Orthogonal frequency division multiplexing (OFDM) system is the standard of next generation mobile communication, one of the major drawbacks of OFDM systems is the peak-to-average power ratio (PAPR). In this paper, we proposed a low complexity Selected mapping (SLM) scheme to reduce PAPR. In [27], Wang proposed a low complexity SLM scheme by utilizing conversion vectors having the form of a perfect sequence to solve the problem that phase rotation vectors of the conversion vectors do not usually have an equal magnitude in frequency domain. This paper proposed a low complexity SLM scheme based on perfect sequence and consider the symbol interleaving to reduce the correlation between signals in time domain. It is shown that the (Complementary Cumulative Distribution Function, CCDF) of our proposed scheme are closer to the traditional SLM scheme than Wang¡¦s in [27] but with additional complexity. And the computational complexity is much lower than traditional SLM.

A Web-server farm is a specialized facility designed specifically for housing Web servers catering to one or more Internet facing Web sites. In this dissertation, stochastic dynamic programming technique is used to obtain the optimal admission control policy with different classes of customers, and stochastic uid- ow models are used to compute the performance measures in the network. The two types of network traffic considered in this research are streaming (guaranteed bandwidth per connection) and elastic (shares available bandwidth equally among connections). We first obtain the optimal admission control policy using stochastic dynamic programming, in which, based on the number of requests of each type being served, a decision is made whether to allow or deny service to an incoming request. In this subproblem, we consider a xed bandwidth capacity server, which allocates the requested bandwidth to the streaming requests and divides all of the remaining bandwidth equally among all of the elastic requests. The performance metric of interest in this case will be the blocking probability of streaming traffic, which will be computed in order to be able to provide Quality of Service (QoS) guarantees. Next, we obtain bounds on the expected waiting time in the system for elastic requests that enter the system. This will be done at the server level in such a way that the total available bandwidth for the requests is constant. Trace data will be converted to an ON-OFF source and fluid- flow models will be used for this analysis. The results are compared with both the mean waiting time obtained by simulating real data, and the expected waiting time obtained using traditional queueing models. Finally, we consider the network of servers and routers within the Web farm where data from servers flows and merges before getting transmitted to the requesting users via the Internet. We compute the waiting time of the elastic requests at intermediate and edge nodes by obtaining the distribution of the out ow of the upstream node. This out ow distribution is obtained by using a methodology based on minimizing the deviations from the constituent in flows. This analysis also helps us to compute waiting times at different bandwidth capacities, and hence obtain a suitable bandwidth to promise or satisfy the QoS guarantees. This research helps in obtaining performance measures for different traffic classes at a Web-server farm so as to be able to promise or provide QoS guarantees; while at the same time helping in utilizing the resources of the server farms efficiently, thereby reducing the operational costs and increasing energy savings.

Along with the rapidly increasing demand for high data rate communications, orthogonal frequency division multiplexing (OFDM) has become a popular modulation in current and future communication standards. By distributing a high-speed data stream to many parallel low-rate data streams, OFDM is able to mitigate the detrimental effects of multipath fading using simple one-tap equalizers and achieve high spectral efficiency. However, the OFDM signal waveform suffers from large envelop variations, which are usually measured by the peak-to-average power ratio (PAR). In wireless transmitters, many RF components, especially the power amplifiers, are inherently nonlinear and peak power constrained. Therefore, low power efficiency and/or severe nonlinear distortions are the main shortcomings of OFDM systems. In this dissertation, we develop algorithms and analyze performance bounds for peak power constrained wireless communications. To address the balance between power efficiency and nonlinear distortions, we model the peak power constrained OFDM systems in both statistical and deterministic manners. We first propose an error vector magnitude (EVM) optimization algorithm to strictly satisfy the distortion requirements in accordance with communication standards and provide the maximum power efficiency for OFDM transmitters without receiver-side cooperations. Moreover, we develop a multi-channel partial transmit sequence (MCPTS) PAR reduction method for OFDM-based frequency-division multiple access (OFDM-FDMA) multiuser systems, which can achieve significant power efficiency improvement without using side information. Joint MCPTS and power allocation schemes are also proposed to improve the error performance of OFDM-FDMA systems. Furthermore, diversity-enabled communication systems have practical merits in combating channel fadings. Therefore, in the second part of this dissertation, peak power constrained diversity techniques are proposed. The error performance of peak power constrained single-input multiple-output (SIMO) OFDM is studied. Several low-complexity SIMO-OFDM transceiver designs are presented to collect full antenna diversity with respective performance and complexity tradeoffs. The next major piece of work in this dissertation addresses the design of peak power constrained amplify-and-forward (AF) cooperative networks, which enable the cooperative diversity with single-antenna terminals. The effects of the availability of channel state information and the peak power constraint on the diversity performance are theoretically studied. Design criteria for general diversity-enabled AF relaying strategies are established and further applied to the designs in peak power constrained networks. In the end, a general theorem that relates the diversity gain function with the probability density function of instantaneous signal-to-noise ratio is derived and used to analyze the diversity performance of relay selection schemes.

