1,491 research outputs found
Efficient Fast-Convolution-Based Waveform Processing for 5G Physical Layer
This paper investigates the application of fast-convolution (FC) filtering
schemes for flexible and effective waveform generation and processing in the
fifth generation (5G) systems. FC-based filtering is presented as a generic
multimode waveform processing engine while, following the progress of 5G new
radio standardization in the Third-Generation Partnership Project, the main
focus is on efficient generation and processing of subband-filtered cyclic
prefix orthogonal frequency-division multiplexing (CP-OFDM) signals. First, a
matrix model for analyzing FC filter processing responses is presented and used
for designing optimized multiplexing of filtered groups of CP-OFDM physical
resource blocks (PRBs) in a spectrally well-localized manner, i.e., with narrow
guardbands. Subband filtering is able to suppress interference leakage between
adjacent subbands, thus supporting independent waveform parametrization and
different numerologies for different groups of PRBs, as well as asynchronous
multiuser operation in uplink. These are central ingredients in the 5G waveform
developments, particularly at sub-6-GHz bands. The FC filter optimization
criterion is passband error vector magnitude minimization subject to a given
subband band-limitation constraint. Optimized designs with different guardband
widths, PRB group sizes, and essential design parameters are compared in terms
of interference levels and implementation complexity. Finally, extensive coded
5G radio link simulation results are presented to compare the proposed approach
with other subband-filtered CP-OFDM schemes and time-domain windowing methods,
considering cases with different numerologies or asynchronous transmissions in
adjacent subbands. Also the feasibility of using independent transmitter and
receiver processing for CP-OFDM spectrum control is demonstrated
Systematic search for gamma-ray periodicity in active galactic nuclei detected by the Fermi Large Area Telescope
We use nine years of gamma-ray data provided by the Fermi Large Area
Telescope (LAT) to systematically study the light curves of more than two
thousand active galactic nuclei (AGN) included in recent Fermi-LAT catalogs.
Ten different techniques are used, which are organized in an automatic
periodicity-search pipeline, in order to search for evidence of periodic
emission in gamma rays. Understanding the processes behind this puzzling
phenomenon will provide a better view about the astrophysical nature of these
extragalactic sources. However, the observation of temporal patterns in
gamma-ray light curves of AGN is still challenging. Despite the fact that there
have been efforts on characterizing the temporal emission of some individual
sources, a systematic search for periodicities by means of a full likelihood
analysis applied to large samples of sources was missing. Our analysis finds 11
AGN, of which 9 are identified for the first time, showing periodicity at more
than 4sigma in at least four algorithms. These findings will help in solving
questions related to the astrophysical origin of this periodic behavior.Comment: 16 pages, 5 figures, 4 tables. Accepted by Ap
Off-The-Grid Spectral Compressed Sensing With Prior Information
Recent research in off-the-grid compressed sensing (CS) has demonstrated
that, under certain conditions, one can successfully recover a spectrally
sparse signal from a few time-domain samples even though the dictionary is
continuous. In this paper, we extend off-the-grid CS to applications where some
prior information about spectrally sparse signal is known. We specifically
consider cases where a few contributing frequencies or poles, but not their
amplitudes or phases, are known a priori. Our results show that equipping
off-the-grid CS with the known-poles algorithm can increase the probability of
recovering all the frequency components.Comment: 5 pages, 4 figure
Acoustical direction finding with time-modulated arrays
Time-Modulated Linear Arrays (TMLAs) offer useful efficiency savings over conventional phased arrays when applied in parameter estimation applications. The present paper considers the application of TMLAs to acoustic systems and proposes an algorithm for efficiently deriving the arrival angle of a signal. The proposed technique is applied in the frequency domain, where the signal and harmonic content is captured. Using a weighted average method on harmonic amplitudes and their respective main beam angles, it is possible to determine an estimate for the signal’s direction of arrival. The method is demonstrated and evaluated using results from both numerical and practical implementations and performance data is provided. The use of Micro-Electromechanical Systems (MEMS) sensors allows time-modulation techniques to be applied at ultrasonic frequencies. Theoretical predictions for an array of five isotropic elements with half-wavelength spacing and 1000 data samples suggest an accuracy of ±1∘ within an angular range of approximately ±50∘ . In experiments of a 40 kHz five-element microphone array, a Direction of Arrival (DoA) estimation within ±2.5∘ of the target signal is readily achieved inside a ±45∘ range using a single switched input stage and a simple hardware setup
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