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Spectrum sharing has become increasingly important since the past decade due to the ongoing congestion of spectral resources. Higher data rates in wireless communications require expansion of existing frequency allocations. Significant research efforts have been made in the direction of cognitive radio to effectively manage the existing frequency usage. Recently, coexistence of multiple platforms within the same frequency bands is considered effective to mitigate spectral congestion. This requires both systems to work collaboratively to mitigate their mutual interference. This challenging problem can be significantly simplified if both systems are controlled by the same entity. Joint radar-communication (JRC) system is such an example where radar and communication system objectives are achieved by the same physical platform. In this dissertation, we consider three different types of JRC systems. These JRC systems respectively exploit a single transmit antenna, an antenna array for beamforming, and a distributed JRC network, and develop novel signal processing techniques to optimize the performance of these systems. Special attention is given to the resource optimization objectives and numerous resource allocation schemes are developed and investigated. First, we consider a single transmit antenna-based JRC system which exploits dual-purpose transmit orthogonal frequency division multiplexing (OFDM) waveforms to perform radar and communication objectives simultaneously. We optimize the power allocation of the OFDM subcarriers based on the frequency-sensitive target response and communication channel characteristics. For this purpose, we employ mutual information as the optimization metric. In the simulation examples considered for this system, we observed that the JRC system enjoys approximately 20\% improvement in the performance of communication subsystem with a mere 5\% reduction in radar subsystem performance. Second, we propose a quadratic amplitude modulation (QAM) based sidelobe modulation scheme for beamforming-based JRC systems which enhances the communication data rate by enabling a novel multiple access strategy. The main principle of this proposed strategy lies in enabling the beamformer to transmit signals with distinct amplitudes and phases in different directions. We also investigate optimal power allocation for such a spectrum sharing approach by employing a spatial power control-based beamforming approach. Furthermore, the robustness of these beamforming-based JRC systems is improved using chance constrained programming. In this context, we observe that the chance constrained optimization can be relaxed to form a deterministic and convex problem by employing the statistical profile of the communication channels. When dealing with JRC systems that are equipped with more antennas than the number of radio frequency chains, we perform the resource optimization in terms of minimized power usage and optimal selection of antennas resulting in an efficient utilization of hardware up-conversion chains. In the simulation examples considered for these schemes, we observe that, even with a reduction of nearly 30\% of the transmit antennas, the beamforming-based JRC system is able to perform the required radar and communication tasks without any disadvantage. Our last contribution is on a distributed JRC system, which is the first effort in this research direction, enabling spectrum sharing for networked radar systems coexisting with the communication systems. We devise a power allocation strategy for such a system by employing convex optimization techniques. In this strategy, the target localization error and the Shannon capacity are respectively considered as the optimization criteria for radar and communication systems. For the simulation example considered in this case, we observe that the proposed resource allocation strategy achieves a communication performance that was approximately 5 times greater than that achieved by the radar-only counterpart. Moreover, the target localization performance achieved by the JRC system using the proposed approach was approximately 4 times better than the performance achieved by the communication-only approach. / Electrical and Computer Engineering

Sensor arrays play an instrumental role in a variety of applications, including radar, sonar, radio astronomy, and wireless communications. Employing an array of sensors permits direction-of-arrival (DOA) estimation, interference suppression, and imaging of spatial distributions of sources or scatterers. Linear and planar array geometries can have sensors with uniform or non-uniform spacings. Non-uniform arrays require much fewer sensors to achieve comparable performance to uniform arrays in terms of the spatial resolution and the number of resolvable sources or scatterers. This dissertation proposes novel signal processing methods for narrowband passive (receive-only) sensing and imaging. The focus is on source estimation using linear and planar passive arrays with uniform and non-uniform geometries. Algorithm development for the non-uniform arrays is facilitated by a virtual array structure, called the difference coarray, which comprises pairwise differences of physical sensor positions. The difference coarray naturally arises from the passive sensing signal model. High-resolution DOA estimation techniques, such as the subspace-based methods, are computationally expensive, especially for arrays that span large apertures. Further, performance of such methods deteriorates for coherent sources. We propose efficient and effective Fourier-based iterative techniques for DOA estimation of coherent and uncorrelated sources using linear and planar arrays with both uniform and non-uniform geometries. The considered non-uniform arrays include those with uniform and non-uniform difference coarrays. The proposed DOA estimation techniques build on the iterative interpolated beamformer, which employs an estimate-and-subtract strategy to successively extract the sources and refines the estimates via an interpolation and spectral leakage subtraction scheme. We enable iterative beamforming in the coarray domain for linear and rectangular arrays, specifically compensating for non-uniformity of difference coarrays to yield asymptotically unbiased DOA estimates. We also design the iterative interpolated beamformer for oversampled and undersampled uniform circular arrays under the manifold separation framework, which permits the application of DOA estimation techniques that were developed for uniform linear arrays to arbitrary array geometries, such as circular arrays. The proposed iterative beamforming techniques not only estimate the source DOAs, but also provide source power/amplitude estimates. As such, these Fourier-based methods are applicable to narrowband passive imaging systems for providing an accurate estimate of the distribution of source intensity or amplitude as a function of angle. / Electrical and Computer Engineering

