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(2005)ThesisIncreasing demand for wireless communication challenges the availability of limited radio resources, such as bandwidth and power etc. Limited resources cause a trade off with the quality of service. The work presented in this thesis is intended to develop algorithms those can be used to demodulate information with optimal amount of resources (Signal to Noise Ratio, Processing memory requirement, Computational complexity etc ). In the first part of the thesis a decision feedback sequence detection algorithm has been proposed that provides exactly the same bit error rate as in standard maximum likelihood sequence estimation but with 95% lowmomputational complexity. Besides that the proposed algorithm achieves 2 dB signal to noise ratio (SNR) gain over the existing decision feedback algorithms. The proposed algorithm is applicable in multiple input multiple output (MIMO) as well as single input single output (SISO) wireless communication systems. In the second part of the thesis an adaptive blind sequence detection algorithm has been proposed where a novel reference channel has been exploited. The problem of bit-shift ambiguity in blind sequence detection is completely eliminated exploiting the proposed algorithm. A 3 dB SNR gain is achieved against the existing blind sequence detection algorithms for the system without error correction code. The BER performance is highly scalable with the variation of segmentation window size. In the third part of the thesis, two different sequence detection algorithms have been proposed to track rapidly time varying channels. One of the algorithms, called extended window survivor processing (EWSP), requires lower computational complexity than that of Per-survivor processing (PSP) sequence detection process. The other algorithm, called bi-directional survivor processing reduces 17% of channel misacquisation than that of PSP. Consequently, both of these algorithms reduce the probability of error propagation in the detection process. In the final part of the thesis, the capacity and coverage of the UMTS urban network has been analyzed while the Repeaters are inserted. It has been found that the system capacity with repeaters is doubled in an environment with the propagation constant 3.7-3.8. As a by product, 10% increase in the cell coverage was also found.
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(1993)ThesisIn view of the specific advantages of using vacuum as device medium and field emission cathode as electron source, a renewed interest in vacuum microelectronics utilizing advanced IC technology is emerging. This thesis demonstrates an application of field emission emitters in two novel pressure sensors. One is based on a diode structure with one electrode fabricated on a pressure sensitive thin diaphragm. The other has two tip-to-tip cantilever beam emitters with a small gap between tips. Both cone-shape and wedge-shape emitters are studied. Some new results on the analysis of the two generic emitter array diodes regarding the geometric design parameters, which are essential to device design, are presented. Various wet and dry etching techniques of forming emitter arrays are compared. A combined wet/dry fabrication process is developed to achieve array uniformity and reproducibility. The characteristics of pressure sensor with ideal field emission array are simulated, methods to take into consideration the nonuniformity of array tips, an inevitable result from fabrication practice, is also discussed. A study of field emission from silicon-based emitter array is present and various factors to affect the stability of emission are investigated. The performance of two fabricated experimental pressure sensors are evaluated, one with cone-shape emitter array and the other with cantilever beam field emitters.
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(2005)ThesisTurbo codes discovered in 1993 by Berrou et al. [1] were the first coding technique that approached the Shannon theoretical limit of information transmission to within 0.5 dB. Soon after this discovery, it was recognized that the same Turbo principle could be applied to a variety of detection/decoding problems such as equalization, multi-user detection, joint channel estimation and decoding etc. The computational complexity of such schemes remains a challenging issue since many Turbo detectors require computationally complex Maximum Likelihood (ML) detection in combination with channel decoding. Consequently, a class of low complexity Turbo detectors employing linear and decision feedback filtering instead of ML have been invented recently in order to solve this problem. This dissertation describes low complexity adaptive turbo detection methods for wireless communications, namely Turbo equalization and Turbo Multi-user detection. The adaptive turbo detectors are shown to outperform their conventional Minimum Mean Squared Error (MMSE) counterparts regarding the SNR-BER performance. For Turbo equalization the most remarkable improvement has been achieved for highly frequency-selective channels. For Turbo Multi-user detection most of the gain is obtained for overloaded DS-CDMA systems where the number of users exceeds the processing gain. A theoretical analysis of Turbo equalization provides a new set of MMSE coefficients. The proposed new detector is shown to outperform all turbo detectors of similar computational complexity. The second major contribution of this thesis is a proposed adaptive method for user ordering for Successive Decision Feedback multi-user Detectors (S-DFD). The method is shown to outperform all previously proposed ordering methods delivering significant improvement in SNR-BER characteristic. The analysis of S-DFD has revealed that a proper user ordering can significantly improve the performance of the system. The proposed ordering has also been implemented in the adaptive iterative S-DFD improving the BER performance especially after the first turbo iteration since this is the most critical part, which determines the SNR floor at which the Turbo effect starts.
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