Title from PDF of title page. / Document formatted into pages; contains 62 pages / Thesis (M.S.E.E.)--University of South Florida, 2003. / Includes bibliographical references. / Text (Electronic thesis) in PDF format. / ABSTRACT: The GSM platform is a extremely successful wireless technology and an unprecedented story of global achievement. The GSM platform is growing and evolving and offers an expanded and feature-rich voice and data enabling services. General Packet Radio Service, (GPRS), will have a tremendous transmission rate, which will make a significant impact on most of the existing services. Additionally, GPRS stands ready for the introduction of new services as operators and users, both business and private, appreciate the capabilities and potential that GPRS provides. Services such as the Internet, videoconferencing and on-line shopping will be as smooth as talking on the phone. Moreover, the capability and ease of access to these services increase at work, at home or during travel. In this research the traffic channel of a GSM system was studied in detail and simulated in order to obtain a performance analysis. Matlab, software from Mathworks, was used for the simulation. / ABSTRACT: Both the forward and the reverse links of a GSM system were simulated. A flat fading model was used to model the channel. Signal to Noise Ratio, (SNR), was the primary metric that was varied during the simulation. All the building blocks for a traffic channel, including a Convolutional encoder, an Interleaver and a Modulator were coded in Matlab. Finally the GPRS system, which is an enhancement of the GSM system for data services was introduced. / System requirements: World Wide Web browser and PDF reader. / Mode of access: World Wide Web.

Use of imaging systems for performing various situational awareness tasks in militaryand commercial settings has a long history. There is increasing recognition,however, that a much better job can be done by developing non-traditional opticalsystems that exploit the task-specific system aspects within the imager itself. Insome cases, a direct consequence of this approach can be real-time data compressionalong with increased measurement fidelity of the task-specific features. In others,compression can potentially allow us to perform high-level tasks such as direct trackingusing the compressed measurements without reconstructing the scene of interest.In this dissertation we present novel advancements in feature-specific (FS) imagersfor large field-of-view surveillence, and estimation of temporal object-scene changesutilizing the compressive imaging paradigm. We develop these two ideas in parallel.In the first case we show a feature-specific (FS) imager that optically multiplexesmultiple, encoded sub-fields of view onto a common focal plane. Sub-field encodingenables target tracking by creating a unique connection between target characteristicsin superposition space and the target's true position in real space. This isaccomplished without reconstructing a conventional image of the large field of view.System performance is evaluated in terms of two criteria: average decoding time andprobability of decoding error. We study these performance criteria as a functionof resolution in the encoding scheme and signal-to-noise ratio. We also includesimulation and experimental results demonstrating our novel tracking method. Inthe second case we present a FS imager for estimating temporal changes in the objectscene over time by quantifying these changes through a sequence of differenceimages. The difference images are estimated by taking compressive measurementsof the scene. Our goals are twofold. First, to design the optimal sensing matrixfor taking compressive measurements. In scenarios where such sensing matrices arenot tractable, we consider plausible candidate sensing matrices that either use theavailable <italic>a priori</italic> information or are non-adaptive. Second, we develop closed-form and iterative techniques for estimating the difference images. We present results to show the efficacy of these techniques and discuss the advantages of each.

Modern networks carry a wide range of different data types, each with its own individual requirements. The scheduler plays an important role in enabling a network to meet all these requirements. In wired networks a large amount of research has been performed on various schedulers, most of which belong to the family of General Processor Sharing (GPS) schedulers. In this dissertation we briefly discuss the work that has been done on a range of wired schedulers, which all attempt to differentiate between heterogeneous traffic. In the world of wireless communications the scheduler plays a very important role, since it can take channel conditions into account to further improve the performance of the network. The main focus of this dissertation is to introduce schedulers, which attempt to meet the Quality of Service requirements of various data types in a wireless environment. Examples of schedulers that take channel conditions into account are the Modified Largest Weighted Delay First (M-LWDF), as well as a new scheduler introduced in this dissertation, known as the Wireless Fair Largest Weighted Delay First (WF-LWDF) algorithm. The two schemes are studied in detail and a comparison of their throughput, delay, power, and packet dropping performance is made through a range of simulations. The results are compared to the performance offour other schedulers. The fairness ofM-LWDF and WFLWDF is determined through simulations. The throughput results are used to establish Chernoff bounds of the fairness of these two algorithms. Finally, a summary is given of the published delay bounds of various schedulers, and the tightness of the resultant bounds is discussed. / Thesis (M.Sc. Eng.)-University of Natal, Durban, 2003.

It is often required in communication and navigation systems to be able to receive signals from multiple stations simultaneously. A common practice to do this is to use multiple hardware resources; a different set of resources for each station. In this thesis, a Coherent Amplitude Modulated (AM) receiver system was developed based on Software Defined Radio (SDR) technology enabling reception of multiple signals using hardware resources needed only for one station. The receiver system architecture employs Time Division Multiplexing (TDM) to share the single hardware resource among multiple streams of data. The architecture is designed so that it can be minimally modified to support any number of stations. The Verilog Hardware Description Language (HDL) was used to capture the receiver system architecture and design. The design and architecture are initially validated using HDL post-synthesis and post-implementation simulation. In addition, the receiver system architecture and design were implemented to a Xilinx Field Programmable Gate Array (FPGA) technology prototyping board for experimental testing and final validation.