Modern medical ultrasound machines produce enormous amounts of data, as much as several gigabytes/sec in some systems. The challenges of generating, storing, processing and reproducing such voluminous data has motivated researchers to search for a feasible compression scheme for the received ultrasound radio frequency (RF) signals. Most of this work has concentrated on the digitized data available after sampling and A/D conversion. We are interested in the possibility of compression implemented directly on the received analog RF signals; hence, we focus on compression of the set of signals in a single receive aperture. We first investigate the model-free approaches to compression that have been proposed by previous researchers that involve applications of some of the well-known signal processing tools like Principal Component Analysis (PCA), wavelets, Fourier Transform, etc. We also consider Bandpass Prolate Spheroidal Functions (BPSFs) in this study. Then we consider the derivation of the optimal basis for the RF signals assuming a white noise model for spatial inhomogeneity field in tissue. We first derive an expression for the (time and space) autocorrelation function of the set of signals received in a linear aperture. This is then used to find the autocorrelation's eigenfunctions, which form an optimal basis for minimum mean-square error compression of the aperture signal set. We show that computation of the coefficients of the signal set with respect to the basis is approximated by calculation of real and imaginary part of the Fourier Series coefficients for the received signal at each aperture element, with frequencies slightly scaled by aperture position, followed by linear combinations of corresponding frequency components across the aperture. The combination weights at each frequency are determined by the eigenvectors of a matrix whose entries are averaged cross-spectral coefficients of the received signal set at that frequency. The principal eigenvector generates a combination that corresponds to a variation on the standard delay-and-sum beamformed aperture center line, while the combinations from other eigenvectors represent aperture information that is not contained in the beamformed line. We then consider how to use the autocorrelation's eigenfunctions and eigenvalues to generate a linear minimum mean-square error beamformer for the center line of each aperture. Finally, we compare the performances of the optimal compression basis and to that of the 2D Fourier Transform.

Phased microphone arrays are valuable tools for aeroacoustic measurements that can measure the directivity of multiple acoustic sources. However, when deployed in closed test-section wind tunnels, the acoustics suffer due to intense pressure fluctuations contained in the wall-bound turbulent boundary layer. Furthermore, phased microphone arrays require many sensors distributed over a large aperture to ensure good spatial resolution over a wide frequency range. Microphone arrays of such large count are not always feasible due to constraints in space and cost. This thesis describes an alternative approach for measuring single broadband acoustic sources that uses an acoustic metasurface. The metasurface is comprised of a meandering channel of quarter-wave cavities and an array of equally spaced half-wave open through-cavities. A series of tests were conducted in Virginia Tech's Anechoic Wall-Jet Tunnel where combinations of a wall-bound turbulent jet-flow and a single broadband acoustic source were used to excite the metasurface and produce acoustic surface waves. Measurements of the acoustic surface waves were performed using two methods: a pair of traversing microphones scanning the pressure field along the length of the metasurface 0.25 mm beneath its bottom face, and an array of unequally spaced microphones embedded inside the metasurface. Spectral analysis on the measurements revealed that the inclusion of multiple through-cavities leads to constructive reinforcement of select acoustic surface waves as a function of the acoustic source location. In the case of the embedded microphones, acoustic beamforming was applied in order to extract spatial information. This reinforcement was observed during measurements made with both flow and acoustic excitation, up to Wall-Jet Tunnel nozzle exit speeds of 40 m/s beyond which it was no longer seen. A series of quiescent measurements made with a range of speaker locations constituted a calibration for the metasurface which was used to locate an unknown broadband acoustic source within an The Root-Mean-Square (RMS) error of 1.06 degrees. / Master of Science / Phased microphone arrays are valuable tools for aeroacoustic measurements that can measure the directivity of multiple acoustic sources within a sound field. When used in conjunction with signal processing techniques, such as delay-and-sum beamforming, a researcher or engineer can obtain an intuitive view of the sound field and distinguish between multiple sources over a wide frequency range. However, these microphone arrays often utilize dozens of microphones which raises the array's complexity and cost. Furthermore, when a phased microphone array is mounted flush to the wall of a wind tunnel test section, it is submerged under a turbulent boundary layer which imposes intense pressure fluctuations on the microphones making it difficult to identify acoustic sources. Boundary layers form at the interface between a fluid and solid interface. This thesis describes experimentation performed in the Virginia Tech Anechoic Wall-Jet Tunnel on a new type of pressure sensing microphone array that leverage acoustic metamaterial technology. The acoustic metamaterial shields the microphones from the flow, lessening the influence of the turbulent boundary layer on the measurement. The focus in this thesis is on the novel array's ability to locate a single broadband acoustic source using as few as six microphones. The metasurface was installed in the Wall-Jet Tunnel test plate such that an array of evenly spaced through-cavities are flush to the surface. The through-cavities communicate the pressure field on top of the test surface to a meandering channel of interconnected closed cavities below. Near the resonant depth frequencies of the closed cavities, acoustic surface waves form which are evanescent pressure waves that are bound to the surface or structure that support them. The interference between the acoustic surface waves generated at each through-cavity leads to reinforced acoustic surface waves which are sensitive to the direction of a broadband source. In all, an acoustic metamaterial was tested under a variety of conditions such as: Wall-Jet Tunnel flow speed, speaker location, and the number of through-cavities open. The performance of the novel array and future plans are discussed.

