994 resultados para Channel identification
Resumo:
Quantum channel identification, a standard problem in quantum metrology, is the task of estimating parameter(s) of a quantum channel. We investigate dissonance (quantum discord in the absence of entanglement) as an aid to quantum channel identification and find evidence for dissonance as a resource for quantum information processing. We consider the specific case of dissonant Bell-diagonal probes of the qubit depolarizing channel, using quantum Fisher information as a measure of statistical information extracted by the probe. In this setting dissonant quantum probes yield more statistical information about the depolarizing probability than do corresponding probes without dissonance and greater dissonance yields greater information. This effect only operates consistently when we control for classical correlation between the probe and its ancilla and the joint and marginal purities of the ancilla and probe.
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We explore the task of optimal quantum channel identification and in particular, the estimation of a general one-parameter quantum process. We derive new characterizations of optimality and apply the results to several examples including the qubit depolarizing channel and the harmonic oscillator damping channel. We also discuss the geometry of the problem and illustrate the usefulness of using entanglement in process estimation.
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In numerical linear algebra, students encounter earlythe iterative power method, which finds eigenvectors of a matrixfrom an arbitrary starting point through repeated normalizationand multiplications by the matrix itself. In practice, more sophisticatedmethods are used nowadays, threatening to make the powermethod a historical and pedagogic footnote. However, in the contextof communication over a time-division duplex (TDD) multipleinputmultiple-output (MIMO) channel, the power method takes aspecial position. It can be viewed as an intrinsic part of the uplinkand downlink communication switching, enabling estimationof the eigenmodes of the channel without extra overhead. Generalizingthe method to vector subspaces, communication in thesubspaces with the best receive and transmit signal-to-noise ratio(SNR) is made possible. In exploring this intrinsic subspace convergence(ISC), we show that several published and new schemes canbe cast into a common framework where all members benefit fromthe ISC.
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A deterministic prototype video deghoster is presented which is capable of calculating all the multipath channel distortion characteristics in one single pass and subsequently removing the multipath distortions, commonly termed ghosts. Within the system, a channel identification algorithm finds in isolation all the ghost components while a dedicated DSP filter subsystem is capable of removing ghosts in real time. The results from the system are presented.
Resumo:
In terrestrial television transmission multiple paths of various lengths can occur between the transmitter and the receiver. Such paths occur because of reflections from objects outside the direct transmission path. The multipath signals arriving at the receiver are all detected along with the intended signal causing time displaced replicas called 'ghosts' to appear on the television picture. With an increasing number of people living within built up areas, ghosting is becoming commonplace and therefore deghosting is becoming increasingly important. This thesis uses a deterministic time domain approach to deghosting, resulting in a simple solution to the problem of removing ghosts. A new video detector is presented which reduces the synchronous detector local oscillator phase error, caused by any practical size of ghost, to a lower level than has ever previously been achieved. From the new detector, dispersion of the video signal is minimised and a known closed-form time domain description of the individual ghost components within the detected video is subsequently obtained. Developed from mathematical descriptions of the detected video, a new specific deghoster filter structure is presented which is capable of removing both inphase (I) and also the phase quadrature (Q) induced ghost signals derived from the VSB operation. The new deghoster filter requires much less hardware than any previous deghoster which is capable of removing both I and Q ghost components. A new channel identification algorithm was also required and written which is based upon simple correlation techniques to find the delay and complex amplitude characteristics of individual ghosts. The result of the channel identification is then passed to the new I and Q deghoster filter for ghost cancellation. Generated from the research work performed for this thesis, five papers have been published. D
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Single-carrier (SC) block transmission with frequency-domain equalisation (FDE) offers a viable transmission technology for combating the adverse effects of long dispersive channels encountered in high-rate broadband wireless communication systems. However, for high bandwidthefficiency and high power-efficiency systems, the channel can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. For such nonlinear Hammerstein channels, the standard SC-FDE scheme no longer works. This paper advocates a complex-valued (CV) B-spline neural network based nonlinear SC-FDE scheme for Hammerstein channels. Specifically, We model the nonlinear HPA, which represents the CV static nonlinearity of the Hammerstein channel, by a CV B-spline neural network, and we develop two efficient alternating least squares schemes for estimating the parameters of the Hammerstein channel, including both the channel impulse response coefficients and the parameters of the CV B-spline model. We also use another CV B-spline neural network to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard least squares algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Equalisation of the SC Hammerstein channel can then be accomplished by the usual one-tap linear equalisation in frequency domain as well as the inverse B-spline neural network model obtained in time domain. Extensive simulation results are included to demonstrate the effectiveness of our nonlinear SC-FDE scheme for Hammerstein channels.