The diagnosis and monitoring of AML relies predominantly on the identification of blast cells in the bone marrow and peripheral blood. While at the time of diagnosis the identification of leukemic cells is relatively easy, during remission the identification of small numbers of blasts is problematic. This is most evident by the fact that patients who achieve complete remission frequently relapse, despite pathologic examination indicating a marked reduction in leukemic cell burden. In this thesis I have explored the potential of using serum proteins secreted by leukemic cells as a means of monitoring disease in patients. To identify proteins that might be useful for monitoring, I took advantage of published gene expression arrays and looked into online bioinformatics databases. Using specific characteristics, I was able to identify approximately 107 candidate proteins secreted by AML cells. RT-PCR analysis and ELISA assays were performed to evaluate the variability of expressions and serum level differences of twelve different proteins in the list.

The diagnosis and monitoring of AML relies predominantly on the identification of blast cells in the bone marrow and peripheral blood. While at the time of diagnosis the identification of leukemic cells is relatively easy, during remission the identification of small numbers of blasts is problematic. This is most evident by the fact that patients who achieve complete remission frequently relapse, despite pathologic examination indicating a marked reduction in leukemic cell burden. In this thesis I have explored the potential of using serum proteins secreted by leukemic cells as a means of monitoring disease in patients. To identify proteins that might be useful for monitoring, I took advantage of published gene expression arrays and looked into online bioinformatics databases. Using specific characteristics, I was able to identify approximately 107 candidate proteins secreted by AML cells. RT-PCR analysis and ELISA assays were performed to evaluate the variability of expressions and serum level differences of twelve different proteins in the list.

The theory of lattices --- a mathematical approach for representing infinite discrete points in Euclidean space, has become a powerful tool to analyze many point-to-point digital and wireless communication systems, particularly, communication systems that can be well-described by the linear Gaussian vector channel model. This is mainly due to the three facts about channel codes constructed using lattices: they have simple structure, their ability to achieve the fundamental limits (the capacity) of the channel, and most importantly, they can be decoded using efficient decoders called lattice decoders. Since its introduction to multiple-input multiple-output (MIMO) wireless communication systems, sphere decoders has become an attractive efficient implementation of lattice decoders, especially for small signal dimensions and/or moderate to large signal-to-noise ratios (SNRs). In the first part of this dissertation, we consider sphere decoding algorithms that describe lattice decoding. The exact complexity analysis of the basic sphere decoder for general space-time codes applied to MIMO wireless channel is known to be difficult. Characterizing and understanding the complexity distribution is important, especially when the sphere decoder is used under practically relevant runtime constraints. In this work, we shed the light on the (average) computational complexity of sphere decoding for the quasi-static, LAttice Space-Time (LAST) coded MIMO channel. Sphere decoders are only efficient in the high SNR regime and low signal dimensions, and exhibits exponential (average) complexity for low-to-moderate SNR and large signal dimensions. On the other extreme, linear and non-linear receivers such as minimum mean-square error (MMSE), and MMSE decision-feedback equalization (DFE) are considered attractive alternatives to sphere decoders in MIMO channels. Unfortunately, the very low decoding complexity advantage that these decoders can provide comes at the expense of poor performance, especially for large signal dimensions. The problem of designing low complexity receivers for the MIMO channel that achieve near-optimal performance is considered a challenging problem and has driven much research in the past years. The problem can solved through the use of lattice sequential decoding that is capable of bridging the gap between sphere decoders and low complexity linear decoders (e.g., MMSE-DFE decoder). In the second part of this thesis, the asymptotic performance of the lattice sequential decoder for LAST coded MIMO channel is analyzed. We determine the rates achievable by lattice coding and sequential decoding applied to such a channel. The diversity-multiplexing tradeoff under such a decoder is derived as a function of its parameter--- the bias term. In this work, we analyze both the computational complexity distribution and the average complexity of such a decoder in the high SNR regime. We show that there exists a cut-off multiplexing gain for which the average computational complexity of the decoder remains bounded. Our analysis reveals that there exists a finite probability that the number of computations performed by the decoder may become excessive, even at high SNR, during high channel noise. This probability is usually referred to as the probability of a decoding failure. Such probability limits the performance of the lattice sequential decoder, especially for a one-way communication system. For a two-way communication system, such as in MIMO Automatic Repeat reQuest (ARQ) system, the feedback channel can be used to eliminate the decoding failure probability. In this work, we modify the lattice sequential decoder for the MIMO ARQ channel, to predict in advance the occurrence of decoding failure to avoid wasting the time trying to decode the message. This would result in a huge saving in decoding complexity. In particular, we will study the throughput-performance-complexity tradeoffs in sequential decoding algorithms and the effect of preprocessing and termination strategies. We show, analytically and via simulation, that using the lattice sequential decoder that implements a simple yet efficient time-out algorithm for joint error detection and correction, the optimal tradeoff of the MIMO ARQ channel can be achieved with significant reduction in decoding complexity.