It is commonly accepted that the induced noise on DFT phase spectrum has a negligible effect on speech intelligibility for short durations of analysis windows, as the early intelligibility studies pointed out. This fact is confirmed by recent intelligibility studies as well. Based on this phenomenon, classical speech enhancement algorithms do not modify DFT phase spectrum and only make changes in the DFT magnitude spectrum. However, in recent studies it is also indicated that these classical speech enhancement algorithms are not capable of improving the intelligibility scores of noise degraded speech signals. In other words, the contained information in a noise degraded signal cannot be increased by classical enhancement methods. Instead the ease of listening, i.e. quality, can be improved. Hence additional effort can be made to increase the amount of quality improvement using both DFT magnitude and DFT phase. Therefore if the performances of the classical methods are to be improved in terms of speech quality, the effect of DFT phase on speech quality needs to be studied. In this work, the contribution of DFT phase on speech quality is investigated through some simulations using an objective quality assessment criterion. It is concluded from these simulations that, the phase spectrum has a significant effect on speech quality for short durations of analysis windows. Furthermore, phase values of low frequency components are found to have the largest contribution to this quality improvement. Under the motivation of these results, a new enhancement method is proposed which modifies the phase of certain low frequency components as well as the magnitude spectrum. The proposed algorithm is implemented in MATLAB environment. The results indicate that the proposed system improves the performance of the classical methods in terms of speech quality.

This study aims to present a sequential method for the classification of the autoregressive processes. Different from the conventional detectors having fixed sample size, the method uses Wald&rsquo / s sequential probability ratio test and has a variable sample size. It is shown that the suggested method produces the classification decisions much earlier than fixed sample size alternative on the average. The proposed method is extended to the case when processes have unknown variance. The effects of the unknown process variance on the algorithmperformance are examined. Finally, the suggested algorithm is applied to the classification of fixed and rotary wing targets. The average detection time and its relation with signal to noise ratio are examined.

An important step for the design of direction finding systems is the performance evaluation using numeric electromagnetic simulation tools. In this thesis, a method is presented for both modeling and simulation in a numeric electromagnetic simulation tool FEKO. The method relies on the data generated by FEKO. The data is then processed by correlative interferometer algorithm. This process is implemented in a MATLAB environment. Different types of antenna arrays including dipole, monopole and discone antennas are used. The antenna arrays are mounted on a UAV and SUV in order to see the platform effects. The direction finding performance is evaluated for different scenarios. It is shown that the presented approach is an effective tool for understanding the direction finding characteristic of antenna arrays.

In an energy harvesting communication system, energy is derived from outside sources and becomes partially available at different points in time. The constraints induced by this property on energy consumption plays an active role in the design of efficient communication systems. This thesis focuses on the optimal design of transmission and networking schemes for energy harvesting wireless communication systems. In particular, an energy harvesting transmitter broadcasting data to two receivers in an AWGN broadcast channel assuming that energy harvests and data arrivals occur at known instants is considered. In this system, optimal packet scheduling that achieves minimum delay is analyzed. An iterative algorithm, DuOpt, that achieves the same structural properties as the optimal schedule is proposed. DuOpt is proved to obtain the optimal solution when weaker user data is ready at the beginning. A dual problem is defined and shown to be strictly convex. Taking advantage of the dual problem, uniqueness of the solution of the main problem is proved. Finally, it is observed that DuOpt is almost two orders of magnitude faster than the SUMT (sequential unconstrained minimization technique) algorithm that solves the same problem.

This thesis proposes a complete framework of an end-to-end transmission of stereo video to mobile devices using DVB-H. Block diagram of the system is presented and operations conducted on the video at each layer are explained. Parameters and methodologies that may make a robust transmission possible are discussed. The transmission performance is analyzed in terms of error robustness under various coding methods, prediction structures, layering and protection strategies for different contents and channel conditions. It also investigates the effect of rate allocation between video quality and protection over robust transmission in erroneous environment. This works provides directive conclusions on the selection of the mentioned parameters and methods.

