Browsing by Author "Dietrich, Carl B."
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- 6 GHz Spectrum Sharing between Fixed Microwave Links and Indoor Positioning SystemsIsaac, Benedict (Virginia Tech, 2023-07-13)
- Adaptive Arrays and Diversity Antenna Configurations for Handheld Wireless Communication TerminalsDietrich, Carl B. (Virginia Tech, 2000-02-15)This dissertation reports results of an investigation into the performance of adaptive beamforming and diversity combining using antenna arrays that can be mounted on handheld radios. Handheld arrays show great promise for improving the coverage, capacity, and power efficiency of wireless communication systems. Diversity experiments using a handheld antenna array testbed (HAAT) are reported here. These experiments indicate that signals received by the antennas in two-element handheld antenna arrays with spacing of 0.15 wavelength or greater can be combined to provide 7-9 dB diversity gain against fading at the 99% reliability level in non line-of-sight multipath channels. Thus, peer-to-peer systems of handheld transceivers that use antenna arrays can achieve reliability comparable to systems of single-antenna handheld units, with only one-fifth the transmitter power, resulting in lower overall power consumption and increased battery life. Similar gains were observed for spatial, polarization, and pattern diversity. Adaptive beamforming with single- and multi-polarized four-element arrays of closely spaced elements was investigated by experiment using the HAAT, and by computer simulation using a polarization-sensitive vector multipath propagation simulator developed for this purpose. Small and handheld adaptive arrays were shown to provide 25 to 40 dB or more of interference rejection in the presence of a single interferer in rural, suburban, and urban channels including line-of-sight and non line-of-sight cases. In multipath channels, these performance levels were achieved even when there was no separation between the transmitters in azimuth angle as seen from the receiver, and no difference in the orientations of the two transmitting antennas. This interference rejection capability potentially allows two separate spatial channels to coexist in the same time/frequency channel, doubling system capacity.
- Application of Machine Learning to Multi Antenna Transmission and Machine Type Resource AllocationEmenonye, Don-Roberts Ugochukwu (Virginia Tech, 2020-09-11)Wireless communication systems is a well-researched area in electrical engineering that has continually evolved over the past decades. This constant evolution and development have led to well-formulated theoretical baselines in terms of reliability and efficiency. However, most communication baselines are derived by splitting the baseband communications into a series of modular blocks like modulation, coding, channel estimation, and orthogonal frequency modulation. Subsequently, these blocks are independently optimized. Although this has led to a very efficient and reliable process, a theoretical verification of the optimality of this design process is not feasible due to the complexities of each individual block. In this work, we propose two modifications to these conventional wireless systems. First, with the goal of designing better space-time block codes for improved reliability, we propose to redesign the transmit and receive blocks of the physical layer. We replace a portion of the transmit chain - from modulation to antenna mapping with a neural network. Similarly, the receiver/decoder is also replaced with a neural network. In other words, the first part of this work focuses on jointly optimizing the transmit and receive blocks to produce a set of space-time codes that are resilient to Rayleigh fading channels. We compare our results to the conventional orthogonal space-time block codes for multiple antenna configurations. The second part of this work investigates the possibility of designing a distributed multiagent reinforcement learning-based multi-access algorithm for machine type communication. This work recognizes that cellular networks are being proposed as a solution for the connectivity of machine type devices (MTDs) and one of the most crucial aspects of scheduling in cellular connectivity is the random access procedure. The random access process is used by conventional cellular users to receive an allocation for the uplink transmissions. This process usually requires six resource blocks. It is efficient for cellular users to perform this process because transmission of cellular data usually requires more than six resource blocks. Hence, it is relatively efficient to perform the random access process in order to establish a connection. Moreover, as long as cellular users maintain synchronization, they do not have to undertake the random access process every time they have data to transmit. They can maintain a connection with the base station through discontinuous reception. On the other hand, the random access process is unsuitable for MTDs because MTDs usually have small-sized packets. Hence, performing the random access process to transmit such small-sized packets is highly inefficient. Also, most MTDs are power constrained, thus they turn off when they have no data to transmit. This means that they lose their connection and can't maintain any form of discontinuous reception. Hence, they perform the random process each time they have data to transmit. Due to these observations, explicit scheduling is undesirable for MTC. To overcome these challenges, we propose bypassing the entire scheduling process by using a grant free resource allocation scheme. In this scheme, MTDs pseudo-randomly transmit their data in random access slots. Note that this results in the possibility of a large number of collisions during the random access slots. To alleviate the resulting congestion, we exploit a heterogeneous network and investigate the optimal MTD-BS association which minimizes the long term congestion experienced in the overall cellular network. Our results show that we can derive the optimal MTD-BS association when the number of MTDs is less than the total number of random access slots.
