When a microphone array is mounted on a mobile aerial platform, such as an unmanned aerial vehicle (UAV), most existing beamforming methods cannot be used to adequately identify continuous and impulsive ground. Here, numerical simulation results and laboratory experiments are presented that validate a proposed time-frequency beamforming method based on the Multiple Signal Classification (MUSIC) algorithm to detect these acoustic sources from a mobile aerial platform. In the numerical simulations three parameters were varied to test the proposed algorithm’s location estimation performance: 1) the acoustic excitation types; 2) the moving receiver’s simulated flight conditions; and 3) the number of acoustic sources. Also, a distance and angle error analysis was done to quantify the proposed algorithm’s source location estimation accuracy when considering microphone positioning uncertainty. For experimental validation, three laboratory experiments were conducted. Source location estimations were done for: a 600 Hz sine source, a banded white noise source between 700-800 Hz, and a composite source combined simultaneously with both the sine and banded white noise sources. The proposed algorithm accurately estimates the simulated monopole’s location coordinates no matter the excitation type or simulated trajectory. When considering simultaneously-excited, multiple monopoles at high altitudes, e.g. 50 m, the proposed algorithm had no error when estimating the source’s locations. Finally, a distance and angle error analysis exposed how relatively small microphone location error, e.g. 1 cm maximum error, can propagate into large averaged distance error of about 10 m in the far-field for all monopole excitation types. For all simulations, however, the averaged absolute angle error remained small, e.g. less than 4 degrees, even when considering a 5 cm maximum microphone location error. For the laboratory experiments, the sine source had averaged distance and absolute angle errors of 0.9 m and 14.07 degrees from the source’s true location, respectively. Similarly, the banded white noise source’s averaged distance and absolute angle errors were 1.9 m and 47.14 degrees; and lastly, the averaged distance and absolute angle errors of 0.78 m and 8.14 degrees resulted when both the sources were simultaneously excited.

Thesis (M.S.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 76-77). Also available on the World Wide Web.

Alongside the ever increasing traffic demand, the fifth generation (5G) cellular network architecture is being proposed to provide better quality of service, increased data rate, decreased latency, and increased capacity. Without any doubt, the 5G cellular network will comprise of ultra-dense networks and multiple input multiple output technologies. This will make the current centralised solutions impractical due to increased complexity. Moreover, the amount of coordination information that needs to be transported over the backhaul links will be increased. Distributed or decentralised solutions are promising to provide better alternatives. This thesis proposes new distributed algorithms for wireless networks which aim to reduce the amount of system overheads in the backhaul links and the system complexity. The analysis of conflicts amongst transmitters, and resource allocation are conducted via the use of game theory, convex optimisation, and auction theory. Firstly, game-theoretic model is used to analyse a mixed quality of service (QoS) strategic non-cooperative game (SNG), for a two-user multiple-input single-output (MISO) interference channel. The players are considered to have different objectives. Following this, the mixed QoS SNG is extended to a multicell multiuser network in terms of signal-to-interference-and-noise ratio (SINR) requirement. In the multicell multiuser setting, each transmitter is assumed to be serving real time users (RTUs) and non-real time users (NRTUs), simultaneously. A novel mixed QoS SNG algorithm is proposed, with its operating point identified as the Nash equilibrium-mixed QoS (NE-mixed QoS). Nash, Kalai-Smorodinsky, and Egalitarian bargain solutions are then proposed to improve the performance of the NE-mixed QoS. The performance of the bargain solutions are observed to be comparable to the centralised solutions. Secondly, user offloading and user association problems are addressed for small cells using auction theory. The main base station wishes to offload some of its users to privately owned small cell access points. A novel bid-wait-auction (BWA) algorithm, which allows single-item bidding at each auction round, is designed to decompose the combinatorial mathematical nature of the problem. An analysis on the existence and uniqueness of the dominant strategy equilibrium is conducted. The BWA is then used to form the forward BWA (FBWA) and the backward BWA (BBWA). It is observed that the BBWA allows more users to be admitted as compared to the FBWA. Finally, simultaneous multiple-round ascending auction (SMRA), altered SMRA (ASMRA), sequential combinatorial auction with item bidding (SCAIB), and repetitive combinatorial auction with item bidding (RCAIB) algorithms are proposed to perform user offloading and user association for small cells. These algorithms are able to allow bundle bidding. It is then proven that, truthful bidding is individually rational and leads to Walrasian equilibrium. The performance of the proposed auction based algorithms is evaluated. It is observed that the proposed algorithms match the performance of the centralised solutions when the guest users have low target rates. The SCAIB algorithm is shown to be the most preferred as it provides high admission rate and competitive revenue to the bidders.

