Browsing by Subject "Wireless Communications"
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Item Acoustical Communications for Wireless Downhole Telemetry Systems(2012-08-22) Farraj, AbdallahThis dissertation investigates the use of advanced acoustical communication techniques for wireless downhole telemetry systems. Using acoustic waves for downhole telemetry systems is investigated in order to replace the wired communication systems currently being used in oil and gas wells. While the acoustic technology offers great benefits, a clear understanding of its propagation aspects inside the wells is lacking. This dissertation describes a testbed that was designed to study the propagation of acoustic waves over production pipes. The wireless communication system was built using an acoustic transmitter, five connected segments of seven inch production pipes, and an acoustic receiver. The propagation experiments that were conducted on this testbed in order to characterize the channel behavior are explained as well. Moreover, the large scale statistics of the acoustic waves along the pipe string are described. Results of this work indicate that acoustic waves experience a frequency- dependent attenuation and dispersion over the pipe string. In addition, the testbed was modified by encasing one pipe segment in concrete in order to study the effect of concrete on wave propagation. The concrete was found to filter out many of the signal harmonics; accordingly, the acoustic waves experienced extra attenuation and dispersion. Signal processing techniques are also investigated to address the effects of multipaths and attenuation in the acoustic channel; results show great enhancements in signal qualities and the usefulness of these algorithms for downhole communication systems. Furthermore, to explore an alternative to vibrating the body of a cemented pipe string, a testbed was designed to investigate the propagation aspects of sound waves inside the interior of the production pipes. Results indicate that some low-frequency sound waves can travel for thousands of feet inside a cemented pipe string and can still be detected reliably.Item Aspects of Interface between Information Theory and Signal Processing with Applications to Wireless Communications(2012-10-05) Park, Sang WooThis dissertation studies several aspects of the interface between information theory and signal processing. Several new and existing results in information theory are researched from the perspective of signal processing. Similarly, some fundamental results in signal processing and statistics are studied from the information theoretic viewpoint. The first part of this dissertation focuses on illustrating the equivalence between Stein's identity and De Bruijn's identity, and providing two extensions of De Bruijn's identity. First, it is shown that Stein's identity is equivalent to De Bruijn's identity in additive noise channels with specific conditions. Second, for arbitrary but fixed input and noise distributions, and an additive noise channel model, the first derivative of the differential entropy is expressed as a function of the posterior mean, and the second derivative of the differential entropy is expressed in terms of a function of Fisher information. Several applications over a number of fields, such as statistical estimation theory, signal processing and information theory, are presented to support the usefulness of the results developed in Section 2. The second part of this dissertation focuses on three contributions. First, a connection between the result, proposed by Stoica and Babu, and the recent information theoretic results, the worst additive noise lemma and the isoperimetric inequality for entropies, is illustrated. Second, information theoretic and estimation theoretic justifications for the fact that the Gaussian assumption leads to the largest Cramer-Rao lower bound (CRLB) is presented. Third, a slight extension of this result to the more general framework of correlated observations is shown. The third part of this dissertation concentrates on deriving an alternative proof for an extremal entropy inequality (EEI), originally proposed by Liu and Viswanath. Compared with the proofs, presented by Liu and Viswanath, the proposed alternative proof is simpler, more direct, and more information-theoretic. An additional application for the extremal inequality is also provided. Moreover, this section illustrates not only the usefulness of the EEI but also a novel method to approach applications such as the capacity of the vector Gaussian broadcast channel, the lower bound of the achievable rate for distributed source coding with a single quadratic distortion constraint, and the secrecy capacity of the Gaussian wire-tap channel. Finally, a unifying variational and novel approach for proving fundamental information theoretic inequalities is proposed. Fundamental information theory results such as the maximization of differential entropy, minimization of Fisher information (Cramer-Rao inequality), worst additive noise lemma, entropy power