The evolution to 5G and its use cases is driven by data-intensive applications requiring higher data rates over wireless channels. This has led to research in massive multiple input multiple output (MIMO) techniques and the use of the millimeter wave (mm wave) band. Because of the higher path loss at mm wave frequencies and the poor scattering nature of the mm wave channel (fewer paths exist), this thesis first proposes the use of the sphere decoding (SD) algorithm, and the semidefinite relaxation (SDR) detector to improve the performance of a uniform planar array (UPA) hybrid beamforming technique with large antenna arrays. The second contributions of this thesis consist of a low-complexity algorithm using the gradient descent for hybrid precoding and combining designs in mm wave systems. Also, in this thesis we present a low-complexity algorithm for hybrid precoding and combining designs that uses momentum gradient descent and Newton’s Method for mm wave systems which makes the objective function converge faster compared to other iterative methods in the literature; the two proposed low-complexity algorithms for hybrid precoding and combining do not depend on the antenna array geometry, unlike the orthogonal matching pursuit (OMP) hybrid precoding/combining approach. Moreover, these algorithms allow hybrid precoders/combiners to yield a performance very close to that of the optimal unconstrained digital precoders and combiners with a small number of iterations. Simulation results verify that the proposed hybrid precoding/combining scheme that uses momentum gradient descent and Newton’s Method outperforms previous methods that appear in the literature in terms of bit error rate (BER) and achievable spectral efficiency with lower complexity. Finally, an iterative algorithm that directly converts the hybrid precoding/combining in the full array (FA) architecture to subarray (SA) architecture is proposed and examined in this thesis. It is called direct conversion of iterative hybrid precoding/combining from FA to SA (DCIFS) hybrid precoding/combining. The proposed DCIFS design takes into consideration the matrix structure of the analog and baseband precoding and combining in the design derivation. Moreover, it does not depend on the antenna array geometry, unlike other techniques, such as the orthogonal matching pursuit (OMP) hybrid precoding/combining approach, nor does it assume any other constraints. Simulation results show that the proposed DCIFS hybrid design, when compared to the FA hybrid designs counterpart, can provide a spectral efficiency that is close to optimum while maintaining a very low complexity and better spectral efficiency than the conventional SA hybrid design with the same hardware complexity.