- Automatic Generation of Efficient Parallel Streaming Structures for Hardware ImplementationKoehn, Thaddeus E. (Virginia Tech, 2016-11-30)Digital signal processing systems demand higher computational performance and more operations per second than ever before, and this trend is not expected to end any time soon. Processing architectures must adapt in order to meet these demands. The two techniques most prevalent for achieving throughput constraints are parallel processing and stream processing. By combining these techniques, significant throughput improvements have been achieved. These preliminary results apply to specific applications, and general tools for automation are in their infancy. In this dissertation techniques are developed to automatically generate efficient parallel streaming hardware architectures.
- Black-Box Fuzzing of the REDHAWK Software Communications ArchitectureSayed, Shereef (Virginia Tech, 2015-07-17)As the complexity of software increases, so does the complexity of software testing. This challenge is especially true for modern military communications as radio functionality becomes more digital than analog. The Software Communications Architecture was introduced to manage the increased complexity of software radios. But the challenge of testing software radios still remains. A common methodology of software testing is the unit test. However, unit testing of software assumes that the software under test can be decomposed into its fundamental units of work. The intention of such decomposition is to simplify the problem of identifying the set of test cases needed to demonstrate correct behavior. In practice, large software efforts can rarely be decomposed in simple and obvious ways. In this paper, we introduce the fuzzing methodology of software testing as it applies to software radios. Fuzzing is a methodology that acts only on the inputs of a system and iteratively generates new test cases in order to identify points of failure in the system under test. The REDHAWK implementation of the Software Communications Architecture is employed as the system under test by a fuzzing framework called Peach. Fuzz testing of REDHAWK identified a software bug within the Core Framework, along with a systemic flaw that leaves the system in an invalid state and open to malicious use. It is recommended that a form of Fault Detection be integrated into REDHAWK for collocated processes at a minimum, and distributed processes at best, in order to provide a more fault tolerant system.
- Cellular-Assisted Vehicular Communications: A Stochastic Geometric ApproachGuha, Sayantan (Virginia Tech, 2016-02-04)A major component of future communication systems is vehicle-to-vehicle (V2V) communications, in which vehicles along roadways transfer information directly among themselves and with roadside infrastructure. Despite its numerous potential advantages, V2V communication suffers from one inherent shortcoming: the stochastic and time-varying nature of the node distributions in a vehicular ad hoc network (VANET) often leads to loss of connectivity and lower coverage. One possible way to improve this coverage is to allow the vehicular nodes to connect to the more reliable cellular network, especially in cases of loss of connectivity in the vehicular network. In this thesis, we analyze this possibility of boosting performance of VANETs, especially their node coverage, by taking assistance from the cellular network. The spatial locations of the vehicular nodes in a VANET exhibit a unique characteristic: they always lie on roadways, which are predominantly linear but are irregularly placed on a two dimensional plane. While there has been a signifcant work on modeling wireless networks using random spatial models, most of it uses homogeneous planar Poisson Point Process (PPP) to maintain tractability, which is clearly not applicable to VANETs. Therefore, to accurately capture the spatial distribution of vehicles in a VANET, we model the roads using the so called Poisson Line Process and then place vehicles randomly on each road according to a one-dimensional homogeneous PPP. As is usually the case, the locations of the cellular base stations are modeled by a planar two-dimensional PPP. Therefore, in this thesis, we propose a new two-tier model for cellular-assisted VANETs, where the cellular base stations form a planar PPP and the vehicular nodes form a one-dimensional PPP on roads modeled as undirected lines according to a Poisson Line Process. The key contribution of this thesis is the stochastic geometric analysis of a maximum power-based cellular-assisted VANET scheme, in which a vehicle receives information from either the nearest vehicle or the nearest cellular base station, based on the received power. We have characterized the network interference and obtained expressions for coverage probability in this cellular-assisted VANET, and successfully demonstrated that using this switching technique can provide a significant improvement in coverage and thus provide better vehicular network performance in the future. In addition, this thesis also analyzes two threshold-distance based schemes which trade off network coverage for a reduction in additional cellular network load; notably, these schemes also outperform traditional vehicular networks that do not use any cellular assistance. Thus, this thesis mathematically validates the possibility of improving VANET performance using cellular networks.
