63 research outputs found

    Wavelet-based multi-carrier code division multiple access systems

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    EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years

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    Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions

    On the performance and capacity of space-time block coded multicarrier CDMA communication systems

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    Ph.DDOCTOR OF PHILOSOPH

    Reduced Complexity Sequential Monte Carlo Algorithms for Blind Receivers

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    Monte Carlo algorithms can be used to estimate the state of a system given relative observations. In this dissertation, these algorithms are applied to physical layer communications system models to estimate channel state information, to obtain soft information about transmitted symbols or multiple access interference, or to obtain estimates of all of these by joint estimation. Initially, we develop and analyze a multiple access technique utilizing mutually orthogonal complementary sets (MOCS) of sequences. These codes deliberately introduce inter-chip interference, which is naturally eliminated during processing at the receiver. However, channel impairments can destroy their orthogonality properties and additional processing becomes necessary. We utilize Monte Carlo algorithms to perform joint channel and symbol estimation for systems utilizing MOCS sequences as spreading codes. We apply Rao-Blackwellization to reduce the required number of particles. However, dense signaling constellations, multiuser environments, and the interchannel interference introduced by the spreading codes all increase the dimensionality of the symbol state space significantly. A full maximum likelihood solution is computationally expensive and generally not practical. However, obtaining the optimum solution is critical, and looking at only a part of the symbol space is generally not a good solution. We have sought algorithms that would guarantee that the correct transmitted symbol is considered, while only sampling a portion of the full symbol space. The performance of the proposed method is comparable to the Maximum Likelihood (ML) algorithm. While the computational complexity of ML increases exponentially with the dimensionality of the problem, the complexity of our approach increases only quadratically. Markovian structures such as the one imposed by MOCS spreading sequences can be seen in other physical layer structures as well. We have applied this partitioning approach with some modification to blind equalization of frequency selective fading channel and to multiple-input multiple output receivers that track channel changes. Additionally, we develop a method that obtains a metric for quantifying the convergence rate of Monte Carlo algorithms. Our approach yields an eigenvalue based method that is useful in identifying sources of slow convergence and estimation inaccuracy.Ph.D.Committee Chair: Douglas B. Williams; Committee Member: Brani Vidakovic; Committee Member: G. Tong zhou; Committee Member: Gordon Stuber; Committee Member: James H. McClella

    Soft detection and decoding in wideband CDMA systems

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    A major shift is taking place in the world of telecommunications towards a communications environment where a range of new data services will be available for mobile users. This shift is already visible in several areas of wireless communications, including cellular systems, wireless LANs, and satellite systems. The provision of flexible high-quality wireless data services requires a new approach on both the radio interface specification and the design and the implementation of the various transceiver algorithms. On the other hand, when the processing power available in the receivers increases, more complex receiver algorithms become feasible. The general problem addressed in this thesis is the application of soft detection and decoding algorithms in the wideband code division multiple access (WCDMA) receivers, both in the base stations and in the mobile terminals, so that good performance is achieved but that the computational complexity remains acceptable. In particular, two applications of soft detection and soft decoding are studied: coded multiuser detection in the CDMA base station and improved RAKE-based reception employing soft detection in the mobile terminal. For coded multiuser detection, we propose a novel receiver structure that utilizes the decoding information for multiuser detection. We analyze the performance and derive lower bounds for the capacity of interference cancellation CDMA receivers when using channel coding to improve the reliability of tentative decisions. For soft decision and decoding techniques in the CDMA downlink, we propose a modified maximal ratio combining (MRC) scheme that is more suitable for RAKE receivers in WCDMA mobile terminals than the conventional MRC scheme. We also introduce an improved soft-output RAKE detector that is especially suitable for low spreading gains and high-order modulation schemes. Finally we analyze the gain obtained through the use of Brennan's MRC scheme and our modified MRC scheme. Throughout this thesis Bayesian networks are utilized to develop algorithms for soft detection and decoding problems. This approach originates from the initial stages of this research, where Bayesian networks and algorithms using such graphical models (e.g. the so-called sum-product algorithm) were used to identify new receiver algorithms. In the end, this viewpoint may not be easily noticeable in the final form of the algorithms, mainly because the practical efficiency considerations forced us to select simplified variants of the algorithms. However, this viewpoint is important to emphasize the underlying connection between the apparently different soft detection and decision algorithms described in this thesis.reviewe

    Soft-in soft-output detection in the presence of parametric uncertainty via the Bayesian EM algorithm

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    We investigate the application of the Bayesian expectation-maximization (BEM) technique to the design of soft-in soft-out (SISO) detection algorithms for wireless communication systems operating over channels affected by parametric uncertainty. First, the BEM algorithm is described in detail and its relationship with the well-known expectation-maximization (EM) technique is explained. Then, some of its applications are illustrated. In particular, the problems of SISO detection of spread spectrum, single-carrier and multicarrier space-time block coded signals are analyzed. Numerical results show that BEM-based detectors perform closely to the maximum likelihood (ML) receivers endowed with perfect channel state information as long as channel variations are not too fast

    Blind source separation for interference cancellation in CDMA systems

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    Communication is the science of "reliable" transfer of information between two parties, in the sense that the information reaches the intended party with as few errors as possible. Modern wireless systems have many interfering sources that hinder reliable communication. The performance of receivers severely deteriorates in the presence of unknown or unaccounted interference. The goal of a receiver is then to combat these sources of interference in a robust manner while trying to optimize the trade-off between gain and computational complexity. Conventional methods mitigate these sources of interference by taking into account all available information and at times seeking additional information e.g., channel characteristics, direction of arrival, etc. This usually costs bandwidth. This thesis examines the issue of developing mitigating algorithms that utilize as little as possible or no prior information about the nature of the interference. These methods are either semi-blind, in the former case, or blind in the latter case. Blind source separation (BSS) involves solving a source separation problem with very little prior information. A popular framework for solving the BSS problem is independent component analysis (ICA). This thesis combines techniques of ICA with conventional signal detection to cancel out unaccounted sources of interference. Combining an ICA element to standard techniques enables a robust and computationally efficient structure. This thesis proposes switching techniques based on BSS/ICA effectively to combat interference. Additionally, a structure based on a generalized framework termed as denoising source separation (DSS) is presented. In cases where more information is known about the nature of interference, it is natural to incorporate this knowledge in the separation process, so finally this thesis looks at the issue of using some prior knowledge in these techniques. In the simple case, the advantage of using priors should at least lead to faster algorithms.reviewe

    MIMO-aided near-capacity turbo transceivers: taxonomy and performance versus complexity

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    In this treatise, we firstly review the associated Multiple-Input Multiple-Output (MIMO) system theory and review the family of hard-decision and soft-decision based detection algorithms in the context of Spatial Division Multiplexing (SDM) systems. Our discussions culminate in the introduction of a range of powerful novel MIMO detectors, such as for example Markov Chain assisted Minimum Bit-Error Rate (MC-MBER) detectors, which are capable of reliably operating in the challenging high-importance rank-deficient scenarios, where there are more transmitters than receivers and hence the resultant channel-matrix becomes non-invertible. As a result, conventional detectors would exhibit a high residual error floor. We then invoke the Soft-Input Soft-Output (SISO) MIMO detectors for creating turbo-detected two- or three-stage concatenated SDM schemes and investigate their attainable performance in the light of their computational complexity. Finally, we introduce the powerful design tools of EXtrinsic Information Transfer (EXIT)-charts and characterize the achievable performance of the diverse near- capacity SISO detectors with the aid of EXIT charts
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