies. What is more, in non-line-of-sight (NLOS) propagation, the attenuation of mmWave is larger compared to the lower frequencies, which can seriously degrade the performance. It is therefore necessary to investigate mmWave propagation characteristics for a given deployment scenario to understand coverage and rate performance for that environment. In this paper, we focus on 28 GHz wideband mmWave signal propagation characteristics at Johnston Regional Airport (JNX), a local airport near Raleigh, NC. To collect data, we use an NI PXI based channel sounder at 28 GHz for indoor, outdoor, and indoor-to-outdoor scenarios. Results on LOS propagation, reflection, penetration, signal coverage, and multi-path components (MPCs) show a lower indoor FSPL, a richer scattering, and a better coverage compared to outdoor. We also observe high indoor-to-outdoor propagation losses.

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arXiv2020

Base Station and Passive Reflectors Placement for Urban mmWave Networks

The use of millimeter-wave (mmWave) bands in 5G networks introduce a new set of challenges to network planning. Vulnerability to blockages and high path loss at mmWave frequencies require careful planning of the network to achieve the desired service quality. In this paper, we propose a novel 3D geometry-based framework for deploying mmWave base stations (gNBs) in urban environments by considering first-order reflection effects. We also provide a solution for the optimum deployment of passive metallic reflectors (PMRs) to extend radio coverage to non-line-of-sight (NLoS) areas. In particular, we perform visibility analysis to find the direct and indirect visibility regions, and using these, we derive a geometry-and-blockage-aided path loss model. We then formulate the network planning problem as two independent optimization problems, placement of gNB(s) and PMRs, to maximize the coverage area with a certain quality-of-service constraint and minimum cost. We test the efficacy of our proposed approach using a generic map and compare our simulation results with the ray-tracing solution. Our simulation results show that considering the first-order reflections in planning the mmWave network helps reduce the number of PMRs required to cover the NLoS area and the gNB placement aided with PMRs requires fewer gNBs to cover the same area, which in turn reduces the deployment cost.

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arXiv2020

EMR: A New Metric to Assess the Resilience of Directional mmWave Channels to Blockages

Millimeter-wave (mmWave) communication systems require narrow beams to increase communication range. If the dominant communication direction is blocked by an obstacle, an alternative and reliable spatial communication path should be quickly identified to maintain connectivity. In this paper, we introduce a new metric to quantify the effective multipath richness (EMR) of a directional communication channel by considering the strength and spatial diversity of the resolved paths, while also taking into account beamwidth and blockage characteristics. The metric is defined as a weighted sum of the number of multipath component (MPC) clusters, where clustering is performed based on the cosine-distance between the MPCs that have power above a certain threshold. This process returns a single scalar value for a transmitter (TX)/receiver (RX) location pair in a given environment. It is also possible to represent the EMR of the whole environment with a probability distribution function of the metric by considering a set of TX/RX locations. Using this proposed metric, one can assess the scattering richness of different communication environments to achieve a particular quality of service (QoS). This metric is especially informative and useful at higher frequencies, such as mmWave and terahertz (THz), where the propagation path loss and penetration loss are high, and directional non-light-of-sight (NLOS) communication is critical for the success of the network. We evaluate the proposed metric using our channel measurements at 28 GHz in a large indoor environment at a library setting for LOS and NLOS scenarios.

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arXiv2020

RF-Based Low-SNR Classification of UAVs Using Convolutional Neural Networks

This paper investigates the problem of classification of unmanned aerial vehicles (UAVs) from radio frequency (RF) fingerprints at the low signal-to-noise ratio (SNR) regime. We use convolutional neural networks (CNNs) trained with both RF time-series images and the spectrograms of 15 different off-the-shelf drone controller RF signals. When using time-series signal images, the CNN extracts features from the signal transient and envelope. As the SNR decreases, this approach fails dramatically because the information in the transient is lost in the noise, and the envelope is distorted heavily. In contrast to time-series representation of the RF signals, with spectrograms, it is possible to focus only on the desired frequency interval, i.e., 2.4 GHz ISM band, and filter out any other signal component outside of this band. These advantages provide a notable performance improvement over the time-series signals-based methods. To further increase the classification accuracy of the spectrogram-based CNN, we denoise the spectrogram images by truncating them to a limited spectral density interval. Creating a single model using spectrogram images of noisy signals and tuning the CNN model parameters, we achieve a classification accuracy varying from 92% to 100% for an SNR range from -10 dB to 30 dB, which significantly outperforms the existing approaches to our best knowledge.