- Channel Propagation Model for Train to Vehicle Alert System at 5.9 GHz using Dedicated Short Range CommunicationRowe, Christopher D. (Virginia Tech, 2016-10-07)The most common railroad accidents today involve collisions between trains and passenger vehicles at railroad grade crossings [1][2]. Due to the size and speed of a train, these collisions generally result in significant damage and serious injury. Despite recent efforts by projects such as Operation Lifesaver to install safety features at grade crossings, up to 80% of the United States railroad grade crossings are classified as 'unprotected' with no lights, warnings, or crossing gates [2]. Further, from January to September 2012, nearly 10% of all reported vehicle accidents were a result of train-to-vehicle collisions. These collisions also accounted for nearly 95% of all reported fatalities from vehicular accidents [2]. To help provide a more rapidly deployable safety system, advanced dedicated short range communication (DSRC) systems are being developed. DSRC is an emerging technology that is currently being explored by the automotive safety industry for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications to provide intelligent transportation services (ITS). DSRC uses WAVE protocols and the IEEE 1609 standards. Among the many features of DSRC systems is the ability to sense and then provide an early warning of a potential collision [6]. One potential adaption for this technology is for use as a train-to-vehicle collision warning system for unprotected grade crossings. These new protocols pose an interesting opportunity for enhancing cybersecurity since terrorists will undoubtedly eventually identify these types of mass disasters as targets of opportunity. To provide a thorough channel model of the train to vehicle communication environment that is proposed above, large-scale path loss and small scale fading will both be analyzed to characterize the propagation environment. Measurements were collected at TTCI in Pueblo Colorado to measure the received signal strength in a train to vehicle communication environment. From the received signal strength, different channel models can be developed to characterize the communication environment. Documented metrics include large scale path loss, Rician small scale fading, Delay spread, and Doppler spread. An analysis of the DSRC performance based on Packet Error Rate is also included.
- Coexistence of Wireless Systems for Spectrum SharingKim, Seungmo (Virginia Tech, 2017-07-28)Sharing a band of frequencies in the radio spectrum among multiple wireless systems has emerged as a viable solution for alleviating the severe capacity crunch in next-generation wireless mobile networks such as 5th generation mobile networks (5G). Spectrum sharing can be achieved by enabling multiple wireless systems to coexist in a single spectrum band. In this dissertation, we discuss the following coexistence problems in spectrum bands that have recently been raising notable research interest: 5G and Fixed Satellite Service (FSS) at 27.5-28.35 GHz (28 GHz); 5G and Fixed Service (FS) at 71-76 GHz (70 GHz); vehicular communications and Wi-Fi at 5.85-5.925 GHz (5.9 GHz); and mobile broadband communications and radar at 3.55-3.7 GHz (3.5 GHz). The results presented in each of the aforementioned parts show comprehensively that the coexistence methods help achieve spectrum sharing in each of the bands, and therefore contribute to achieve appreciable increase of bandwidth efficiency. The proposed techniques can contribute to making spectrum sharing a viable solution for the ever evolving capacity demands in the wireless communications landscape.
