7,766 research outputs found

    Distributed Resource Allocation Assisted by Intercell Interference Mitigation in Downlink Multicell MC DS-CDMA Systems

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    This paper investigates the allocation of resources, including subcarriers and spreading codes, as well as intercell interference (ICI) mitigation for multicell downlink multicarrier direct-sequence code division multiple-access systems, which aim to maximize the system's spectral efficiency (SE). The analytical benchmark scheme for resource allocation and ICI mitigation is derived by solving or closely solving a series of mixed integer non-convex optimization problems. Based on the optimization objectives the same as the benchmark scheme, we propose a novel distributed resource allocation assisted by ICI mitigation scheme referred to as resource allocation assisted by ICI mitigation (RAIM), which requires very low implementation complexity and demands little backhaul resource. Our RAIM algorithm is a fully distributed algorithm, which consists of the subcarrier allocation (SA) algorithm named RAIM-SA, spreading code allocation (CA) algorithm called RAIM-CA and the ICI mitigation algorithm termed RAIM-IM. The advantages of the RAIM are that its CA only requires limited binary ICI information of intracell channels, and it is able to make mitigation decisions without any knowledge of ICI information. Our simulation results show that the proposed RAIM scheme, with very low complexity required, achieves significantly better SE performance than other existing schemes, and its performance is very close to that obtained by the benchmark scheme

    Performance Bounds for Finite Moving Average Change Detection: Application to Global Navigation Satellite Systems

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    Due to the widespread deployment of Global Navigation Satellite Systems (GNSSs) for critical road or urban applications, one of the major challenges to be solved is the provision of integrity to terrestrial environments, so that GNSS may be safety used in these applications. To do so, the integrity of the received GNSS signal must be analyzed in order to detect some local effect disturbing the received signal. This is desirable because the presence of some local effect may cause large position errors, and hence compromise the signal integrity. Moreover, the detection of such disturbing effects must be done before some pre-established delay. This kind of detection lies within the field of transient change detection. In this work, a finite moving average stopping time is proposed in order to approach the signal integrity problem with a transient change detection framework. The statistical performance of this stopping time is investigated and compared, in the context of multipath detection, to other different methods available in the literature. Numerical results are presented in order to assess their performance.Comment: 12 pages, 2 figures, transaction paper, IEEE Transaction on Signal Processing, 201

    Safety arguments for next generation location aware computing

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    Concerns over the accuracy, availability, integrity and continuity of Global Navigation Satellite Systems (GNSS) have limited the integration of GPS and GLONASS for safety-critical applications. More recent augmentation systems, such as the European Geostationary Navigation Overlay Service (EGNOS) and the North American Wide Area Augmentation System (WAAS) have begun to address these concerns. Augmentation architectures build on the existing GPS/GLONASS infrastructures to support locationbased services in Safety of Life (SoL) applications. Much of the technical development has been directed by air traffic management requirements, in anticipation of the more extensive support to be offered by GPS III and Galileo. WAAS has already been approved to provide vertical guidance against ICAO safety performance criteria for aviation applications. During the next twelve months, we will see the full certification of EGNOS for SoL applications. This paper identifies strong similarities between the safety assessment techniques used in Europe and North America. Both have relied on hazard analysis techniques to derive estimates of the Probability of Hazardously Misleading Information (PHMI). Later sections identify significant differences between the approaches adopted in application development. Integrated fault trees have been developed by regulatory and commercial organisations to consider both infrastructure hazards and their impact on non-precision RNAV/VNAV approaches using WAAS. In contrast, EUROCONTROL and the European Space Agency have developed a more modular approach to safety-case development for EGNOS. It remains to be seen whether the European or North American strategy offers the greatest support as satellite based augmentation systems are used within a growing range of SoL applications from railway signalling through to Unmanned Airborne Systems. The key contribution of this paper is to focus attention on the safety arguments that might support this wider class of location based services

    Distributed Resource Allocation Assisted by Intercell Interference Mitigation in Downlink Multicell MC DS-CDMA Systems

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    This paper investigates the allocation of resources, including subcarriers and spreading codes, as well as intercell interference (ICI) mitigation for multicell downlink multicarrier direct-sequence code division multiple-access systems, which aim to maximize the system's spectral efficiency (SE). The analytical benchmark scheme for resource allocation and ICI mitigation is derived by solving or closely solving a series of mixed integer non-convex optimization problems. Based on the optimization objectives the same as the benchmark scheme, we propose a novel distributed resource allocation assisted by ICI mitigation scheme referred to as resource allocation assisted by ICI mitigation (RAIM), which requires very low implementation complexity and demands little backhaul resource. Our RAIM algorithm is a fully distributed algorithm, which consists of the subcarrier allocation (SA) algorithm named RAIM-SA, spreading code allocation (CA) algorithm called RAIM-CA and the ICI mitigation algorithm termed RAIM-IM. The advantages of the RAIM are that its CA only requires limited binary ICI information of intracell channels, and it is able to make mitigation decisions without any knowledge of ICI information. Our simulation results show that the proposed RAIM scheme, with very low complexity required, achieves significantly better SE performance than other existing schemes, and its performance is very close to that obtained by the benchmark scheme

