7,973 research outputs found
Waveform Design for 5G and Beyond
5G is envisioned to improve major key performance indicators (KPIs), such as
peak data rate, spectral efficiency, power consumption, complexity, connection
density, latency, and mobility. This chapter aims to provide a complete picture
of the ongoing 5G waveform discussions and overviews the major candidates. It
provides a brief description of the waveform and reveals the 5G use cases and
waveform design requirements. The chapter presents the main features of cyclic
prefix-orthogonal frequency-division multiplexing (CP-OFDM) that is deployed in
4G LTE systems. CP-OFDM is the baseline of the 5G waveform discussions since
the performance of a new waveform is usually compared with it. The chapter
examines the essential characteristics of the major waveform candidates along
with the related advantages and disadvantages. It summarizes and compares the
key features of different waveforms.Comment: 22 pages, 21 figures, 2 tables; accepted version (The URL for the
final version:
https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119333142.ch2
Why Noise and Dispersion may Seriously Hamper Nonlinear Frequency-Division Multiplexing
The performance of optical fiber systems based on nonlinear
frequency-division multiplexing (NFDM) or on more conventional transmission
techniques is compared through numerical simulations. Some critical issues
affecting NFDM systems-namely, the strict requirements needed to avoid burst
interaction due to signal dispersion and the unfavorable dependence of
performance on burst length-are investigated, highlighting their potentially
disruptive effect in terms of spectral efficiency. Two digital processing
techniques are finally proposed to halve the guard time between NFDM symbol
bursts and reduce the size of the processing window at the receiver, increasing
spectral efficiency and reducing computational complexity.Comment: The manuscript has been submitted to Photonics Technology Letters for
publicatio
The SFXC software correlator for Very Long Baseline Interferometry: Algorithms and Implementation
In this paper a description is given of the SFXC software correlator,
developed and maintained at the Joint Institute for VLBI in Europe (JIVE). The
software is designed to run on generic Linux-based computing clusters. The
correlation algorithm is explained in detail, as are some of the novel modes
that software correlation has enabled, such as wide-field VLBI imaging through
the use of multiple phase centres and pulsar gating and binning. This is
followed by an overview of the software architecture. Finally, the performance
of the correlator as a function of number of CPU cores, telescopes and spectral
channels is shown.Comment: Accepted by Experimental Astronom
ShearLab: A Rational Design of a Digital Parabolic Scaling Algorithm
Multivariate problems are typically governed by anisotropic features such as
edges in images. A common bracket of most of the various directional
representation systems which have been proposed to deliver sparse
approximations of such features is the utilization of parabolic scaling. One
prominent example is the shearlet system. Our objective in this paper is
three-fold: We firstly develop a digital shearlet theory which is rationally
designed in the sense that it is the digitization of the existing shearlet
theory for continuous data. This implicates that shearlet theory provides a
unified treatment of both the continuum and digital realm. Secondly, we analyze
the utilization of pseudo-polar grids and the pseudo-polar Fourier transform
for digital implementations of parabolic scaling algorithms. We derive an
isometric pseudo-polar Fourier transform by careful weighting of the
pseudo-polar grid, allowing exploitation of its adjoint for the inverse
transform. This leads to a digital implementation of the shearlet transform; an
accompanying Matlab toolbox called ShearLab is provided. And, thirdly, we
introduce various quantitative measures for digital parabolic scaling
algorithms in general, allowing one to tune parameters and objectively improve
the implementation as well as compare different directional transform
implementations. The usefulness of such measures is exemplarily demonstrated
for the digital shearlet transform.Comment: submitted to SIAM J. Multiscale Model. Simu
Edge Potential Functions (EPF) and Genetic Algorithms (GA) for Edge-Based Matching of Visual Objects
Edges are known to be a semantically rich representation of the contents of a digital image. Nevertheless, their use in practical applications is sometimes limited by computation and complexity constraints. In this paper, a new approach is presented that addresses the problem of matching visual objects in digital images by combining the concept of Edge Potential Functions (EPF) with a powerful matching tool based on Genetic Algorithms (GA). EPFs can be easily calculated starting from an edge map and provide a kind of attractive pattern for a matching contour, which is conveniently exploited by GAs. Several tests were performed in the framework of different image matching applications. The results achieved clearly outline the potential of the proposed method as compared to state of the art methodologies. (c) 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works
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