- Cognitive Radio Network Testbed: Design, Deployment, Administration and ExamplesDePoy, Daniel R. (Virginia Tech, 2012-05-29)Development of Cognitive Radio (CR) applications, which rely on a radio's ability to adapt intelligently to it's spectral surroundings will soon make the all important technological jump from research interest to systems integration, as demand for highly adaptive wireless applications expand. VT-CORNET (Virginia Tech – Cognitive Radio Network Testbed) is a unique testbed concept, designed to facilitate this technology leap by offering researchers — both local and remote — the opportunity to conduct CR experiments on an installed infrastructure of highly flexible radio nodes. These nodes — 48 in total — are distributed throughout four floors of a building on the Virginia Tech campus, and provide researchers with diverse options in terms of channel conditions and deployment scenarios. The radios themselves consist of the widely used USRP2 Software Defined Radio (SDR) platform, coupled to a centrally located cluster of rack servers — which provide a high performance GPP environment for real-time software based signal processing. VT-CORNET is specially licensed to operate our low-power nodes over a broad range of frequencies, which provides researcher the opportunity to conduct experiments on live spectrum — in the presence of real primary users. Testbeds are a widely used tool in the wireless and networking fields, and VT-CORNET expands the concept through a focus on CR research and education. This thesis describes the construction and deployment of the CORNET testbed in detail. Specific contributions made to the testbed include the design and implementation of the management network, as well as the initial deployment of the SDR nodes in the ceiling. In addition, this thesis describes the administration and management of the CORNET GPP cluster, and provides a instructions for the basic usage of CORNET from an administrative and user perspective. Finally, this thesis describes a number of custom SDR waveforms implemented on CORNET which demonstrate the utility of the testbed for cognitive radio applications.
- Component-Based Design and Service-Oriented Architectures in Software-Defined RadioHilburn, Benjamin Cantrell (Virginia Tech, 2011-04-22)Software-Defined Radio (SDR) is a large field of research, and is rapidly expanding in terms of capabilities and applications. As the number of SDR platforms, deployments, and use-cases grow, interoperability, compatibility, and software re-use becomes more difficult. Additionally, advanced SDR applications require more advanced hardware and software platforms to support them, necessitating intelligent management of resources and functionality. Realizing these goals can be done using the paradigms of Component-Based Design (CBD) and Service-Oriented Architectures (SOAs). Component-based design has been applied to the field of SDR in the past to varying levels of success. We discuss the benefits of CBD, and how to successfully use CBD for SDR. We assert that by strictly enforcing the principles of CBD, we can achieve a high level of independence from both the hardware and software platforms, and enable component compatibility and interoperability between SDR platforms and deployments. Using CBD, we also achieve the use-case of a fully distributed SDR, where multiple hardware nodes act as one cohesive radio unit. Applying the concept of service-orientation to SDR is a novel idea, and we discuss how this enables a new radio paradigm in the form of goal-oriented autonomic radios. We define SOAs in the context of SDR, explain how our vision is different than middle-wares like CORBA, describe how SOAs can be used, and discuss the possibilities of autonomic radio systems. This thesis also presents our work on the Cognitive Radio Open Source Systems (CROSS) project. CROSS is a free and open-source prototype architecture that uses CBD to achieve platform independence and distributed SDR deployments. CROSS also provides an experimental system for using SOAs in SDRs. Using our reference implementation of CROSS, we successfully demonstrated a distributed cognitive radio performing dynamic spectrum access to communicate with another SDR while avoiding an interferer operating in the spectrum.