Cognitive radio improves radio spectrum utilization either by spectrum sharing or by opportunistically utilizing the spectrum of the licensed users. Cognitive beam- forming is a prominent technique that can further enhance the overall performance of the wireless communication systems through beamforming vector design and/or power allocation. Harvesting radio frequency (RF) energy from existing wireless communication systems is a promising potential solution for providing convenient, perpetual and green energy supply to wireless sensor networks (WSN). The amount of energy that can be harvested from existing RF energy sources over a short period of time can only support low data rate applications with simply transmission strategies. The main challenge for satisfying the energy requirement of WSN is the time-varying wireless fading channels. Low complexity cooperation between WSN and RF energy source can effectively enhance the stability of energy supply for the sensor node. While multiple transmission antennas are deployed at the existing RF energy source, judicious transmit beam selection can further improve the harvested energy at the sensor node, while simultaneously serving multiple users. In this doctoral research, we present random unitary beamforming (RUB) cooperative beam selection schemes to ensure the QoS of primary system and reduce the hardware and software complexities of secondary system. We analyze the exact out- age performance of the primary system, and investigate the tradeoff between primary system outage probability versus secondary system sum-rate performance. We also study the performance of overlaid wireless sensor transmission powered by RF energy harvested from existing wireless system. We derive the exact distribution function of harvested energy over a certain number channel coherence time over Rayleigh fading channels with the consideration of hardware limitation, such as energy harvesting sensitivity and harvesting efficiency. We also analyze the average packet delay and packet loss probability of sensor transmission subject to interference from existing system, for both delay insensitive traffics and delay sensitive traffics. The optimal design of energy storage capacity of the sensor nodes is proposed to minimize the average packet transmission delay for delay insensitive traffics with two candidate transmission strategies. We further investigate the energy harvesting performance of a wireless sensor node powered by RF energy from an existing multiuser MIMO system. Specifically, we propose based cooperative beam selection schemes to enhance the energy harvesting performance at the sensor. We derive the exact distribution function of harvested energy in a coherence time and further investigate the performance tradeoff of the average harvested energy at the sensor versus the sum-rate of the multiuser MIMO system. / Graduate

Swath bathymetry sidescan (SBS) sonar and the angle-of-arrival processing that underlies these systems has the capability to produce much higher resolution three dimensional imagery and bathymetry than traditional beamformed approaches. However, the performance of these high resolution systems is limited by signal-to-noise ratio (SNR) and they are also susceptible to multipath interference. This thesis explores two methods for increasing SNR and mitigating multipath interference for SBS systems. The first, binary coded pulse transmission and pulse compression is shown to increase the SNR and in turn provide reduced angle variance in SBS systems. The second, transmit beamforming, and more specifically steering and shading, is shown to increase both acoustic power in the water and directivity of the transmitted acoustic radiation. The transmit beamforming benefits are achieved by making use of the 8-element linear angle-of-arrival array typical in SBS sonars, but previously not utilized for transmit. Both simulations and real world SBS experiments are devised and conducted and it is shown that in practice pulse compression increases the SNR, and that transmit beamforming increases backscatter intensity and reduces the intensity of interfering multipaths. The improvement in achievable SNR and the reduction in multipath interference provided by the contributions in this thesis further strengthens the importance of SBS systems and angle-of-arrival based processing, as an alternative to beamforming, in underwater three dimensional imaging and mapping. / Graduate / 0544 / 0547 / mark.butowski@gmail.com

This thesis presents a simulation model of Stepped Frequency (SF) and Near Field BeamForming (NF BF) based stationary Through Wall Imaging (TWI) system to scan an object behind the wall for the reconstruction of 2D/3D image of it. The developed simulation model of TWI system requires neither the movement of the antenna array nor the object to reconstruct the image of the object behind the wall, thus overcoming the limitation of SAR/ISAR based TWI system. The simulation model of TWI system arrived at in this thesis facilitates the scan of the desired scenario in both azimuth and elevation to maximize the information available for more effective reconstruction of the Image of object behind the wall. The reconstruction of the image has been realized through conventional image processing algorithms which are devoid of inversion techniques to minimize the computational burden as well as the overall execution time of the TWI system. Contrary to the present TWI systems, the proposed simulation model has the capability for the reconstruction of the shape and contour of the object. In addition, the formulated simulation model of the TWI system overcomes the previously imposed constraints on the distances of separation between the object and the wall as well as the wall and the target. The simulation model of TWI of this thesis can handle arbitrary distances (far field or near field) between the antenna array and the wall as well as the wall and the object, which is not the case with the existing TWI systems. The thesis provides wave propagation analysis from the transmitting antenna array through the wall and the obstacle behind it and back to the receiver. Subsystems of TWI system like beamforming antenna arrays, wall and obstacles have been modeled individually. The thesis proposes a novel near field beamforming method that overcomes the usual requirement of 3D or volumetric near field radiation patterns of the beamforming array. Typical simulation results of NF BF with linear and planar arrays reveal the beam formation at a distance of one wavelength from the aperture of the array and which corresponds to the ratio of observation distance to aperture of array to be 0.2334. As a supplement to the presented NF BF a generic and versatile procedure to compute near field radiation patterns of antennas with prior knowledge of its either field or current distribution over the radiating aperture is also proposed. Examples of reconstruction of images of typical 2D and 3D objects are also illustrated in the thesis.

