Cognitive radio (CR) is a multi-disciplinary field that makes use of knowledge from a multitude of specialties such as antenna design, circuits, systems and digital signal processing among many others. CR has emerged as an area of interest over 20 years ago and in the years since has evolved to encompass both realizable theory and physical hardware. Key among the latter are reconfigurable, software defined radios and embedded sensors that incorporate flexible parameters, allowing a CR to operate in a wide variety of electromagnetic (EM) environments.
The ideal cognitive radio would be capable of adapting to a changing EM environment without any specific knowledge or direction from the operator. This would require the radio itself to be aware of the EM environment and ideally, to sense the EM environment and act upon it in a semi-autonomous or autonomous way. While most research in this field has focused on the spectrum sensing aspects of the domain, development of the above-described "ideal CR" would require that the EM environment be characterized in domains such as angular, time and polarization among others. Signal dependent parameters can also be characterized such as bandwidth and modulation. The multi-dimensionality of the environment and the signals present within entail challenges with scalability and efficiency. This work focuses on the efficient sensing of signals in the angular domain also known as direction-of-arrival (DOA).
There are a multitude of ways to find a signal's DOA. All require multiple antennas connected to a single or multiple radio nodes, antennas with patterns that gather energy in a particular direction, or multiple single antenna radios. The methods that utilize multiple antennas exploit the phase and/or amplitude relationships between the antennas themselves for a signal's DOA. The principal tradeoff between DOA methods typically converges to scan time vs. number of antenna elements. For many DOA architectures, this also means a scan time tradeoff with angular resolution as well. Since fast and accurate measurements are important for characterizing a quickly changing EM environment, sensing speed becomes a key requirement in designing a CR and associated sensing architecture.
In this work, we present a DOA sensing architecture suitable for use in CR systems called the Direct Space to Information Converter (DSIC). Unlike current state-of-the art DOA methods, the DSIC breaks the tradeoff between scan time and the number of antenna elements needed for a given angular resolution when compared to other DOA and beamforming architectures. By randomly modulating the received signals in space, across multiple antenna elements and taking a few, compressed sensing (CS) measurements, the DSIC is able to angularly scan a wide field of view in an order of magnitude less time than other DOA methods. These CS measurements correspond to different random perturbations of the DSIC's antenna factor and can be quantized in as little as a single bit of resolution in the DSIC's phaseshifters/vector modulators. The DSIC is able to create multiple user-specified nulls in the antenna pattern to reduce the impact of strong known interferers while also simultaneously scanning the full field of view. Additionally, the designer has the option of performing simultaneous reception or nulling while sensing. If nulling, a few different methods are available each suitable for varying EM environments and potential use cases.
We show in detail the multi-disciplinary process in designing a complete end-to-end hardware solution, selecting the parameters necessary to design the DSIC as well as test and characterize it. The benefits of the DSIC are discussed and compared to the current state-of the art with an emphasis on architectures suitable for use in interferer rich environments. We demonstrate that the energy usage of the DSIC is lower than comparable CR architectures by a large factor and scales much more favorably in terms of energy and physical complexity as the number of antenna elements increase. At the conclusion of this work we also discuss future areas of exploration in extending the DSIC's capability by incorporating an ability to sense the spectrum as well as the DOA of a signal.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/4rpb-3942 |
| Date | January 2022 |
| Creators | Bajor, Matthew |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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