190 research outputs found
Orthogonal Multiple Access with Correlated Sources: Feasible Region and Pragmatic Schemes
In this paper, we consider orthogonal multiple access coding schemes, where
correlated sources are encoded in a distributed fashion and transmitted,
through additive white Gaussian noise (AWGN) channels, to an access point (AP).
At the AP, component decoders, associated with the source encoders, iteratively
exchange soft information by taking into account the source correlation. The
first goal of this paper is to investigate the ultimate achievable performance
limits in terms of a multi-dimensional feasible region in the space of channel
parameters, deriving insights on the impact of the number of sources. The
second goal is the design of pragmatic schemes, where the sources use
"off-the-shelf" channel codes. In order to analyze the performance of given
coding schemes, we propose an extrinsic information transfer (EXIT)-based
approach, which allows to determine the corresponding multi-dimensional
feasible regions. On the basis of the proposed analytical framework, the
performance of pragmatic coded schemes, based on serially concatenated
convolutional codes (SCCCs), is discussed
Linear predictive receivers for phase-uncertain channels
In this paper, we propose linear predictive receivers for phaseuncertain channels. These receivers are attractive from a conceptual viewpoint because they generalize previous solutions based on noncoherent sequence detection. On the practical side, the proposed algorithms lend themselves to the implementation of adaptive receivers capable of copying with possible time variations of the statistics of the underlying phase model. 1
Adaptive Iterative Detection for the Phase-Uncertain Channel: Limited-Tree-Search Versus Truncated-Memory Detection
Detection of linear modulations in the presence of strong phase and frequency instabilities
Bringing ICT into newborn monitoring: A video-based approach
In both clinical and domestic environments, newborns deserve continuous attention from the medical personnel or the caring parents. In a Neonatal Intensive Care Unit (NICU), neonates affected by perinatal diseases are at risk of neonatal seizures, which are the most common sign of acute neurological dysfunctions and must be promptly and accurately recognized in order to establish timely treatments. In a domestic scenario, respiration disorders and the possible occurrence of apnoea episodes may be related with a potential risk of Sudden Infant Death Syndrome (SIDS) and should be immediately reported to a pediatrician. All these potential events may occur unexpectedly and with low rate, causing a non negligible risk of letting their initial occurrence go unnoticed with possible detriment to the health of the newborn. Continuous wide-scale newborn monitoring by caring personnel is of course unfeasible, even if we restrict our interest to a subset of the population which may exhibit a higher risk of disorders. As a consequence, there has been interest in devising automatic real-time low-cost systems, based on Information and Communication Technology (ICT), capable of continuously monitoring a newborn and prompting the attention of the caring personnel in a timely and reliable manner. Among various options, one that appears particularly convenient and appealing, both from the scientific and application viewpoints, is the use of one or multiple video cameras positioned around the cradle and framing the newborn, equipped with proper signal processing algorithms designed to detect the occurrence of possible disorders and alert the caring personnel. This tutorial will provide an overview of video signal processing methods for newborn monitoring which have been the subject of research and experimentation in recent years. As a specific case study, we focus on monitoring infants potentially at risk of diseases characterized by the presence or absence of rhythmic movements of one or more body parts, such as the limbs, the chest or the abdomen. In fact, a specific category of neonatal seizures, named “clonic”, are characterized by repetitive movement patterns of some body parts, whose possible presence can be detected automatically by a video processing system. Likewise, respiration monitoring can be considered in which possible apnoeas can be detected by the temporary absence of repetitive movement patterns. After introducing the subject and providing an overview of earlier work, we shall present the principles underlying the extraction of relevant information content from video signals. We shall then present specific video-based solutions to newborn monitoring, their performance and the results of initial experiments in a real NICU environment. Finally, we shall discuss potential applications of these methods to respiration monitoring in a domestic environment employing low-cost devices, such as smartphones or tablets
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