In binaural hearing aids, several beamforming algorithms can be used. These beamformers aim to enhance the target speech signal and preserve the binaural cues of the target source (e.g. with constraints on the target). However, the binaural cues of the other directional sources as well the background noise are often lost after processing. This affects the global impression of the acoustic scene, and it limits the perceptual separation of the sources by the hearing aids users. To help the hearing aids users to localize all the sound sources, it is important to keep the binaural cues of all directional sources and the background noise. Therefore, this work is devoted to find the best trade-off between the noise/interferers reduction and the cues preservations not only for the directional interferers but also for the background noise based on selection and mixing processes. In this thesis, some classification decision algorithms, which are based on different criteria such as the power, the power difference, and the coherence, are proposed to complete the selection and mixing processes. Simulations are completed using recorded signals provided by a hearing aid manufacturer to validate the performance of the proposed algorithm under different realistic acoustic scenarios. After detailed testing using different complex acoustic scenarios and different beamforming configurations, the results indicate that some of the proposed classification decision algorithms show good promise, in particular the classification decision algorithm based on coherence.

Traditional cryptographic encryption techniques at higher layers require a certain form of information sharing between the transmitter and the legitimate user to achieve security. Besides, it also assumes that the eavesdropper has an insufficient computational capability to decrypt the ciphertext without the shared information. However, traditional cryptographic encryption techniques may be insufficient or even not suit- able in wireless communication systems. Physical layer security (PLS) can enhance the security of wireless communications by leveraging the physical nature of wireless transmission. Thus, in this thesis, we study the PLS performance in emerging wireless transmission systems. The thesis consists of two main parts. We first consider the PLS design and analysis for ground-based networks em- ploying random unitary beamforming (RUB) scheme at the transmitter. With RUB technique, the transmitter serves multiple users with pre-designed beamforming vectors, selected using limited channel state information (CSI). We study multiple-input single-output single-eavesdropper (MISOSE) transmission system, multi-user multiple-input multiple-output single-eavesdropper (MU-MIMOSE) transmission system, and massive multiple-input multiple-output multiple-eavesdropper (massive MI- MOME) transmission system. The closed-form expressions of ergodic secrecy rate and the secrecy outage probability (SOP) for these transmission scenarios are derived. Besides, the effect of artificial noise (AN) on secrecy performance of RUB-based transmission is also investigated. Numerical results are presented to illustrate the trade-off between performance and complexity of the resulting PLS design. We then investigate the PLS design and analysis for unmanned aerial vehicle (UAV)-based networks. We first study the secrecy performance of UAV-assisted relaying transmission systems in the presence of a single ground eavesdropper. We derive the closed-form expressions of ergodic secrecy rate and intercept probability. When multiple aerial and ground eavesdroppers are located in the UAV-assisted relaying transmission system, directional beamforming technique is applied to enhance the secrecy performance. Assuming the most general κ-μ shadowed fading channel, the SOP performance is obtained in the closed-form expression. Exploiting the derived expressions, we investigate the impact of different parameters on secrecy performance. Besides, we utilize a deep learning approach in UAV-based network analysis. Numerical results show that our proposed deep learning approach can predict secrecy performance with high accuracy and short running time. / Graduate

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The millimeter wave (mmW) band, commonly referred to as the frequency band between 30 GHz and 300 GHz, is seen as a possible candidate to increase achievable rates for mobile applications due to the existence of free spectrum. However, the high path loss necessitates the use of highly directional antennas. Furthermore, impairments and power constraints make it difficult to provide full digital beamforming systems. In this thesis, we approach this problem by proposing effective beam alignment and beam tracking algorithms for low-complex analog beamforming (ABF) systems, showing their applicability by experimental demonstration. After taking a closer look at particular features of the mmW channel properties and introducing the beamforming as a spatial filter, we begin our investigations with the application of detection theory for the non-convex beam alignment problem. Based on an M-ary hypothesis test, we derive algorithms for defining the length of the training signal efficiently. Using the concept of black-box optimization algorithms, which allow optimization of non-convex algorithms, we propose a beam alignment algorithm for codebook-based ABF based systems, which is shown to reduce the training overhead significantly. As a low-complex alternative, we propose a two-staged gradient-based beam alignment algorithm that uses convex optimization strategies after finding a subregion of the beam alignment function in which the function can be regarded convex. This algorithm is implemented in a real-time prototype system and shows its superiority over the exhaustive search approach in simulations and experiments. Finally, we propose a beam tracking algorithm for supporting mobility. Experiments and comparisons with a ray-tracing channel model show that it can be used efficiently in line of sight (LoS) and non line of sight (NLoS) scenarios for walking-speed movements.