- A Comprehensive Analysis of Deep Learning for Interference Suppression, Sample and Model Complexity in Wireless SystemsOyedare, Taiwo Remilekun (Virginia Tech, 2024-03-12)The wireless spectrum is limited and the demand for its use is increasing due to technological advancements in wireless communication, resulting in persistent interference issues. Despite progress in addressing interference, it remains a challenge for effective spectrum usage, particularly in the use of license-free and managed shared bands and other opportunistic spectrum access solutions. Therefore, efficient and interference-resistant spectrum usage schemes are critical. In the past, most interference solutions have relied on avoidance techniques and expert system-based mitigation approaches. Recently, researchers have utilized artificial intelligence/machine learning techniques at the physical (PHY) layer, particularly deep learning, which suppress or compensate for the interfering signal rather than simply avoiding it. In addition, deep learning has been utilized by researchers in recent years to address various difficult problems in wireless communications such as, transmitter classification, interference classification and modulation recognition, amongst others. To this end, this dissertation presents a thorough analysis of deep learning techniques for interference classification and suppression, and it thoroughly examines complexity (sample and model) issues that arise from using deep learning. First, we address the knowledge gap in the literature with respect to the state-of-the-art in deep learning-based interference suppression. To account for the limitations of deep learning-based interference suppression techniques, we discuss several challenges, including lack of interpretability, the stochastic nature of the wireless channel, issues with open set recognition (OSR) and challenges with implementation. We also provide a technical discussion of the prominent deep learning algorithms proposed in the literature and also offer guidelines for their successful implementation. Next, we investigate convolutional neural network (CNN) architectures for interference and transmitter classification tasks. In particular, we utilize a CNN architecture to classify interference, investigate model complexity of CNN architectures for classifying homogeneous and heterogeneous devices and then examine their impact on test accuracy. Next, we explore the issues with sample size and sample quality with regards to the training data in deep learning. In doing this, we also propose a rule-of-thumb for transmitter classification using CNN based on the findings from our sample complexity study. Finally, in cases where interference cannot be avoided, it is important to suppress such interference. To achieve this, we build upon autoencoder work from other fields to design a convolutional neural network (CNN)-based autoencoder model to suppress interference thereby ensuring coexistence of different wireless technologies in both licensed and unlicensed bands.
- A Context-Aware Dynamic Spectrum Access System for Spectrum Research and DevelopmentKumar, Saurav (Virginia Tech, 2024-01-03)Our hunger for data has grown tremendously over the years which has led to a demand for the increase in the available radio spectrum for communications. The Federal Communications Commission in the United States allowed for the sharing of the CBRS band (3550-3700 MHz) a few years ago. Since then, research has been done by both industry and academia to identify similar opportunities in other radio bands as well. This research is, however, being hampered due to a lack of experimental frameworks where the various aspects of spectrum sharing can be studied. To this end, we propose to develop an open-source spectrum access system that incorporates context awareness and multi-band operational support and serves as an RandD tool for the research community. We have developed a novel Prioritization Framework that takes the current operational context of each user into account to determine their relative priority, within or outside their user class/group, for transmission in the network. We also introduce a Policy Engine for the configuration and management of dynamic policies (or rules) for defining the relationships between the various forms of context information and their relative impact on a user's overall priority. We have performed several experiments to show how context awareness impacts the spectrum sharing efficiency and quality of service. Due to its modular and extensible nature, we expect that this tool will be used by researchers and policy-makers to implement their own policies and algorithms and test their efficacy in a simulated radio environment.
- Design and Implementation of a Constant Envelope OFDM Waveform in a Software-Defined Radio PlatformAjo Jr, Amos V. (Virginia Tech, 2016-06-30)This thesis examines the high peak-to-average-power ratio (PAPR) problem of OFDM and other spectrally-efficient multicarrier modulation schemes, specifically their stringent requirements for highly linear, power-inefficient amplification. The thesis then presents a most intriguing answer to the PAPR-problem in the form of a constant-envelope OFDM (CE-OFDM) waveform, a waveform which employs phase modulation to transform the high-PAPR OFDM signal into a constant envelope signal, like FSK or GMSK, which can be amplified with non-linear power amplifiers at near saturation levels of efficiency. A brief analytical description of CE-OFDM and its suboptimal receiver architecture is provided in order to define and analyze the key parameters of the waveform and their performance impacts. The primary contribution of this thesis is a highly tunable software-defined radio (SDR) implementation of the waveform which enables rapid-prototyping and testing of CE-OFDM systems. The digital baseband processing of the waveform is executed on a general purpose processor (GPP) in the Linux Ubuntu 14.04 operating system, and programmed using the GNU Radio SDR software framework with a mixture of Python and C++ routines. A detailed description of the software implementation is provided, and baseband simulations of the SDR CE-OFDM receiver in additive white Gaussian noise (AWGN) validate the performance of the implemented signal processing. A fully-functional CE-OFDM radio system is proposed in which GPPs executing the software defined transmitter and receiver routines are interfaced with Ettus Universal Software Radio Peripheral (USRP) transceiver front ends. A software testbench is created to enable rapid configuration and testing of the CE-OFDM waveform over all permutations of its parameters, over both simulated and physical RF channels, to draw deeper insights into the characteristics of the waveform and the necessary design considerations and improvements for further development and deployment of CE-OFDM systems.
