773 resultados para Data transmission systems.


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The optical regeneration is an attractive method to improve the performance of long-distance data transmission, though its application in high-speed fiber systems requires careful design consideration/optimization. In this letter we investigate 40 Gbit/s dispersion-managed fiber transmission with optical 2R regeneration based on quantum well saturable absorber and highly non-linear fiber. We demonstrate through numerical modeling a feasibility of a single channel transmission over 10,000 km using optimized system design. © 2003 Elsevier B.V. All rights reserved.

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Long-haul high speed optical transmission systems are significantly distorted by the interplay between the electronic chromatic dispersion (CD) equalization and the local oscillator (LO) laser phase noise, which leads to an effect of equalization enhanced phase noise (EEPN). The EEPN degrades the performance of optical communication systems severely with the increment of fiber dispersion, LO laser linewidth, symbol rate, and modulation format. In this paper, we present an analytical model for evaluating the performance of bit-error-rate (BER) versus signal-to-noise ratio (SNR) in the n-level phase shift keying (n-PSK) coherent transmission system employing differential carrier phase estimation (CPE), where the influence of EEPN is considered. Theoretical results based on this model have been investigated for the differential quadrature phase shift keying (DQPSK), the differential 8-PSK (D8PSK), and the differential 16-PSK (D16PSK) coherent transmission systems. The influence of EEPN on the BER performance in term of the fiber dispersion, the LO phase noise, the symbol rate, and the modulation format are analyzed in detail. The BER behaviors based on this analytical model achieve a good agreement with previously reported BER floors influenced by EEPN. Further simulations have also been carried out in the differential CPE considering EEPN. The results indicate that this analytical model can give an accurate prediction for the DQPSK system, and a leading-order approximation for the D8PSK and the D16PSK systems.

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Every high resolution imaging system suffers from the bottleneck problem. This problem relates to the huge amount of data transmission from the sensor array to a digital signal processing (DSP) and to bottleneck in performance, caused by the requirement to process a large amount of information in parallel. The same problem exists in biological vision systems, where the information, sensed by many millions of receptors should be transmitted and processed in real time. Models, describing the bottleneck problem solutions in biological systems fall in the field of visual attention. This paper presents the bottleneck problem existing in imagers used for real time salient target tracking and proposes a simple solution by employing models of attention, found in biological systems. The bottleneck problem in imaging systems is presented, the existing models of visual attention are discussed and the architecture of the proposed imager is shown.

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This letter proposes the introduction of discrete modal crosstalk (XT) through fiber splices for the improvement of the distance reach (DR) of mode division multiplexed (MDM) transmission systems over few mode fibers (FMFs). The proposed method increases the DR, reducing the time spread of the FMFs' impulse response. The effectiveness of this method is assessed through simulation considering 3 × 136-Gbit/s MDM-coherently-detected polarization-multiplexed quadrature-phase-shift-keying ultralong haul transmission systems employing inherently low differential mode delay (DMD) FMFs or DMD compensated FMFs. A maximum DR increase factor of 1.9 is obtained for the optimum number of splices per span and optimum splice XT level. © 1989-2012 IEEE.

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IEEE 802.15.4 networks has the features of low data rate and low power consumption. It is a strong candidate technique for wireless sensor networks and can find many applications to smart grid. However, due to the low network and energy capacities it is critical to maximize the bandwidth and energy efficiencies of 802.15.4 networks. In this paper we propose an adaptive data transmission scheme with CSMA/CA access control, for applications which may have heavy traffic loads such as smart grids. The adaptive access control is simple to implement. Its compatibility with legacy 802.15.4 devices can be maintained. Simulation results demonstrate the effectiveness of the proposed scheme with largely improved bandwidth and power efficiency. © 2013 International Information Institute.

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We experimentally demonstrate performance enhancements enabled by weighted digital back propagation method for 28 Gbaud PM-16QAM transmission systems, over a 250 km ultra-large area fibre, using only one back-propagation step for the entire link, enabling up to 3 dB improvement in power tolerance with respect to linear compensation only. We observe that this is roughly the same improvement that can be obtained with the conventional, computationally heavy, non-weighted digital back propagation compensation with one step per span. As a further benchmark, we analyze performance improvement as a function of number of steps, and show that the performance improvement saturates at approximately 20 steps per span, at which a 5 dB improvement in power tolerance is obtained with respect to linear compensation only. Furthermore, we show that coarse-step self-phase modulation compensation is inefficient in wavelength division multiplexed transmission.

