70 research outputs found

    Advanced receivers for distributed cooperation in mobile ad hoc networks

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    Mobile ad hoc networks (MANETs) are rapidly deployable wireless communications systems, operating with minimal coordination in order to avoid spectral efficiency losses caused by overhead. Cooperative transmission schemes are attractive for MANETs, but the distributed nature of such protocols comes with an increased level of interference, whose impact is further amplified by the need to push the limits of energy and spectral efficiency. Hence, the impact of interference has to be mitigated through with the use PHY layer signal processing algorithms with reasonable computational complexity. Recent advances in iterative digital receiver design techniques exploit approximate Bayesian inference and derivative message passing techniques to improve the capabilities of well-established turbo detectors. In particular, expectation propagation (EP) is a flexible technique which offers attractive complexity-performance trade-offs in situations where conventional belief propagation is limited by computational complexity. Moreover, thanks to emerging techniques in deep learning, such iterative structures are cast into deep detection networks, where learning the algorithmic hyper-parameters further improves receiver performance. In this thesis, EP-based finite-impulse response decision feedback equalizers are designed, and they achieve significant improvements, especially in high spectral efficiency applications, over more conventional turbo-equalization techniques, while having the advantage of being asymptotically predictable. A framework for designing frequency-domain EP-based receivers is proposed, in order to obtain detection architectures with low computational complexity. This framework is theoretically and numerically analysed with a focus on channel equalization, and then it is also extended to handle detection for time-varying channels and multiple-antenna systems. The design of multiple-user detectors and the impact of channel estimation are also explored to understand the capabilities and limits of this framework. Finally, a finite-length performance prediction method is presented for carrying out link abstraction for the EP-based frequency domain equalizer. The impact of accurate physical layer modelling is evaluated in the context of cooperative broadcasting in tactical MANETs, thanks to a flexible MAC-level simulato

    Adaptive implementation of turbo multi-user detection architecture

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    MULTI-access techniques have been adopted widely for communications in underwater acoustic channels, which present many challenges to the development of reliable and practical systems. In such an environment, the unpredictable and complex ocean conditions cause the acoustic waves to be affected by many factors such as limited bandwidth, large propagation losses, time variations and long latency, which limit the usefulness of such techniques. Additionally, multiple access interference (MAI) signals and poor estimation of the unknown channel parameters in the presence of limited training sequences are two of the major problems that degrade the performance of such technologies. In this thesis, two different single-element multi-access schemes, interleave division multiple access (IDMA) and code division multiple access (CDMA), employing decision feedback equalization (DFE) and soft Rake-based architectures, are proposed for multi-user underwater communication applications. By using either multiplexing pilots or continuous pilots, these adaptive turbo architectures with carrier phase tracking are jointly optimized based on the minimum mean square error (MMSE) criterion and adapted iteratively by exchanging soft information in terms of Log-Likelihood Ratio (LLR) estimates with the single-user’s channel decoders. The soft-Rake receivers utilize developed channel estimation and the detection is implemented using parallel interference cancellation (PIC) to remove MAI effects between users. These architectures are investigated and applied to simulated data and data obtained from realistic underwater communication trials using off-line processing of signals acquired during sea-trials in the North Sea. The results of different scenarios demonstrate the penalty in performance as the fading induces irreducible error rates that increase with channel delay spread and emphasize the benefits of using coherent direct adaptive receivers in such reverberant channels. The convergence behaviour of the detectors is evaluated using EXIT chart analyses and issues such as the adaptation parameters and their effects on the performance are also investigated. However, in some cases the receivers with partial knowledge of the interleavers’ patterns or codes can still achieve performance comparable to those with full knowledge. Furthermore, the thesis describes implementation issues of these algorithms using digital signal processors (DSPs), such as computational complexity and provides valuable guidelines for the design of real time underwater communication systems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Adaptive implementation of turbo multi-user detection architecture