The development of 5G and 6G entails new demandson antennas. This includes fast and reliable connections to a largenumber of devices. A wider area of coverage, and thus moreantennas are also expected, which is problematic for the expensiveantennas used today. To meet those demands, a geodesic lensantenna has been proposed. The antenna utilises several feedingports for beam forming. It is designed to operate at a frequencyof 8 to 12 GHz and is optimised to have an even coverage in thefar-field. The design is modulated with one fold to reduce theheight of the antenna. A prototype of the antenna is 3D printedwith PLA and coated with aluminium tape. The design has asimulated realised gain of 13.5 dBi and beam width of around30°. The 3D printed antenna could not be tested due to technicalproblems with the testing facilities, but is expected to have similarresults. / Med utvecklingen av 5G och 6G kommer stora krav på antenner. Flera enheter skall kunna vara uppkopplade och samtidigt krävs högre hastigheter med stabil uppkoppling. Utöver det ställs det även krav på en bred täckning vilket innebär att fler antenner behöver kopplas upp, vilka har höga kostnader idag. För att möta dessa krav har en design för en geodetisk linsantenn lagts fram. Antennen använder flera ingångar för att skapa en riktbar stråle. Den är designad för att operera inom frekvenserna 8 till 12 GHz och är optimerad för att få en jämn täckning i fjärrfältet. Designen nyttjar en vikning för att minska antennens höjd. En prototyp av antennen tillverkas med hjälp av 3D printad plast som beläggs med aluminiumtejp. Designen har en simulerad förstärking av 13.5 dBi och en strålbredd runt 30°. Den 3D printade antennen kunde inte testas på grund av tekniska problem med testutrustningen men förväntas ha liknande resultat som den simulerade. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm

Multiple-Input, Multiple-Output (MIMO) processing techniques for wireless communication are of interest for next-generation systems because of their potential to dramatically improve capacity in some propagation environments. When used in applications such as wireless LAN and cellular telephony, the MIMO processing methods must be adapted for the situation where a base station is communicating with many users simultaneously. This dissertation focuses on the downlink of such a channel, where the base station and all of the users have antenna arrays. If the transmitter has advance knowledge of the users' channel transfer functions, it can use that information to minimize the interuser interference due to the signals that are simultaneously transmitted to other users. If the transmitter assumes that all receivers treat the interference as noise, finding a solution that optimizes the use of resources is very difficult. This work proposes two classes of solutions to this problem. First, by forcing some or all of the interference to zero, it is possible to achieve a sub-optimal solution in closed-form. Second, a class of iterative solutions can be derived by extending optimal algorithms for multi-user downlink beamforming to accommodate receivers with multiple antennas. The closed-form solutions generally require less computation, but the iterative solutions offer improved performance are more robust to channel estimation errors, and thus may be more useful in practical applications. The performance of these algorithms were tested under realistic channel conditions by testing them on channels derived from both measurement data and a statistical model of an indoor propagation environment. These tests demonstrated both the ability of the channel to support multiple users, and the expected amount of channel estimation error due to movement of the users, with promising results. The success of any multi-user MIMO processing algorithm is ultimately dependent on the degree of correlation between the users' channels. If a base station is required to support a large number of users, one way to ensure minimal correlation between users' channels is to select groups of users whose channels are most compatible. The globally optimal solution to this problem is not possible without an exhaustive search, so a channel allocation algorithm is proposed that attempts to intelligently select groups of users at a more reasonable computational cost.

Radio frequency interference (RFI) is a growing problem for radio astronomers. One potential solution utilizes spatial filtering by placing an array of electrically small antennas at the focal plane of a parabolic reflector. This thesis documents the design and characterization of a prototype array feed and RF receiver that were used to demonstrate the spatial filtering principle. The array consists of a 7-element hexagonal arrangement of thickened dipole antennas tuned to a center frequency of 1600 MHz. The receiver is a two-stage, low-noise frequency mixer that is tunable over the entire L-band. This thesis also documents a new receiver design that is part of an upgrade to the outdoor antenna test range for the National Radio Astronomy Observatory in Green Bank, West Virginia. The array feed was demonstrated on a three-meter parabolic reflector by recovering a weak signal of interest that was obscured by a strong, broadband interferer. Similar results were also obtained when the interferer moved with an angular velocity of 0.1 degree per second, but only when the power in the interferer dominated the signal. The aperture efficiency was measured at 64%, but adaptive beamformers can slightly perturb this value through distortions in the beam pattern. This phenomenon, called pattern rumble, effectively reduced the sensitivity of the radio telescope, and was measured by comparing the SNRs of adaptive beamformers to the SNR of a fixed-weight beamformer. It was found that pattern rumble can reduce the useful integration time by roughly one order of magnitude. It was also found that mechanical instability of the primary reflector introduces a great deal of pattern rumble, even when the interferer is fixed in direction.

Presented herein is the design and construction process in the expansion of BYU's seven-element experimental platform to a nineteen-element platform for phased array feed experiments. The nineteen-element system was deployed at the National Radio Astronomy Observatory (NRAO) in Green Bank West Virginia for use on the Green Bank 20-Meter Telescope. Numerical simulations were performed to determine how sensitivity was affected by electronic beam steering and offset of the phased array feed (PAF) relative to the focal plane of the reflector. These simulated results were then compared to experimental data.