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We extend the theory of parametric noise amplification to the case of transmission systems employing multiple optical phase conjugators, demonstrating that the excess noise due to this process may be reduced in direct proportion to the number of phase conjugation devices employed. We further identify that the optimum noise suppression is achieved for an odd number of phase conjugators, and that the noise may be further suppressed by up to 3dB by partial digital back propagation (or fractional spans at the ends of the links).

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The results of numerical modelling of nonlinear propagation of an optical signal in multimode fibres with a small differential group delay are presented. It is found that the dependence of the error vector magnitude (EVM) on the differential group delay can be reduced by increasing the number of ADC samples per symbol in the numerical implementation of the differential group delay compensation algorithm in the receiver. The possibility of using multimode fibres with a small differential group delay for data transmission in modern digital communication systems is demonstrated. It is shown that with increasing number of modes the strong coupling regime provides a lower EVM level than the weak coupling one.

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For intelligent DC distributed power systems, data communication plays a vital role in system control and device monitoring. To achieve communication in a cost effective way, power/signal dual modulation (PSDM), a method that integrates data transmission with power conversion, can be utilized. In this paper, an improved PSDM method using phase shift full bridge (PSFB) converter is proposed. This method introduces a phase control based freedom in the conventional PSFB control loop to realize communication using the same power conversion circuit. In this way, decoupled data modulation and power conversion are realized without extra wiring and coupling units, and thus the system structure is simplified. More importantly, the signal intensity can be regulated by the proposed perturbation depth, and so this method can adapt to different operating conditions. Application of the proposed method to a DC distributed power system composed of several PSFB converters is discussed. A 2kW prototype system with an embedded 5kbps communication link has been implemented, and the effectiveness of the method is verified by experimental results.

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The current mobile networks don't offer sufficient data rates to support multimedia intensive applications in development for multifunctional mobile devices. Ultra wideband (UWB) wireless technology is being considered as the solution to overcome data rate bottlenecks in the current mobile networks. UWB is able to achieve such high data transmission rates because it transmits data over a very large chunk of the frequency spectrum. As currently approved by the U.S. Federal Communication Commission it utilizes 7.5 GHz of spectrum between 3.1 GHz and 10.6 GHz. ^ Successful transmission and reception of information data using UWB wireless technology in mobile devices, requires an antenna that has linear phase, low dispersion and a voltage standing wave ratio (VSWR) ≤ 2 throughout the entire frequency band. Compatibility with an integrated circuit requires an unobtrusive and electrically small design. The previous techniques that have been used to optimize the performance of UWB wireless systems, involve proper design of source pulses for optimal UWB performance. The goal of this work is directed towards the designing of antennas for personal communication devices, with optimal UWB bandwidth performance. Several techniques are proposed for optimal UWB bandwidth performance of the UWB antenna designs in this Ph.D. dissertation. ^ This Ph.D. dissertation presents novel UWB antenna designs for personal communication devices that have been characterized and optimized using the finite difference time domain (FDTD) technique. The antenna designs reported in this research are physically compact, planar for low profile use, with sufficient impedance bandwidth (>20%), antenna input impedance of 50-Ω, and an omni-directional (±1.5 dB) radiation pattern in the operating bandwidth. ^