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    MULTI-access techniques have been adopted widely for communications in underwater acoustic channels, which present many challenges to the development of reliable and practical systems. In such an environment, the unpredictable and complex ocean conditions cause the acoustic waves to be affected by many factors such as limited bandwidth, large propagation losses, time variations and long latency, which limit the usefulness of such techniques. Additionally, multiple access interference (MAI) signals and poor estimation of the unknown channel parameters in the presence of limited training sequences are two of the major problems that degrade the performance of such technologies. In this thesis, two different single-element multi-access schemes, interleave division multiple access (IDMA) and code division multiple access (CDMA), employing decision feedback equalization (DFE) and soft Rake-based architectures, are proposed for multi-user underwater communication applications. By using either multiplexing pilots or continuous pilots, these adaptive turbo architectures with carrier phase tracking are jointly optimized based on the minimum mean square error (MMSE) criterion and adapted iteratively by exchanging soft information in terms of Log-Likelihood Ratio (LLR) estimates with the single-user’s channel decoders. The soft-Rake receivers utilize developed channel estimation and the detection is implemented using parallel interference cancellation (PIC) to remove MAI effects between users. These architectures are investigated and applied to simulated data and data obtained from realistic underwater communication trials using off-line processing of signals acquired during sea-trials in the North Sea. The results of different scenarios demonstrate the penalty in performance as the fading induces irreducible error rates that increase with channel delay spread and emphasize the benefits of using coherent direct adaptive receivers in such reverberant channels. The convergence behaviour of the detectors is evaluated using EXIT chart analyses and issues such as the adaptation parameters and their effects on the performance are also investigated. However, in some cases the receivers with partial knowledge of the interleavers’ patterns or codes can still achieve performance comparable to those with full knowledge. Furthermore, the thesis describes implementation issues of these algorithms using digital signal processors (DSPs), such as computational complexity and provides valuable guidelines for the design of real time underwater communication systems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Façonnement de l'Interférence en vue d'une Optimisation Globale d'un Système Moderne de Communication

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    A communication is impulsive whenever the information-bearing signal is burst-like in time. Examples of the impulsive concept are: impulse-radio signals, that is, wireless signals occurring within short intervals of time; optical signals conveyed by photons; speech signals represented by sound pressure variations; pulse-position modulated electrical signals; a sequence of arrival/departure events in a queue; neural spike trains in the brain. Understanding impulsive communications requires to identify what is peculiar to this transmission paradigm, that is, different from traditional continuous communications.In order to address the problem of understanding impulsive vs. non-impulsive communications, the framework of investigation must include the following aspects: the different interference statistics directly following from the impulsive signal structure; the different interaction of the impulsive signal with the physical medium; the actual possibility for impulsive communications of coding information into the time structure, relaxing the implicit assumption made in continuous transmissions that time is a mere support. This thesis partially addresses a few of the above issues, and draws future lines of investigation. In particular, we studied: multiple access channels where each user adopts time-hopping spread-spectrum; systems using a specific prefilter at the transmitter side, namely the transmit matched filter (also known as time reversal), particularly suited for ultrawide bandwidhts; the distribution function of interference for impulsive systems in several different settings.Une communication est impulsive chaque fois que le signal portant des informations est intermittent dans le temps et que la transmission se produit à rafales. Des exemples du concept impulsife sont : les signaux radio impulsifs, c’est-à-dire des signaux très courts dans le temps; les signaux optiques utilisé dans les systèmes de télécommunications; certains signaux acoustiques et, en particulier, les impulsions produites par le système glottale; les signaux électriques modulés en position d’impulsions; une séquence d’événements dans une file d’attente; les trains de potentiels neuronaux dans le système neuronal. Ce paradigme de transmission est différent des communications continues traditionnelles et la compréhension des communications impulsives est donc essentielle. Afin d’affronter le problème des communications impulsives, le cadre de la recherche doit inclure les aspects suivants : la statistique d’interférence qui suit directement la structure des signaux impulsifs; l’interaction du signal impulsif avec le milieu physique; la possibilité pour les communications impulsives de coder l’information dans la structure temporelle. Cette thèse adresse une partie des questions précédentes et trace des lignes indicatives pour de futures recherches. En particulier, nous avons étudié: un système d'accès multiple où les utilisateurs adoptent des signaux avec étalement de spectre par saut temporel (time-hopping spread spectrum) pour communiquer vers un récepteur commun; un système avec un préfiltre à l'émetteur, et plus précisément un transmit matched filter, également connu comme time reversal dans la littérature de systèmes à bande ultra large; un modèle d'interférence pour des signaux impulsifs