inequality (EPI), and EEI are interpreted as functional problems and proved within the framework of calculus of variations. Several extensions and applications of the proposed results are briefly mentioned.Item Design of frequency synthesizers for short range wireless transceivers(Texas A&M University, 2004-09-30) Valero Lopez, Ari YakovThe rapid growth of the market for short-range wireless devices, with standards such as Bluetooth and Wireless LAN (IEEE 802.11) being the most important, has created a need for highly integrated transceivers that target drastic power and area reduction while providing a high level of integration. The radio section of the devices designed to establish communications using these standards is the limiting factor for the power reduction efforts. A key building block in a transceiver is the frequency synthesizer, since it operates at the highest frequency of the system and consumes a very large portion of the total power in the radio. This dissertation presents the basic theory and a design methodology of frequency synthesizers targeted for short-range wireless applications. Three different examples of synthesizers are presented. First a frequency synthesizer integrated in a Bluetooth receiver fabricated in 0.35?m CMOS technology. The receiver uses a low-IF architecture to downconvert the incoming Bluetooth signal to 2MHz. The second synthesizer is integrated within a dual-mode receiver capable of processing signals of the Bluetooth and Wireless LAN (IEEE 802.11b) standards. It is implemented in BiCMOS technology and operates the voltage controlled oscillator at twice the required frequency to generate quadrature signals through a divide-by-two circuit. A phase switching prescaler is featured in the synthesizer. A large capacitance is integrated on-chip using a capacitance multiplier circuit that provides a drastic area reduction while adding a negligible phase noise contribution. The third synthesizer is an extension of the second example. The operation range of the VCO is extended to cover a frequency band from 4.8GHz to 5.85GHz. By doing this, the synthesizer is capable of generating LO signals for Bluetooth and IEEE 802.11a, b and g standards. The quadrature output of the 5 - 6 GHz signal is generated through a first order RC - CR network with an automatic calibration loop. The loop uses a high frequency phase detector to measure the deviation from the 90? separation between the I and Q branches and implements an algorithm to minimize the phase errors between the I and Q branches and their differential counterparts.Item Machine learning for link adaptation in wireless networks(2011-12) Daniels, Robert C.; Heath, Robert W., Ph. D.; Andrews, Jeffrey; Nettles, Scott; Caramanis, Constantine; Qiu, LiliLink adaptation is an important component of contemporary wireless networks that require high spectral efficiency and service a variety of network applications/configurations. By exploiting information about the wireless channel, link adaptation strategically selects wireless communication transmission parameters in real-time to optimize performance. Link adaptation in practice has proven challenging due to impairments outside system models and analytical intractability in modern broadband networks with multiple antennas (MIMO), orthogonal frequency division multiplexing (OFDM), forward error correction, and bit-interleaving. The objective of this dissertation is to provide simple and flexible link adaptation algorithms with few link model assumptions that are amenable to modern wireless networks. First, a complete design and analysis of supervised learning for link adaptation in MIMO-OFDM is provided. This includes the construction of a publicly available data set, a new frame error rate bound leading to a new feature set, and IEEE 802.11n performance evaluation to verify that my design outperforms existing link quality metrics. Next, two supervised learning classification algorithms are designed to exploit information collected from packets transmitted and received over standard links in real time: database learning with nearest neighbor classifiers and support vector machines. Algorithms are also proposed to preserve diversity of feature sets in the database and to allow learning algorithms to seek out more information about the network. Finally, link adaptation with supervised learning is applied to MIMO-OFDM systems where the modulation order may be adapted per-stream. This leads to the analysis of the ordered SNR per stream and its connection to the cumulative distribution function of SNR on each stream. Decoupled link adaptation algorithms, which significantly reduce the complexity of non-uniform link adaptation algorithms, are proposed. New analysis of non-uniform link adaptation shows that the performance of decoupled link adaptation algorithms converge to the performance of joint (optimal) link adaptation algorithms as the number of modulation and coding options per-stream increase. This guides the construction of future standards to reduce the complexity of link adaptation in MIMO-OFDM.