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A practical orthogonal frequency-division multiplexing (OFDM) system can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. In this contribution, we advocate a novel nonlinear equalization scheme for OFDM Hammerstein systems. We model the nonlinear HPA, which represents the static nonlinearity of the OFDM Hammerstein channel, by a B-spline neural network, and we develop a highly effective alternating least squares algorithm for estimating the parameters of the OFDM Hammerstein channel, including channel impulse response coefficients and the parameters of the B-spline model. Moreover, we also use another B-spline neural network to model the inversion of the HPA’s nonlinearity, and the parameters of this inverting B-spline model can easily be estimated using the standard least squares algorithm based on the pseudo training data obtained as a byproduct of the Hammerstein channel identification. Equalization of the OFDM Hammerstein channel can then be accomplished by the usual one-tap linear equalization as well as the inverse B-spline neural network model obtained. The effectiveness of our nonlinear equalization scheme for OFDM Hammerstein channels is demonstrated by simulation results.
Resumo:
A practical single-carrier (SC) block transmission with frequency domain equalisation (FDE) system can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. For such Hammerstein channels, the standard SC-FDE scheme no longer works. We propose a novel Bspline neural network based nonlinear SC-FDE scheme for Hammerstein channels. In particular, we model the nonlinear HPA, which represents the complex-valued static nonlinearity of the Hammerstein channel, by two real-valued B-spline neural networks, one for modelling the nonlinear amplitude response of the HPA and the other for the nonlinear phase response of the HPA. We then develop an efficient alternating least squares algorithm for estimating the parameters of the Hammerstein channel, including the channel impulse response coefficients and the parameters of the two B-spline models. Moreover, we also use another real-valued B-spline neural network to model the inversion of the HPA’s nonlinear amplitude response, and the parameters of this inverting B-spline model can be estimated using the standard least squares algorithm based on the pseudo training data obtained as a byproduct of the Hammerstein channel identification. Equalisation of the SC Hammerstein channel can then be accomplished by the usual one-tap linear equalisation in frequency domain as well as the inverse Bspline neural network model obtained in time domain. The effectiveness of our nonlinear SC-FDE scheme for Hammerstein channels is demonstrated in a simulation study.
Resumo:
High bandwidth-efficiency quadrature amplitude modulation (QAM) signaling widely adopted in high-rate communication systems suffers from a drawback of high peak-toaverage power ratio, which may cause the nonlinear saturation of the high power amplifier (HPA) at transmitter. Thus, practical high-throughput QAM communication systems exhibit nonlinear and dispersive channel characteristics that must be modeled as a Hammerstein channel. Standard linear equalization becomes inadequate for such Hammerstein communication systems. In this paper, we advocate an adaptive B-Spline neural network based nonlinear equalizer. Specifically, during the training phase, an efficient alternating least squares (LS) scheme is employed to estimate the parameters of the Hammerstein channel, including both the channel impulse response (CIR) coefficients and the parameters of the B-spline neural network that models the HPA’s nonlinearity. In addition, another B-spline neural network is used to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard LS algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Nonlinear equalisation of the Hammerstein channel is then accomplished by the linear equalization based on the estimated CIR as well as the inverse B-spline neural network model. Furthermore, during the data communication phase, the decision-directed LS channel estimation is adopted to track the time-varying CIR. Extensive simulation results demonstrate the effectiveness of our proposed B-Spline neural network based nonlinear equalization scheme.
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Fast synaptic neurotransmission is mediated by transmitter-activated conformational changes in ligand-gated ion channel receptors, culminating in opening of the integral ion channel pore. Human hereditary hyperekplexia, or startle disease, is caused by mutations in both the intracellular or extracellular loops flanking the pore-lining M2 domain of the glycine receptor alpha 1 subunit. These flanking domains are designated the M1-M2 loop and the M2-M3 loop respectively. We show that four startle disease mutations and six additional alanine substitution mutations distributed throughout both loops result in uncoupling of the ligand binding sites from the channel activation gate. We therefore conclude that the M1-M2 and M2-M3 loops act in parallel to activate the channel. Their locations strongly suggest that they act as hinges governing allosteric control of the M2 domain. As the members of the ligand-gated ion channel superfamily share a common structure, this signal transduction model may apply to all members of this superfamily.