    Digitally Enhanced Interferometry for Precision Metrology

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    In this thesis we employ Digitally Enhanced Interferometric techniques to manage, measure or reject spurious interference. The technique, by using digitally controlled spread-spectrum modulation, manipulates the coherence of an optical source, enabling selective decoding of optical fields based on time-of-flight. Through this thesis, we demonstrate the use of this technique across three scenarios. Firstly, in Part 1, we consider the application to quasi-distributed interferometric sensing in the form of a multi-point interferometric acoustic sensing array. Using Digitally Enhanced Heterodyne interferometry, we demonstrate simultaneous readout from four discrete in-line surfaces using a single measurement optical field. The demonstration characterises the displacement sensitivity of the measurement system, and proceeds to characterise the residual cross-coupling between the independent reflection surfaces. We further demonstrate some of the limitations of the digitally enhanced readout when considering equidistant targets, which has ramifications for multi-point sensing applications such as LIDAR. The second body of work, presented in Part 2, discuses the continued development of the Digitally Enhanced Fibre Frequency Reference. In this instance, we consider the coupling of coherent Rayleigh backscatter into the interferometric measurement. Using Digitally Enhanced Homodyne interferometry, we enable digital manipulation of the coherence length, thereby restricting the coupling of Rayleigh backscatter. The resultant phase noise is both modelled and measured, with good agreement between both. We further implement a method, using a Rubidium stabilised optical frequency comb, to measure the long term drift of the fibre frequency reference. From this we are able to infer the thermal performance of the interferometer isolation chambers, the therm-optic and thermo-elastic expansion of the interferometer. From these insights, we continue on to develop a nominal design for a future fibre frequency reference architecture. The third and final project; Part 3, considers the implementation of a Digitally Enhanced Homodyne interferometric readout to a Sagnac interferometer. The objective of this work was to demonstrate rejection of first order Rayleigh scattering, and was informed by the work on Rayleigh scattering in Part 2. As part of this project, we also demonstrate the first demonstration of a digital interferometric readout using an incoherent source, one which is significantly broader than the digital interferometric spread-spectrum modulation. We also present a first demonstration of sub 1 urad/rt(Hz) noise floor using a digital interferometric readout. Finally, we also surpass the theoretical Rayleigh backscatter induced phase noise floor by over an order of magnitude, demonstrating rejection of first order Rayleigh scattering

    MIMO Systems

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    In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

    Joint Communication and Positioning based on Channel Estimation

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    Mobile wireless communication systems have rapidly and globally become an integral part of everyday life and have brought forth the internet of things. With the evolution of mobile wireless communication systems, joint communication and positioning becomes increasingly important and enables a growing range of new applications. Humanity has already grown used to having access to multimedia data everywhere at every time and thereby employing all sorts of location-based services. Global navigation satellite systems can provide highly accurate positioning results whenever a line-of-sight path is available. Unfortunately, harsh physical environments are known to degrade the performance of existing systems. Therefore, ground-based systems can assist the existing position estimation gained by satellite systems. Determining positioning-relevant information from a unified signal structure designed for a ground-based joint communication and positioning system can either complement existing systems or substitute them. Such a system framework promises to enhance the existing systems by enabling a highly accurate and reliable positioning performance and increased coverage. Furthermore, the unified signal structure yields synergetic effects. In this thesis, I propose a channel estimation-based joint communication and positioning system that employs a virtual training matrix. This matrix consists of a relatively small training percentage, plus the detected communication data itself. Via a core semi- blind estimation approach, this iteratively includes the already detected data to accurately determine the positioning-relevant parameter, by mutually exchanging information between the communication part and the positioning part of the receiver. Synergy is created. I propose a generalized system framework, suitable to be used in conjunction with various communication system techniques. The most critical positioning-relevant parameter, the time-of-arrival, is part of a physical multipath parameter vector. Estimating the time-of-arrival, therefore, means solving a global, non-linear, multi-dimensional optimization problem. More precisely, it means solving the so-called inverse problem. I thoroughly assess various problem formulations and variations thereof, including several different measurements and estimation algorithms. A significant challenge, when it comes to solving the inverse problem to determine the positioning-relevant path parameters, is imposed by realistic multipath channels. Most parameter estimation algorithms have proven to perform well in moderate multipath environments. It is mathematically straightforward to optimize this performance in the sense that the number of observations has to exceed the number of parameters to be estimated. The typical parameter estimation problem, on the other hand, is based on channel estimates, and it assumes that so-called snapshot measurements are available. In the case of realistic channel models, however, the number of observations does not necessarily exceed the number of unknowns. In this thesis, I overcome this problem, proposing a method to reduce the problem dimensionality via joint model order selection and parameter estimation. Employing the approximated and estimated parameter covariance matrix inherently constrains the estimation problem’s model order selection to result in optimal parameter estimation performance and hence optimal positioning performance. To compare these results with the optimally achievable solution, I introduce a focused order-related lower bound in this thesis. Additionally, I use soft information as a weighting matrix to enhance the positioning algorithm positioning performance. For demonstrating the feasibility and the interplay of the proposed system components, I utilize a prototype system, based on multi-layer interleave division multiple access. This proposed system framework and the investigated techniques can be employed for multiple existing systems or build the basis for future joint communication and positioning systems. The assessed estimation algorithms are transferrable to all kinds of joint communication and positioning system designs. This thesis demonstrates their capability to, in principle, successfully cope with challenging estimation problems stemming from harsh physical environments

    Iterative Receiver Techniques for Data-Driven Channel Estimation and Interference Mitigation in Wireless Communications