- Design and Implementation of a Distributed Tdoa-Based Geolocation System Using Ossie and Low-Cost Usrp BoardsMeuleners, Michael (Virginia Tech, 2012-05-02)The Software Communications Architecture (SCA) specification defines a framework that allows modular software components to be developed and assembled to build larger radio applications. The specification allows for these components to be distributed among a set of computing hardware and to be connected by standard interfaces. This research aims to build a spatially distributed SCA application for the Open Source SCA Implementation: Embedded (OSSIE) implementation using low-cost Universal Software Radio Peripheral (USRP) hardware. The system collects signals from multiple spatially distributed collection devices and use those signals to compute precision estimates for the location of emitters using time difference of arrival (TDOA) computations. Several OSSIE components and tools are developed to support this research. Results are presented showing the capabilities of the geolocation system.
- Design and Implementation of a MAC protocol for Wireless Distributed ComputingBera, Soumava (Virginia Tech, 2011-06-20)The idea of wireless distributed computing (WDC) is rapidly gaining recognition owing to its promising potential in military, public safety and commercial applications. This concept basically entails distributing a computationally intensive task that one radio device is assigned, among its neighboring peer radio devices. The added processing power of multiple radios can be harnessed to significantly reduce the time consumed in obtaining the results of the original complex task. Since the idea of wireless distributed computing depends on a radio device forming a network with its peers, it is imperative and necessary to have a medium access control (MAC) protocol for such networks which is capable of scheduling channel access by multiple radios in the network, ensuring reliable data transfer, incorporating rate adaptation as well as handling link failures. The thesis presented here elaborates the design and implementation of such a MAC protocol for WDC employed in a practical network of radio devices configurable through software. It also brings to light the design and implementation constraints and challenges faced in this endeavor and puts forward viable solutions.
- A Design Assembly Technique for FPGA Back-End AccelerationFrangieh, Tannous (Virginia Tech, 2012-09-28)Long wait times constitute a bottleneck limiting the number of compilation runs performed in a day, thus risking to restrict Field-Programmable Gate Array (FPGA) adaptation in modern computing platforms. This work presents an FPGA development paradigm that exploits logic variance and hierarchy as a means to increase FPGA productivity. The practical tasks of logic partitioning, placement and routing are examined and a resulting assembly framework, Quick Flow (qFlow), is implemented. Experiments show up to 10x speed-ups using the proposed paradigm compared to vendor tool flows.
- Design, Deployment and Performance of an Open Source Spectrum Access SystemKikamaze, Shem (Virginia Tech, 2018-11-01)Spectrum sharing is possible, but lacks R & D support for practical solutions that satisfy both the incumbent and secondary or opportunistic users. The author found a lack of an openly available framework supporting experimental research on the performance of a Spectrum Access System (SAS) and propose to build an open-source Software Defined Radio (SDR) based framework. This framework will test different dynamic spectrum scenarios in a wireless testbed. This thesis presents our Spectrum Access System prototype, discusses the design choices and trade-offs and provides a proof of concept implementation. We show that an Internet-accessible CORNET test bed provides the ideal platform for developing and testing the SAS functionality and its building blocks and offerss the hardware and software as a community resource for research and education. This design provides the necessary interfaces for researchers to develop and test their SAS-related modules, waveforms and scenarios.