Ground based radars often experience difficulties in target detection and direction finding (DF) applications due to the interference between the direct and surface reflected signals when the targets fly at low altitudes. In this thesis, the phenomena governing the low angle propagation are overviewed and a multipath signal model including the effects of refraction, specular reflection, diffuse reflection, curvature of the earth and antenna polarization is presented. Then, the model is utilized to develop detection and DF algorithms for the targets at low altitudes. The target detection algorithm aims to increase signal-to-noise ratio (SNR) to overcome the effects of signal fading caused by surface reflections. The algorithm is based on diversity combining and the combining weight vector is calculated by maximizing average value of SNR. The technique is compared with Maximum Ratio Combining (MRC) algorithm which is optimal in terms of SNR. In direction finding, it is the height of the target that is explored since the target range information is obtained from the time delay. The target height is estimated by utilizing Maximum Likelihood Estimation (MLE). The performance of our algorithm is compared with that of the technique that is known in the literature as Refined Maximum Likelihood (RML).

An antenna array is an indispensable portion of a direction-of-arrival (DOA) estimation operation. A number of error sources in the arrays degrade the DOA estimation accuracy. Mutual coupling effect is one of the main error sources and should be corrected for any antenna array. In this thesis, a system theoretic approach is presented for mutual coupling characterization of antenna arrays. In this approach, the idea is to model the mutual coupling effect through a simple linear transformation between the measured and the ideal array data. In this context, a measurement reduction method (MRM) is proposed to decrease the number of calibration measurements. This new method dramatically reduces the number of calibration measurements for omnidirectional antennas. It is shown that a single calibration measurement is sufficient for uniform circular arrays when MRM is used. The method is extended for the arrays composed of non-omnidirectional (NOD) antennas. It is shown that a single calibration matrix can not properly model the mutual coupling effect in an NOD antenna array. Therefore, a sectorized calibration approach is proposed for NOD antenna arrays where the mutual coupling calibration is done in angular sectors. Furthermore, mutual coupling problem is also investigated for antenna arrays over a perfect electric conductor plate. In this case, reflections from the plate lead to gain/phase mismatches in the antenna elements. In this context, a composite matrix approach is proposed where mutual coupling and gain/phase mismatch are jointly modelled by using a single composite calibration matrix. The proposed methods are evaluated over DOA estimation accuracies using Multiple Signal Classification (MUSIC) algorithm. The calibration measurements are obtained using the numerical electromagnetic simulation tool FEKO. The evaluation results show that the proposed methods effectively realize the mutual coupling calibration of antenna arrays.

Subjective video quality and video decoding complexity are jointly optimized in order to determine the video encoding parameters that will result in the best Quality of Experience (QoE) for an end user watching a video clip on a mobile device. Subjective video quality is estimated by an objective criteria, video quality metric (VQM), and a method for predicting the video quality of a test sequence from the available training sequences with similar content characteristics is presented. Standardized spatial index and temporal index metrics are utilized in order to measure content similarity. A statistical approach for modeling decoding complexity on a hardware platform using content features extracted from video clips is presented. The overall decoding complexity is modeled as the sum of component complexities that are associated with the computation intensive code blocks present in state-of-the-art hybrid video decoders. The content features and decoding complexities are modeled as random parameters and their joint probability density function is predicted as Gaussian Mixture Models (GMM). These GMMs are obtained off-line using a large training set comprised of video clips. Subsequently, decoding complexity of a new video clip is estimated by using the available GMM and the content features extracted in real time. A novel method to determine the video decoding capacity of mobile terminals by using a set of subjective decodability experiments that are performed once for each device is also proposed. Finally, the estimated video quality of a content and the decoding capacity of a device are combined in a utility-complexity framework that optimizes complexity-quality trade-off to determine video coding parameters that result in highest video quality without exceeding the hardware capabilities of a client device. The simulation results indicate that this approach is capable of predicting the user viewing satisfaction on a mobile device.

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Elections are one of the most fundamental activities of a democratic society. As is the case in any other aspect of life, developments in technology have resulted changes in the voting procedure from using the traditional paper-based voting to voting by use of electronic means, or e-voting. E-voting involves using different forms of electronic means like / voting machines, voting via the Internet, telephone, SMS and digital interactive television. This thesis concerns voting by telephone, or televoting, it starts by giving a brief overview and evaluation of various models and technologies that are implemented within such systems. The aspects of televoting that have been investigated are technologies that provide a voice interface to the voter and conduct the voting process, namely the Election Markup Language (EML), Automated Speech Recognition (ASR) and Text-to-Speech (TTS).