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    Wireless mobile communications were initially a way for people to communicate through low data rate voice call connections. As data enabled devices allow users the ability to do much more with their mobile devices, so to will the demand for more reliable and pervasive wireless data. This is being addressed by so-called 4th generation wireless systems based on orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) antenna systems. Mobile wireless customers are becoming more demanding and expecting to have a great user experience over high speed broadband access at any time and anywhere, both indoor and outdoor. However, these promising improvements cannot be realized without an e±cient design of the receiver. Recently, receivers utilizing iterative detection and decoding have changed the fundamental receiver design paradigm from traditional separated parameter estimation and data detection blocks to an integrated iterative parameter estimator and data detection unit. Motivated by this iterative data driven approach, we develop low complexity iterative receivers with improved sensitivity compared to the conventional receivers, this brings potential benefits for the wireless communication system, such as improving the overall system throughput, increasing the macro cell coverage, and reducing the cost of the equipments in both the base station and mobile terminal. It is a challenge to design receivers that have good performance in a highly dynamic mobile wireless environment. One of the challenges is to minimize overhead reference signal energy (preamble, pilot symbols) without compromising the performance. We investigate this problem, and develop an iterative receiver with enhanced data-driven channel estimation. We discuss practical realizations of the iterative receiver for SISO-OFDM system. We utilize the channel estimation from soft decoded data (the a priori information) through frequency-domain combining and time-domain combining strategies in parallel with limited pilot signals. We analyze the performance and complexity of the iterative receiver, and show that the receiver's sensitivity can be improved even with this low complexity solution. Hence, seamless communications can be achieved with better macro cell coverage and mobility without compromising the overall system performance. Another challenge is that a massive amount of interference caused by MIMO transmission (spatial multiplexing MIMO) reduces the performance of the channel estimation, and further degrades data detection performance. We extend the iterative channel estimation from SISO systems to MIMO systems, and work with linear detection methods to perform joint interference mitigation and channel estimation. We further show the robustness of the iterative receivers in both indoor and outdoor environment compared to the conventional receiver approach. Finally, we develop low complexity iterative spatial multiplexed MIMO receivers for nonlinear methods based on two known techniques, that is, the Sphere Decoder (SD) method and the Markov Chain Monte Carlo (MCMC) method. These methods have superior performance, however, they typically demand a substantial increase in computational complexity, which is not favorable in practical realizations. We investigate and show for the first time how to utilize the a priori information in these methods to achieve performance enhancement while simultaneously substantially reducing the computational complexity. In our modified sphere decoder method, we introduce a new accumulated a priori metric in the tree node enumeration process. We show how we can improve the performance by obtaining the reliable tree node candidate from the joint Maximum Likelihood (ML) metric and an approximated a priori metric. We also show how we can improve the convergence speed of the sphere decoder (i.e., reduce the com- plexity) by selecting the node with the highest a priori probability as the starting node in the enumeration process. In our modified MCMC method, the a priori information is utilized for the firrst time to qualify the reliably decoded bits from the entire signal space. Two new robust MCMC methods are developed to deal with the unreliable bits by using the reliably decoded bit information to cancel the interference that they generate. We show through complexity analysis and performance comparison that these new techniques have improved performance compared to the conventional approaches, and further complexity reduction can be obtained with the assistance of the a priori information. Therefore, the complexity and performance tradeoff of these nonlinear methods can be optimized for practical realizations

    Characterizing radio channels : the science and technology of propagation and interference, 1900-1935

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    Thesis (Ph. D. in History and Social Study of Science and Technology (HASTS))--Massachusetts Institute of Technology, Program in Science, Technology and Society, 2004.Includes bibliographical references (p. 409-429).Guglielmo Marconi's trans-Atlantic wireless experiment in 1900 marked the beginning of a communication revolution that transformed the open space above the earth into channels of information flow. This dissertation grapples with the historical conditions that gave rise to such a transformation: the studies of radio-wave propagation and the treatments of radio interferences in early twentieth-century America and Western Europe. The part on propagation examines the debate between the surface diffraction theory and the atmospheric reflection theory for long waves, the development of the ionic refraction theory for short waves, the evidential quests for the existence of the ionosphere, and the studies of the geomagnetic effects on propagation. The part on interferences focuses on the engineering efforts toward the characterization of atmospheric noise and signal-intensity fluctuations, the policies of radio-channel allocation for fighting man-made interference, and the scientific research into electronic tube noise. By the mid-30s, the results from these endeavors had considerably improved the quality of radio communication. Characterizing Radio Channels builds a bridge between the history of science and the history of technology by inspecting an immaterial engineering entity--radio channels--whose control required significant scientific research. In the history of science, it contributes to an integrated study of electrical physics and geophysics. In the history of technology, it enriches radio history, epistemology of engineering knowledge, consumer studies, and the studies of technological policies. Combining both fields with the concept of radio channels enables a new understanding of the historical conditions that made the information society(cont.) social factors that facilitated the modern research organizations in academia, industry, governments and the military.by Chen-Pang Yeang.Ph.D.in History and Social Study of Science and Technology (HAST
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