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arXiv2020

Outdoor mmWave Base Station Placement: A Multi-Armed Bandit Learning Approach

Base station (BS) placement in mobile networks is critical to the efficient use of resources in any communication system and one of the main factors that determines the quality of communication. Although there is ample literature on the optimum placement of BSs for sub-6 GHz bands, channel propagation characteristics, such as penetration loss, are notably different in millimeter-wave (mmWave) bands than in sub-6 GHz bands. Therefore, designated solutions are needed for mmWave systems to have reliable quality of service (QoS) assessment. This article proposes a multi-armed bandit (MAB) learning approach for the mmWave BS placement problem. The proposed solution performs viewshed analysis to identify the areas that are visible to a given BS location by considering the 3D geometry of the outdoor environments. Coverage probability, which is used as the QoS metric, is calculated using the appropriate path loss model depending on the viewshed analysis and a probabilistic blockage model and then fed to the MAB learning mechanism. The optimum BS location is then determined based on the expected reward that the candidate locations attain at the end of the training process. Unlike the optimization-based techniques, this method can capture the time-varying behavior of the channel and find the optimal BS locations that maximize long-term performance.

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arXiv2020

UAV Aided Search and Rescue Operation Using Reinforcement Learning

Owing to the enhanced flexibility in deployment and decreasing costs of manufacturing, the demand for unmanned aerial vehicles (UAVs) is expected to soar in the upcoming years. In this paper, we explore a UAV aided search and rescue~(SAR) operation in indoor environments, where the GPS signals might not be reliable. We consider a SAR scenario where the UAV tries to locate a victim trapped in an indoor environment by sensing the RF signals emitted from a smart device owned by the victim. To locate the victim as fast as possible, we leverage tools from reinforcement learning~(RL). Received signal strength~(RSS) at the UAV depends on the distance from the source, indoor shadowing, and fading parameters, and antenna radiation pattern of the receiver mounted on the UAV. To make our analysis more realistic, we model two indoor scenarios with different dimensions using commercial ray-tracing software. Then, the corresponding RSS values at each possible discrete UAV location are extracted and used in a Q-learning framework. Unlike the traditional location-based navigation approach that exploits GPS coordinates, our method uses the RSS to define the states and rewards of the RL algorithm. We compare the performance of the proposed method where directional and omnidirectional antennas are used. The results reveal that the use of directional antennas provides faster convergence rates than the omnidirectional antennas.

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arXiv2020

28 GHz mmWave Channel Measurements: A Comparison of Horn and Phased Array Antennas and Coverage Enhancement Using Passive and Active Repeaters

Propagation channel characteristics are substantially different in sub-6 GHz and millimeter-wave (mmWave) bands. A typical mmWave link experiences more than an order-of-magnitude larger path loss and is more susceptible to blockages than a traditional sub-6 GHz link. Therefore, extensive measurement campaigns with efficient channel sounders are needed for a complete understanding of the mmWave propagation channel characteristics. In addition, solutions should be sought to overcome the outage problems associated with the mmWave bands and to achieve acceptable communication performance. In this paper, our 28 GHz channel sounder is introduced that can be used with horn antennas as well as phased array antennas. The two antenna types are then compared in terms of speed they switch from one direction to another and extracted multipath component (MPC) properties, such as path gain. We then propose the use of passive reflectors and an active repeater for coverage enhancement by improving the received signal strength. In particular, ECHO reflector and TURBO repeater are introduced, and measurement results using them are presented.

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arXiv2020

Multiple Ray Received Power Modeling for mmWave Indoor and Outdoor Scenarios

Millimeter-wave (mmWave) frequency bands are expected to be used for future 5G networks due to the availability of large unused spectrum. However, the attenuation at mmWave frequencies is high. To resolve this issue, the utilization of high gain antennas and beamforming mechanisms are widely investigated in the literature. In this work, we considered mmWave end-to-end propagation modeled by individual ray sources, and explored the effects of the number of rays in the model and radiation patterns of the deployed antennas on the received power. It is shown that taking the dominant two rays is sufficient to model the channel for outdoor open areas as opposed to the indoor corridor which needs five dominant rays to have a good fit for the measurement and simulation results. It is observed that the radiation pattern of the antenna affects the slope of the path loss. Multi-path components increase the received power, thus, for indoor corridor scenarios, path loss according to the link distance is smaller for lower gain antennas due to increased reception of reflected components. For an outdoor open area, the slope of the path loss is found to be very close to that of the free space.

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arXiv2019

28 GHz mmWave Channel Measurements and Modeling in a Library Environment

To fully exploit the millimeter-wave bands for the fifth generation cellular systems, an accurate understanding of the channel propagation characteristics is required, and hence extensive measurement campaigns in different environments are needed. In this paper, we use a rotated directional antenna-based channel sounder for measurements at 28 GHz in large indoor environments at a library setting. We present models for power angular-delay profile and large-scale path loss based on the measurements over distances ranging from 10 m to 50 m. In total, nineteen different line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are considered, including the cases where the transmitter and the receiver are placed on different floors. Results show that the close-in free space reference distance and the floating intercept path loss models both perform well in fitting the empirical data. The path loss exponent obtained for the LOS scenarios is found to be very close to that of the free space path loss model.