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This work is the first work using patterned soft underlayers in multilevel three-dimensional vertical magnetic data storage systems. The motivation stems from an exponentially growing information stockpile, and a corresponding need for more efficient storage devices with higher density. The world information stockpile currently exceeds 150EB (ExaByte=1x1018Bytes); most of which is in analog form. Among the storage technologies (semiconductor, optical and magnetic), magnetic hard disk drives are posed to occupy a big role in personal, network as well as corporate storage. However; this mode suffers from a limit known as the Superparamagnetic limit; which limits achievable areal density due to fundamental quantum mechanical stability requirements. There are many viable techniques considered to defer superparamagnetism into the 100's of Gbit/in2 such as: patterned media, Heat-Assisted Magnetic Recording (HAMR), Self Organized Magnetic Arrays (SOMA), antiferromagnetically coupled structures (AFC), and perpendicular magnetic recording. Nonetheless, these techniques utilize a single magnetic layer; and can thusly be viewed as two-dimensional in nature. In this work a novel three-dimensional vertical magnetic recording approach is proposed. This approach utilizes the entire thickness of a magnetic multilayer structure to store information; with potential areal density well into the Tbit/in2 regime. ^ There are several possible implementations for 3D magnetic recording; each presenting its own set of requirements, merits and challenges. The issues and considerations pertaining to the development of such systems will be examined, and analyzed using empirical and numerical analysis techniques. Two novel key approaches are proposed and developed: (1) Patterned soft underlayer (SUL) which allows for enhanced recording of thicker media, (2) A combinatorial approach for 3D media development that facilitates concurrent investigation of various film parameters on a predefined performance metric. A case study is presented using combinatorial overcoats of Tantalum and Zirconium Oxides for corrosion protection in magnetic media. ^ Feasibility of 3D recording is demonstrated, and an emphasis on 3D media development is emphasized as a key prerequisite. Patterned SUL shows significant enhancement over conventional "un-patterned" SUL, and shows that geometry can be used as a design tool to achieve favorable field distribution where magnetic storage and magnetic phenomena are involved. ^

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The tragic events of September 11th ushered a new era of unprecedented challenges. Our nation has to be protected from the alarming threats of adversaries. These threats exploit the nation's critical infrastructures affecting all sectors of the economy. There is the need for pervasive monitoring and decentralized control of the nation's critical infrastructures. The communications needs of monitoring and control of critical infrastructures was traditionally catered for by wired communication systems. These technologies ensured high reliability and bandwidth but are however very expensive, inflexible and do not support mobility and pervasive monitoring. The communication protocols are Ethernet-based that used contention access protocols which results in high unsuccessful transmission and delay. An emerging class of wireless networks, named embedded wireless sensor and actuator networks has potential benefits for real-time monitoring and control of critical infrastructures. The use of embedded wireless networks for monitoring and control of critical infrastructures requires secure, reliable and timely exchange of information among controllers, distributed sensors and actuators. The exchange of information is over shared wireless media. However, wireless media is highly unpredictable due to path loss, shadow fading and ambient noise. Monitoring and control applications have stringent requirements on reliability, delay and security. The primary issue addressed in this dissertation is the impact of wireless media in harsh industrial environment on the reliable and timely delivery of critical data. In the first part of the dissertation, a combined networking and information theoretic approach was adopted to determine the transmit power required to maintain a minimum wireless channel capacity for reliable data transmission. The second part described a channel-aware scheduling scheme that ensured efficient utilization of the wireless link and guaranteed delay. Various analytical evaluations and simulations are used to evaluate and validate the feasibility of the methodologies and demonstrate that the protocols achieved reliable and real-time data delivery in wireless industrial networks.

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With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

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With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

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The performance of algorithms for fault location i n transmission lines is directly related to the accuracy of its input data. Thus, fa ctors such as errors in the line parameters, failures in synchronization of oscillographic recor ds and errors in measurements of voltage and current can significantly influence the accurac y of algorithms that use bad data to indicate the fault location. This work presents a new method ology for fault location in transmission lines based on the theory of state estimation in or der to determine the location of faults more accurately by considering realistic systematic erro rs that may be present in measurements of voltage and current. The methodology was implemente d in two stages: pre-fault and post- fault. In the first step, assuming non-synchronized data, the synchronization angle and positive sequence line parameters are estimated, an d in the second, the fault distance is estimated. Besides calculating the most likely faul t distance obtained from measurement errors, the variance associated with the distance f ound is also determined, using the errors theory. This is one of the main contributions of th is work, since, with the proposed algorithm, it is possible to determine a most likely zone of f ault incidence, with approximately 95,45% of confidence. Tests for evaluation and validation of the proposed algorithm were realized from actual records of faults and from simulations of fictitious transmission systems using ATP software. The obtained results are relevant to show that the proposed estimation approach works even adopting realistic variances, c ompatible with real equipments errors.