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Bibliography: p. 285-305. / Microfiche. / viii, 305 leaves, bound 29 cm

In recent decades, communication networks have had a profound effect on society. Wireless communication has affected our lifestyle and altered how humans communicate and the Internet has revolutionized how we access, publish and disseminate information. In recent years we have also witnessed a radical change in how information is generated on the Internet. Today, information is no longer only generated by a small group of professionals but it is created by the users themselves and shared with a broad community with matching interests. This is evident with ”Web 2.0” applications such as blogs, podcasts, YouTube and social platforms like Facebook and Flickr. As a result of these trends, the Internet is today mainly used to provide users with access to contents. With recent advances in mobile platforms, information generation and consumption has spread from personal computers and Internet into people’s palms. This calls for efficient dissemination of information to and from mobile devices. This thesis considers content-centric networking in the context of mobile wireless networks. The main focus is on opportunistic distribution of content where mobile nodes directly exchange content items when they are within communication range. This communication mode enables dissemination of content between mobile nodes without relying on infrastructure, which can be beneficial for several reasons: infrastructure may be absent, overloaded, unreliable, expensive to use, censored or limited to certain users or contents. Opportunistic networking also has different properties than infrastructure based wireless networking, particularly in terms of scalability, locality and dissemination delay. The contributions of this thesis lie in two areas. Firstly we study the feasibility and performance of opportunistic networking among mobile nodes in urban areas using both analytic models and simulations. In particular we study the effect of two enablers of opportunistic networking: cooperation and mobility. By applying models from epidemic modeling, we show that if nodes cooperate by sharing, even in a limited manner, content can spread efficiently in a number of common case scenarios. We also study in detail which aspects of human mobility affect wireless communication and conclude that performance is not very sensitive to accurate estimation of the probability distributions of mobility parameters such as speed and arrival process. Our results however suggest that it is important to capture the scenario and space in which mobility occurs since this may affect performance significantly. Secondly, we present our design and implementation of a middleware architecture for a mobile peer-to-peer content distribution. Our system uses a decentralized content solicitation scheme that allows the distribution of content between mobile devices without requiring Internet connectivity and infrastructure support. Our system is based on the publish/subscribe paradigm and we describe the design and implementation of key components. We evaluate the performance and correctness of the system using both large-scale simulations and small-scale experimentation with our implementation. Finally we present the design and evaluation of an energy-efficient radio subsystem for opportunistic networking. / QC 20110524

In the lossy coding of perceptually relevant signals, such as sound and images, the ultimate goal is to achieve good perceived quality of the reconstructed signal, under a constraint on the bit-rate. Conventional methodologies focus either on a rate-distortion optimization or on the preservation of signal features. Technologies resulting from these two perspectives are efficient only for high-rate or low-rate scenarios. In this dissertation, a new objective is proposed: to seek the optimal rate-distortion trade-off under a constraint that statistical properties of the reconstruction are similar to those of the source. The new objective leads to a new quantization concept: distribution preserving quantization (DPQ). DPQ preserves the probability distribution of the source by stochastically switching among an ensemble of quantizers. At low rates, DPQ exhibits a synthesis nature, resembling existing coding methods that preserve signal features. Compared with rate-distortion optimized quantization, DPQ yields some rate-distortion performance for perceptual benefits. The rate-distortion optimization for DPQ facilitates mathematical analysis. The dissertation defines a distribution preserving rate-distortion function (DP-RDF), which serves as a lower bound on the rate of any DPQ method for a given distortion. For a large range of sources and distortion measures, the DP-RDF approaches the classic rate-distortion function with increasing rate. This suggests that, at high rates, an optimal DPQ can approach conventional quantization in terms of rate-distortion characteristics. After verifying the perceptual advantages of DPQ with a relatively simple realization, this dissertation focuses on a method called transformation-based DPQ, which is based on dithered quantization and a non-linear transformation. Asymptotically, with increasing dimensionality, a transformation-based DPQ achieves the DP-RDF for i.i.d. Gaussian sources and the mean squared error (MSE). This dissertation further proposes a DPQ scheme that asymptotically achieves the DP-RDF for stationary Gaussian processes and the MSE. For practical applications, this scheme can be reduced to dithered quantization with pre- and post-filtering. The simplified scheme preserves the power spectral density (PSD) of the source. The use of dithered quantization and non-linear transformations to construct DPQ is extended to multiple description coding, which leads to a multiple description DPQ (MD-DPQ) scheme. MD-DPQ preserves the source probability distribution for any packet loss scenario. The proposed schemes generally require efficient entropy coding. The dissertation also includes an entropy coding algorithm for lossy coding systems, which is referred to as sequential entropy coding of quantization indices with update recursion on probability (SECURE). The proposed lossy coding methods were subjected to evaluations in the context of audio coding. The experimental results confirm the benefits of the methods and, therewith, the effectiveness of the proposed new lossy coding objective. / QC 20110829

This work considers behavioral modeling, parameter-reduction, and digital predistortion of radio frequency power amplifiers. Due to the use of modern digital modulation methods, contemporary power amplifiers are frequently subjected to signals characterized by considerable bandwidths and fast changing envelopes. As a result, traditional quasi-memoryless amplitudeto-amplitude (AM/AM) and amplitude-to-phase (AM/PM) characteristics are no longer sufficient to describe and model the behavior of power amplifiers; neither can they be successfully used for linearization. In this thesis, sampled input and output data are used for identification and validation of several block structure models with memory. The time-discrete Volterra model, the Wiener model, the Hammerstein model, and the radial-basis function neural network are all identified and compared with respect to in-band and out-of-band errors. Two different signal types (multitones and noise), with different powers, peak-to-average ratios, and bandwidths have been used as inputs to the amplifier. Furthermore, two different power amplifiers were investigated, one designed for third generation mobile telecommunication systems and one for second generation systems. A stepped three-tone measurement technique based on digitally modulated baseband signals is also presented. The third-order Volterra kernel parameters were determined from identified intermodulation products. The symmetry properties of the Volterra kernel along various portions of the three dimensional frequency space were analyzed and compared with the symmetry of the Wiener and Hammerstein systems. / QC 20100824