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One of the characteristic features of the structure of the epithelial sodium channel family (ENaC) is the presence of two highly conserved cysteine-rich domains (CRD1 and CRD2) in the large extracellular loops of the proteins. We have studied the role of CRDs in the functional expression of rat alphabetagamma ENaC subunits by systematically mutating cysteine residues (singly or in combinations) into either serine or alanine. In the Xenopus oocyte expression system, mutations of two cysteines in CRD1 of alpha, beta, or gamma ENaC subunits led to a temperature-dependent inactivation of the channel. In CRD1, one of the cysteines of the rat alphaENaC subunit (Cys158) is homologous to Cys133 of the corresponding human subunit causing, when mutated to tyrosine (C133Y), pseudohypoaldosteronism type 1, a severe salt-loosing syndrome in neonates. In CRD2, mutation of two cysteines in alpha and beta but not in the gamma subunit also produced a temperature-dependent inactivation of the channel. The main features of the mutant cysteine channels are: (i) a decrease in cell surface expression of channel molecules that parallels the decrease in channel activity and (ii) a normal assembly or rate of degradation as assessed by nondenaturing co-immunoprecipitation of [35S]methionine-labeled channel protein. These data indicate that the two cysteines in CRD1 and CRD2 are not a prerequisite for subunit assembly and/or intrinsic channel activity. We propose that they play an essential role in the efficient transport of assembled channels to the plasma membrane.
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The amiloride-sensitive epithelial Na channel (ENaC) is a heteromultimeric channel made of three alpha beta gamma subunits. The structures involved in the ion permeation pathway have only been partially identified, and the respective contributions of each subunit in the formation of the conduction pore has not yet been established. Using a site-directed mutagenesis approach, we have identified in a short segment preceding the second membrane-spanning domain (the pre-M2 segment) amino acid residues involved in ion permeation and critical for channel block by amiloride. Cys substitutions of Gly residues in beta and gamma subunits at position beta G525 and gamma G537 increased the apparent inhibitory constant (Ki) for amiloride by > 1,000-fold and decreased channel unitary current without affecting ion selectivity. The corresponding mutation S583 to C in the alpha subunit increased amiloride Ki by 20-fold, without changing channel conducting properties. Coexpression of these mutated alpha beta gamma subunits resulted in a non-conducting channel expressed at the cell surface. Finally, these Cys substitutions increased channel affinity for block by external Zn2+ ions, in particular the alpha S583C mutant showing a Ki for Zn2+ of 29 microM. Mutations of residues alpha W582L, or beta G522D also increased amiloride Ki, the later mutation generating a Ca2+ blocking site located 15% within the membrane electric field. These experiments provide strong evidence that alpha beta gamma ENaCs are pore-forming subunits involved in ion permeation through the channel. The pre-M2 segment of alpha beta gamma subunits may form a pore loop structure at the extracellular face of the channel, where amiloride binds within the channel lumen. We propose that amiloride interacts with Na+ ions at an external Na+ binding site preventing ion permeation through the channel pore.
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The design of therapeutic compounds targeting transthyretin (TTR) is challenging due to the low specificity of interaction in the hormone binding site. Such feature is highlighted by the interactions of TTR with diclofenac, a compound with high affinity for TTR, in two dissimilar modes, as evidenced by crystal structure of the complex. We report here structural analysis of the interactions of TTR with two small molecules, 1-amino-5-naphthalene sulfonate (1,5-AmNS) and 1-anilino-8-naphthalene sulfonate (1,8-ANS). Crystal structure of TTR: 1,8-ANS complex reveals a peculiar interaction, through the stacking of the naphthalene ring between the side-chain of Lys15 and Leu17. The sulfonate moiety provides additional interaction with Lys15` and a water-mediated hydrogen bond with Thr119`. The uniqueness of this mode of ligand recognition is corroborated by the crystal structure of TTR in complex with the weak analogue 1,5-AmNS, the binding of which is driven mainly by hydrophobic partition and one electrostatic interaction between the sulfonate group and the Lys15. The ligand binding motif unraveled by 1,8-ANS may open new possibilities to treat TTR amyloid diseases by the elucidation of novel candidates for a more specific pharmacophoric pattern. (C) 2009 Published by Elsevier Ltd.
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Short QT syndrome (SQTS) is a genetically determined ion-channel disorder, which may cause malignant tachyarrhythmias and sudden cardiac death. Thus far, mutations in five different genes encoding potassium and calcium channel subunits have been reported. We present, for the first time, a novel loss-of-function mutation coding for an L-type calcium channel subunit.