Recent disasters, including the 9/11 terrorist attacks, Hurricane Katrina, the London subway bombings, and the California wildfires, have all highlighted the limitations of current mobile communication systems for public safety first responders. First, in a point-to-point configuration, legacy radio systems used by first responders from differing agencies are often made by competing manufacturers and may use incompatible waveforms or channels. In addition, first responder radio systems, which may be licensed and programmed to operate in frequency bands allocated within their home jurisdiction, may be neither licensed nor available in forward-deployed disaster response locations, resulting in an operational scarcity of usable frequencies. To address these problems, first responders need smart radio solutions which can bridge these disparate legacy radio systems together, can incorporate new smart radio solutions, or can replace these existing aging radios. These smart radios need to quickly find each other and adhere to spectrum usage and access policies. Second, in an infrastructure configuration, legacy radio systems may not operate at all if the existing communications backbone has been destroyed by the disaster event. A communication system which can provide a new, temporary infrastructure or can extend an existing infrastructure into a shaded region is needed. Smart radio nodes that make up the public safety infrastructure again must be able to find each other, adhere to spectrum usage policies, and provide access to other smart radios and legacy public safety radios within their coverage area. This work addresses these communications problems in the following ways. First, it applies cognitive radio technology to develop a smart radio system capable of rapidly adapting itself so it can communicate with existing legacy radio systems or other smart radios using a variety of standard and customized waveforms. These smart radios can also assemble themselves into an ad-hoc network capable of providing a temporary communications backbone within the disaster area, or a network extension to a shaded communications area. Second, this work analyzes and characterizes a series of rendezvous protocols which enable the smart radios to rapidly find each other within a particular coverage area. Third, this work develops a spectrum sharing protocol that enables the smart radios to adhere to spectral policies by sharing spectrum with other primary users of the band. Fourth, the performance of the smart radio architecture, as well as the performance of the rendezvous and spectrum sharing protocols, is evaluated on a smart radio network testbed, which has been assembled in a laboratory setting. Results are compared, when applicable, to existing radio systems and protocols. Finally, this work concludes by briefly discussing how the smart radio technologies developed in this dissertation could be combined to form a public safety communications architecture, applicable to the FCC's stated intent for the 700 MHz Band. In the future, this work will be extended to applications outside of the public safety community, specifically, to communications problems faced by warfighters in the military. / Ph. D.

Software Defined Radios (SDRs) lend themselves to flexibility and extensibility because they<br />depend on software to implement radio functionality. Cognitive Engines (CEs) introduce<br />intelligence to radio by monitoring radio performance through a set of meters and configuring<br />the underlying radio design by modifying its knobs. In Cognitive Radio (CR) applications,<br />CEs intelligently monitor radio performance and reconfigure them to meet it application<br />and RF channel needs. While the issue of introducing computational knobs and meters<br />is mentioned in literature, there has been little work on the practical issues involved in<br />introducing such computational radio controls.<br /><br />This dissertation decomposes the radio definition to reactive models for the CE domain<br />and real-time, or dataflow models, for the SDR domain. By allowing such design space<br />decomposition, CEs are able to define implementation independent radio graphs and rely on<br />a model transformation layer to transform reactive radio models to real-time radio models<br />for implementation. The definition of knobs and meters in the CE domain is based on<br />properties of the dataflow models used in implementing SDRs. A framework for developing<br />this work is presented, and proof of concept radio applications are discussed to demonstrate<br />how CEs can gain insight into computational aspects of their radio implementation during<br />their reconfiguration decision process.<br /> / Ph. D.

With interoperability issues plaguing emergency responders throughout the country, Cognitive Radio (CR) offers a unique solution to streamline communication between police, Emergency Medical Technicians (EMT), and military officers. Using Software Defined Radio (SDR) technology, a flexible radio platform can be potentially configured using a Cognitive Engine (CE) to transmit and receive many different incompatible radio standards. In this thesis, an interface between a Cognitive Engine and an SDR platform is described which modifies (i.e., configures) the radio's operation. The interface is based upon communicating information via eXtensible Markup Language (XML) data files that contain the radio's Physical (PHY) parameters. The XML data files have been designed such that more development can be made to its structure as this research develops. The GNU Radio and the Universal Software Radio Peripheral (USRP) serve as the SDR platform for an example implementation. The example implementation involves importing XML data files into the SDR for quick configuration. Three configuration examples are used to describe this process. / Master of Science