    Galileo: the added value for integrity in harsh environments

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    A global navigation satellite system (GNSS)-based navigation is a challenging task in a signal-degraded environments where GNSS signals are distorted by multipath and attenuated by fading effects: the navigation solution may be inaccurate or unavailable. A possible approach to improve accuracy and availability is the joint use of measurements from different GNSSs and quality check algorithms; this approach is investigated here using live GPS and Galileo signals. A modified receiver autonomous integrity monitoring (RAIM) algorithm, including geometry and separability checks, is proposed to detect and exclude erroneous measurements: the multi-constellation approach provides redundant measurements, and RAIM exploits them to exclude distorted observations. The synergy between combined GPS/Galileo navigation and RAIM is analyzed using live data; the performance is compared to the accuracy and availability of a GPS-only solution. The tests performed demonstrate that the methods developed are effective techniques for GNSS-based navigation in signal-degraded environments. The joint use of the multi-constellation approach and of modified RAIM algorithms improves the performance of the navigation system in terms of both accuracy and availability.JRC.G.5-Security technology assessmen

    An Extension of Generalized Linear Models to Finite Mixture Outcome Distributions

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    Finite mixture distributions arise in sampling a heterogeneous population. Data drawn from such a population will exhibit extra variability relative to any single subpopulation. Statistical models based on finite mixtures can assist in the analysis of categorical and count outcomes when standard generalized linear models (GLMs) cannot adequately account for variability observed in the data. We propose an extension of GLM where the response is assumed to follow a finite mixture distribution, while the regression of interest is linked to the mixture's mean. This approach may be preferred over a finite mixture of regressions when the population mean is the quantity of interest; here, only a single regression function must be specified and interpreted in the analysis. A technical challenge is that the mean of a finite mixture is a composite parameter which does not appear explicitly in the density. The proposed model is completely likelihood-based and maintains the link to the regression through a certain random effects structure. We consider typical GLM cases where means are either real-valued, constrained to be positive, or constrained to be on the unit interval. The resulting model is applied to two example datasets through a Bayesian analysis: one with success/failure outcomes and one with count outcomes. Supporting the extra variation is seen to improve residual plots and to appropriately widen prediction intervals

    Encoding AIS Binary Messages in XML Format for Providing Hydrographic-related Information

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    A specification is proposed to enable hydrographic and maritime safety agencies to encode AIS messages using Extensible Markup Language (XML). It specifies the order, length, and type of fields contained in ITU-R.M.1371-1. A XML schema validates the message definitions, and a XSLT style sheet produces reference documentation in \u27html\u27 format. AIS binary messages in XML are an effective means to communicate dynamic and real-time port/waterway information. For example, tidal information can be continuously broadcast to maritime users and applied to a tide-aware ENC. The XML format aligns with the type of data encapsulation planned for the IHO Geospatial Standard for Digital Hydrographic Data (S-100)

    Fault detection and isolation for multisensor navigation systems

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    Increasing attention is being given to the problem of erroneous measurement data for multisensor navigation systems. A recursive estimator can be used in conjunction with a 'snapshot' batch estimator to provide fault detection and isolation (FDI) for these systems. A recursive estimator uses past system states to form a new state estimate and compares it to the calculated state based on a new set of measurements. A 'snapshot' batch estimator uses a set of measurements collected simultaneously and compares solutions based on subsets of measurements. The 'snapshot' approach requires redundant measurements in order to detect and isolate faults. FDI is also referred to as Receiver Autonomous Integrity Monitoring (RAIM)

    Modeling Selective Availability of the NAVSTAR Global Positioning System

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    As the development of the NAVSTAR Global Positioning System (GPS) continues, there will increasingly be the need for a software centered signal model. This model must accurately generate the observed pseudorange which would typically be encountered. The observed pseudorange varies from the true geometric (slant) range due to range measurement errors. Errors in range measurement stem from a variety of hardware and environment factors. These errors are classified as either deterministic or random and, where appropriate, their models are summarized. Of particular interest is the model for Selective Availability which is derived from actual GPS data. The procedure for the determination of this model, known as the System Identification Theory, is briefly outlined. The synthesis of these error sources into the final signal model is given along with simulation results
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