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arXiv2019

Adaptive Kalman Tracking for Indoor Visible Light Positioning

Visible light communication (VLC) utilizes light-emitting diodes (LEDs) to transmit wireless data. A VLC network can also be used to localize mobile users in indoor environments, where the global positioning system (GPS) signals are weak. However, the line-of-sight (LOS) links of mobile VLC devices can be blocked easily, which decreases the accuracy of localization. In this paper, we study tracking a VLC user when the availability of VLC access point (AP) link changes over the user's route. We propose a localization method for a single available AP and use known estimation methods when a larger number of APs are available. Tracking mobile users with Kalman filter can increase the accuracy of the positioning, but the generic Kalman filter does not consider instant changes in the measurement method. In order to include this information in the position estimation, we implement an adaptive Kalman filter by modifying the filter parameters based on the availability of APs to the user. Simulation results show that the implemented method decreases the root-mean-square error (RMSE) of the localization down to 30%-50% of the original estimation.

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arXiv2019

Detection and Classification of UAVs Using RF Fingerprints in the Presence of Interference

This paper investigates the problem of detection and classification of unmanned aerial vehicles (UAVs) in the presence of wireless interference signals using a passive radio frequency (RF) surveillance system. The system uses a multistage detector to distinguish signals transmitted by a UAV controller from the background noise and interference signals. First, RF signals from any source are detected using a Markov models-based naïve Bayes decision mechanism. When the receiver operates at a signal-to-noise ratio (SNR) of 10 dB, and the threshold, which defines the states of the models, is set at a level 3.5 times the standard deviation of the preprocessed noise data, a detection accuracy of 99.8% with a false alarm rate of 2.8% is achieved. Second, signals from Wi-Fi and Bluetooth emitters, if present, are detected based on the bandwidth and modulation features of the detected RF signal. Once the input signal is identified as a UAV controller signal, it is classified using machine learning (ML) techniques. Fifteen statistical features extracted from the energy transients of the UAV controller signals are fed to neighborhood component analysis (NCA), and the three most significant features are selected. The performance of the NCA and five different ML classifiers are studied for 15 different types of UAV controllers. A classification accuracy of 98.13% is achieved by k-nearest neighbor classifier at 25 dB SNR. Classification performance is also investigated at different SNR levels and for a set of 17 UAV controllers which includes two pairs from the same UAV controller models.

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arXiv2019

Vehicular LTE Connectivity Analysis in Urban and Rural Environments using USRP Measurements

The intelligent transportation system (ITS) offers a wide range of applications related to traffic management, which often require high data rate and low latency. The ubiquitous coverage and advancements of the Long Term Evolution (LTE) technology have made it possible to achieve these requirements and to enable broadband applications for vehicular users. In this paper, we perform field trial measurements in various different commercial LTE networks using software defined radios (SDRs) and report our findings. First, we provide a detailed tutorial overview on how to post-process SDR measurements for decoding broadcast channels and reference signal measurements from LTE networks. We subsequently describe the details of our measurement campaigns in urban, sub-urban, and rural environments. Based on these measurements, we report joint distributions of base station density, cellular coverage, link strength, disconnected vehicle duration, and vehicle velocity in these environments, and compare the LTE coverage in different settings. Our experimental results quantify the stronger coverage, shorter link distances, and shorter duration of disconnectivity in urban environments when compared to sub-urban and rural settings.

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arXiv2019

Correction of Channel Sounding Clock Drift and Antenna Rotation Effects for mmWave Angular Profile Measurements

Millimeter-wave (mmWave) bands will be used for the fifth generation communication systems to support high data rates. For the proper characterization of the mmWave propagation channel, it is essential to measure the power angular-delay profile (PADP) of the channel which includes angle-of-departure (AoD) and angle-of-arrival (AoA) of the multipath components (MPCs). In this paper, we first describe in detail our 28 GHz channel sounder where directional horn antennas are placed on rotating gimbals. Then, for this specific sounder class, we describe and address the following two problems in extracting the MPCs from the measurements: 1) For the channel measurements at large distances between the transmitter (TX) and the receiver (RX), it is not possible to generate the triggering signal for the TX and the RX using a single clock (SICL). This necessitates the use of separate clocks (SECLs) which introduces a random timing drift between the clocks. 2) As the positions of the antennas change during the scanning process, total distance traveled by the same MPC differs at each measurement. These two errors together cause missing some of the MPCs and detecting MPCs that do not exist in reality. We propose an algorithm to correct the clock drift and the errors in the MPC delays due to the rotation of the antennas. We compare the MPCs from the SICL measurement and the corrected SECL measurements using a Hungarian algorithm based MPC matching method. We show that the percentage of the matched MPCs increases from 28.36% to 74.13% after the correction process.

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