The thesis work shows the implementation of sensing and communication, so a basic knowledge of analog and digital communication systems is needed to understand this paper Background. With the increase in smart devices, the bandwidth requirements are increased, which created congestion in the radio spectrum resources. To overcome this spectrum congestion, Integrated Sensing and Communication (ISAC) can be used. This can be achieved by using Orthogonal Frequency-Division Multiplexing (OFDM) signals. In ISAC, both sensing and communication use the same resources,which in turn predominantly improves the efficiency of the spectrum resources usage and reduces the cost of hardware. Objectives. The main aim of this research is to integrate radar sensing and communication using Software Defined Radios (SDR) and GNU Radio. The goal is to design a signal waveform and a receiver algorithm supporting both sensing and communications and then carry out experiments on an SDR unit to evaluate the functionality and performance. Methods. Experimentation is used in this research and is conducted at Ericsson Research Laboratory. The experiment is divided into three major parts. First, to test the sensing functionalities using Frequency Modulated Continuous Waves (FMCW). Second, to test the communication functionalities using OFDM signals. Third, to design the receiver algorithm and signal waveform for ISAC. To verify the dual functional paradigm, the results from the ISAC are compared with the individual test results of sensing and communications using FMCW and OFDM signals. Results. A receiver algorithm is designed to calculate the sensing range and BER of ISAC using an SDR. The results show the possibility of implementing ISAC using OFDM in GNU Radio with SDR. The thesis project can also be viewed as a proof of concept for ISAC on SDR, helping in providing useful information related to radar sensing and communication using OFDM and performance evaluation. Conclusions. The experimental results show the dual-functional waveform for ISAC, helping in the evolution of 5G and beyond 5G communication systems. The identified drawbacks can be used by future researchers working on advanced 5G mobile communication systems to develop more efficient systems. Keywords: Communications, FMCW, GNU Radio, ISAC, OFDM, SDR, Sensing.

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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. / Master of Science

The ionosphere is a constantly changing medium. From the sun to cosmic rays, the ionosphere proves to be a continually interesting area of study. The most notable change that occurs in the ionosphere is the day and night cycle. The ionosphere is not a singular medium, but rather made up of different sections. The day side of the ionosphere consists of a D, E, F1, and F2 layer. The night day of the ionosphere consists of an E and F layer. These layers all have different properties and characteristics associated with them. A notable interaction is how radio waves propagate through the ionosphere. A radio wave can either reflect, refract, or pass through a layer of the ionosphere depending on the frequency of the signal, among other sources of disturbance. The ability to have a radio wave reflected back downwards is a core principle of an ionosonde, which measures the height of the ionosphere. A solar eclipse presents a night side ionosphere condition during the day. The change in the ionosphere that the eclipse will cause is something not a lot of research has gone into. This thesis aims to elaborate on the design and development of an ionosonde along with eventual ionosphere readings during the August 2017 total solar eclipse. / Master of Science / The atmosphere that surrounds the earth is made up of various unique regions. The region of interest for this thesis is the ionosphere. The ionosphere plays an important role in wireless communication of radio waves. It follows that changes in the ionosphere are something of great interest and study. A notable change that the ionosphere undergoes on a daily basis is the shift from the day side to the night side. A solar eclipse serves not only as a spectacular sight, but also to bring a night side condition to the day side. This thesis aims to uncover the changes that will occur to the ionosphere during the August 2017 total solar eclipse.

Traditional hardware radios provide very rigid solutions to radio problems. Intelligent software defined radios, also known as cognitive radios, provide flexibility and agility compared to hardware radio systems. Cognitive radios are well suited for radio applications in a changing radio frequency environment, such as dynamic spectrum access. In this thesis, a cognitive radio is demonstrated where the system self reconfigures to demodulate a detected waveform. The GNU Radio framework is used to provide basic software defined radio building blocks and is supplemented with FPGA accelerators. The use of GNU Radio compliant hardware interfaces allows for seamless hardware/software radio deployments. Dynamic resource mapping allows radio designers to operate at a layer of abstraction above the physical radio implementation. By establishing lower level abstraction layers, future researchers can focus on larger picture concepts such as learning algorithms and behavioral models for the cognitive engine. / Master of Science