- Dynamic Spectrum Access Network Simulation and Classification of Secondary User PropertiesRebholz, Matthew John (Virginia Tech, 2013-06-17)This thesis explores the use of the Naïve Bayesian classifier as a method of determining high-level information about secondary users in a Dynamic Spectrum Access (DSA) network using a low complexity channel sensing method. With a growing number of users generating an increased demand for broadband access, determining an efficient method for utilizing the limited available broadband is a developing current and future issue. One possible solution is DSA, which we simulate using the Universal DSA Network Simulator (UDNS), created by our team at Virginia Tech. However, DSA requires user devices to monitor large amounts of bandwidth, and the user devices are often limited in their acceptable size, weight, and power. This greatly limits the usable bandwidth when using complex channel sensing methods. Therefore, this thesis focuses on energy detection for channel sensing. Constraining computing requirements by operating with limited spectrum sensing equipment allows for efficient use of limited broadband by user devices. The research on using the Naïve Bayesian classifier coupled with energy detection and the UDNS serves as a strong starting point for supplementary work in the area of radio classification.
- Eigenspace Approach to Specific Emitter Identification of Orthogonal Frequency Division Multiplexing SignalsSahmel, Peter H. (Virginia Tech, 2011-11-16)Specific emitter identification is a technology used to uniquely identify a class of wireless devices, and in some cases a single device. Minute differences in the implementation of a wireless communication standard from one device manufacturer to another make it possi- ble to extract a wireless "fingerprint" from the transmitted signal. These differences may stem from imperfect radio frequency (RF) components such as filters and power amplifiers. However, the problem of identifying a wireless device through analysis of these key signal characteristics presents several difficulties from an algorithmic perspective. Given that the differences in these features can be extremely subtle, in general a high signal to noise ratio (SNR) is necessary for a sufficient probability of correct detection. If a sufficiently high SNR is not guaranteed, then some from of identification algorithm which operates well in low SNR conditions must be used. Cyclostationary analysis offers a method of specific emitter iden- tification through analysis of second order spectral correlation features which can perform well at relatively low SNRs. The eigenvector/eigenvalue decomposition (EVD) is capable of separating principal components from uncorrelated gaussian noise. This work proposes a technique of specific emitter identification which utilizes the principal components of the EVD of the spectral correlation function which has been arranged into a square matrix. An analysis of this EVD-based SEI technique is presented herein, and some limitations are identified. Analysis is constrained to orthogonal frequency division multiplexing (OFDM) using the IEEE 802.16 specification (used for WiMAX) as a guideline for a variety of pilot arrangements.
- Enabling CBRS experimentation and ML-based Incumbent Detection using OpenSASCollaco, Oren Rodney (Virginia Tech, 2023-07-03)In 2015, Federal Communications Commission (FCC) enabled shared commercial use of the 3.550-3.700 GHz band. A framework was developed to enable this spectrum-sharing capa- bility which included an automated frequency coordinator called Spectrum Access System (SAS). This work extends the open source SAS based on the aforementioned FCC SAS framework developed by researchers at Virginia Tech Wireless group, with real-time envi- ronment sensing capability along with intelligent incumbent detection using Software-defined Radios (SDRs) and a real-time graphical user interface. This extended version is called the OpenSAS. Furthermore, the SAS client and OpenSAS are extended to be compliant with the Wireless Innovation Forum (WINNF) specifications by testing the SAS-CBRS Base Station Device (CBSD) interface with the Google SAS Test Environment. The Environment Sensing Capability (ESC) functionality is evaluated and tested in our xG Testbed to verify its ability to detect the presence of users in the CBRS band. An ML-based feedforward neural net- work model is employed and trained using simulated radar waveforms as incumbent signals and captured 5G New Radio (NR) signals as a non-incumbent signal to predict whether the detected user is a radar incumbent or an unknown user. If the presence of incumbent radar is detected with an 85% or above certainty, incumbent protection is activated, terminating CBSD grants causing damaging interference to the detected incumbent. A 5G NR signal is used as a non-incumbent user and added to the training dataset to better the ability of the model to reject non-incumbent signals. The model achieves a maximum validation accuracy of 95.83% for signals in the 40-50 dB Signal-to-Noise Ratio (SNR) range. It achieves an 85.35% accuracy for Over the air (OTA) real-time tests. The non-incumbent 5G NR signal rejection accuracy is 91.30% for a calculated SNR range of 10-20 dB. In conclusion, this work advances state of the art in spectrum sharing systems by presenting an enhanced open source SAS and evaluating the newly added functionalities.
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