266 resultados para Gaussian channel
Resumo:
Based on a comprehensive theoretical optical orthogonal frequency division multiplexing (OOFDM) system model rigorously verified by comparing numerical results with end-to-end real-time experimental measurements at 11.25Gb/s, detailed explorations are undertaken, for the first time, of the impacts of various physical factors on the OOFDM system performance over directly modulated DFB laser (DML)-based, intensity modulation and direct detection (IMDD), single-mode fibre (SMF) systems without in-line optical amplification and chromatic dispersion compensation. It is shown that the low extinction ratio (ER) of the DML modulated OOFDM signal is the predominant factor limiting the maximum achievable optical power budget, and the subcarrier intermixing effect associated with square-law photon detection in the receiver reduces the optical power budget by at least 1dB. Results also indicate that, immediately after the DML in the transmitter, the insertion of a 0.02nm bandwidth optical Gaussian bandpass filter with a 0.01nm wavelength offset with respect to the optical carrier wavelength can enhance the OOFDM signal ER by approximately 1.24dB, thus resulting in a 7dB optical power budget improvement at a total channel BER of 1 × 10(-3).
Resumo:
An experimental and numerical investigation into transonic shock/boundary-layer interactions in rectangular ducts has been performed. Experiments have shown that flow development in the corners of transonic shock/boundary-layer interactions in confined channels can have a significant impact on the entire flowfield. As shock strength is increased from M∞ = 1:3 to 1.5, the flowfield becomes very slightly asymmetrical. The interaction of corner flows with one another is thought to be a potential cause of this asymmetry. Thus, factors that govern the size of corner interactions (such as interaction strength) and their proximity to one another (such as tunnel aspect ratio) can affect flow symmetry. The results of the computational study show reasonable agreement with experiments, although simulations with particular turbulence models predict highly asymmetrical solutions for flows that were predominantly symmetrical in experiments. These discrepancies are attributed to the tendency of numerical schemes to overprediction corner-interaction size, and this also accounts for why computational fluid dynamics predicts the onset of asymmetry at lower shock strengths than in experiments. The findings of this study highlight the importance of making informed decisions about imposing artificial constraints on symmetry and boundary conditions for internal transonic flows. Future effort into modeling corner flows accurately is required. Copyright © 2011 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
Resumo:
To support the development and analysis of engineering designs at the embodiment stage, designers work iteratively with representations of those designs as they consider the function and form of their constituent parts. Detailed descriptions of "what a machine does" usually include flows of forces and active principles within the technical system, and their localization within parts and across the interfaces between them. This means that a representation should assist a designer in considering form and function at the same time and at different levels of abstraction. This paper describes a design modelling approach that enables designers to break down a system architecture into its subsystems and parts, while assigning functions and flows to parts and the interfaces between them. In turn, this may reveal further requirements to fulfil functions in order to complete the design. The approach is implemented in a software tool which provides a uniform, computable language allowing the user to describe functions and flows as they are iteratively discovered, created and embodied. A database of parts allows the user to search for existing design solutions. The approach is illustrated through an example: modelling the complex mechanisms within a humanoid robot. Copyright © 2010 by ASME.
Resumo:
Fading channels, which are used as a model for wireless communication, are often analyzed by assuming that the receiver is aware of the realization of the channel. This is commonly justified by saying that the channel varies typically slowly with time, and the receiver is thus able to estimate it. However, this assumption is optimistic, since it is prima facie not clear whether the channel can be estimated perfectly. This paper investigates the quality of this assumption by means of the channel capacity. In particular, results on the channel capacity of fading channels are presented, both when the receiver is aware of the realization of the channel and when it is aware only of its statistics. A comparison of these results demonstrates that information- theoretic analyses of fading channels that are based on the assumption that the receiver is aware of the channel's realization can yield helpful insights, but have to be taken with a pinch of salt. ©2009 IEEE.
Resumo:
This paper studies on-chip communication with non-ideal heat sinks. A channel model is proposed where the variance of the additive noise depends on the weighted sum of the past channel input powers. It is shown that, depending on the weights, the capacity can be either bounded or unbounded in the input power. A necessary condition and a sufficient condition for the capacity to be bounded are presented. © 2007 IEEE.
Resumo:
We report selective tunnelling through a nanographene intermolecular tunnel junction achieved via scanning tunnelling microscope tip functionalization with hexa-peri-hexabenzocoronene (HBC) molecules. This leads to an offset in the alignment between the energy levels of the tip and the molecular assembly, resulting in the imaging of a variety of distinct charge density patterns in the HBC assembly, not attainable using a bare metallic tip. Different tunnelling channels can be selected by the application of an electric field in the tunnelling junction, which changes the condition of the HBC on the tip. Density functional theory-based calculations relate the imaged HBC patterns to the calculated molecular orbitals at certain energy levels. These patterns bear a close resemblance to the π-orbital states of the HBC molecule calculated at the relevant energy levels, mainly below the Fermi energy of HBC. This correlation demonstrates the ability of an HBC functionalized tip as regards accessing an energy range that is restricted to the usual operating bias range around the Fermi energy with a normal metallic tip at room temperature. Apart from relating to molecular orbitals, some patterns could also be described in association with the Clar aromatic sextet formula. Our observations may help pave the way towards the possibility of controlling charge transport between organic interfaces.
Resumo:
This paper studies a noncoherent multiple-input multiple-output (MIMO) fading multiple-access channel (MAC). The rate region that is achievable with nearest neighbour decoding and pilot-assisted channel estimation is analysed and the corresponding pre-log region, defined as the limiting ratio of the rate region to the logarithm of the signal-to-noise ratio (SNR) as the SNR tends to infinity, is determined. © 2011 IEEE.
Resumo:
Modelling dialogue as a Partially Observable Markov Decision Process (POMDP) enables a dialogue policy robust to speech understanding errors to be learnt. However, a major challenge in POMDP policy learning is to maintain tractability, so the use of approximation is inevitable. We propose applying Gaussian Processes in Reinforcement learning of optimal POMDP dialogue policies, in order (1) to make the learning process faster and (2) to obtain an estimate of the uncertainty of the approximation. We first demonstrate the idea on a simple voice mail dialogue task and then apply this method to a real-world tourist information dialogue task. © 2010 Association for Computational Linguistics.
Resumo:
We present the Gaussian Process Density Sampler (GPDS), an exchangeable generative model for use in nonparametric Bayesian density estimation. Samples drawn from the GPDS are consistent with exact, independent samples from a fixed density function that is a transformation of a function drawn from a Gaussian process prior. Our formulation allows us to infer an unknown density from data using Markov chain Monte Carlo, which gives samples from the posterior distribution over density functions and from the predictive distribution on data space. We can also infer the hyperparameters of the Gaussian process. We compare this density modeling technique to several existing techniques on a toy problem and a skullreconstruction task.