Experimental Study of a Transmission System Based on FBMC/OQAM

Introduction. This paper investigates a transmission system based on FBMC/OQAM multiplexing. This system is characterized by a high spectral efficiency, thereby attracting interest as an alternative transmission method in future wireless mobile communication standards. However, a disadvantage of the system is the high complexity of signal processing. There are numerous publications that study the FBMC/OQAM system from a theoretical perspective. This paper presents an experimental study of a transmission system based on FBMC/OQAM.Aim. Verification of a transmission system based on FBMC/OQAM multiplexing in a wireless channel.Materials and methods. Computer simulation modeling in Matlab and experimental research using Keysight and Rohde & Schwarz certified measuring instruments.Results. A model of synthesis and signal processing was developed, and a frame structure was proposed. The processing included synchronization, since the study was carried out in a wireless double-dispersive channel. Time synchronization was provided by the method of time-domain correlation. A preamble consisting of two symbols was used for CFO compensation. Channel estimation in FBMC/OQAM was conducted by pilot symbols spread over the time-frequency domain, a method with an auxiliary pilot to compensate for intrinsic interference, as well as Zero Forcing and a linear interpolator. As a result, dependences of the bit error rate on the Eb/N0 in various channels were obtained. An error rate of 10−4 was achieved under the Eb/N0 equal to 13.4 dB, 15.3 dB and 20.9 dB in the first, second and third channel, respectively.Conclusion. A FBMC/OQAM-based transmission system with a linear equalizer can operate without a cyclic prefix in a multipath wireless channel, providing comparable noise immunity to OFDM-CP. Long frames should be used to obtain greater spectral efficiency, due to the presence of a transition zone at the beginning and end of the FBMC/OQAM frame.

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Method of estimation of hidden correlation of narrowband noise signals

Izmeritel`naya Tekhnika ◽

10.32446/0368-1025it.2019-12-34-39 ◽

2019 ◽

pp. 34-39 ◽

Cited By ~ 1

Author(s):

E.I. Chernov ◽

N.E. Sobolev ◽

A.A. Bondarchuk ◽

L.E. Aristarhova

Keyword(s):

Signal Processing ◽

Digital Signal Processing ◽

New Technology ◽

Digital Signal ◽

Measuring Instruments ◽

Central Frequency ◽

Pearson Criterion ◽

Useful Signal ◽

Band Limited ◽

Narrowband Noise

The concept of hidden correlation of noise signals is introduced. The existence of a hidden correlation between narrowband noise signals isolated simultaneously from broadband band-limited noise is theoretically proved. A method for estimating the latent correlation of narrowband noise signals has been developed and experimentally investigated. As a result of the experiment, where a time frag ent of band-limited noise, the basis of which is shot noise, is used as the studied signal, it is established: when applying the Pearson criterion, there is practically no correlation between the signal at the Central frequency and the sum of signals at mirror frequencies; when applying the proposed method for the analysis of the same signals, a strong hidden correlation is found. The proposed method is useful for researchers, engineers and metrologists engaged in digital signal processing, as well as developers of measuring instruments using a new technology for isolating a useful signal from noise – the method of mirror noise images.

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BlueFlood

ACM Transactions on Internet of Things ◽

10.1145/3462755 ◽

2021 ◽

Vol 2 (4) ◽

pp. 1-30

Author(s):

Beshr Al Nahas ◽

Antonio Escobar-Molero ◽

Jirka Klaue ◽

Simon Duquennoy ◽

Olaf Landsiedel

Keyword(s):

Experimental Study ◽

Bit Error Rate ◽

Error Rate ◽

Data Dissemination ◽

Delivery Ratio ◽

Controlled Experiments ◽

Seamless Integration ◽

Peer Communication ◽

Shift Keying ◽

University Buildings

Bluetooth is an omnipresent technology, available on billions of devices today. While it has been traditionally limited to peer-to-peer communication and star networks, the recent Bluetooth Mesh standard extends it to multi-hop networking. In addition, the Bluetooth 5 standard introduces new modes to allow for increased reliability. In this article, we evaluate the feasibility of concurrent transmissions (CT) in Bluetooth via modeling and controlled experiments and then devise an efficient network-wide data dissemination protocol, BlueFlood, based on CT for multi-hop Bluetooth networks. First, we model and analyze how CT distorts the received waveform and characterize the Bit Error Rate of a Frequency-Shift Keying receiver to show that CT is feasible over Bluetooth. Second, we verify our analytic results with a controlled experimental study of CT over Bluetooth PHY. Third, we present BlueFlood, a fast and efficient network-wide data dissemination in multi-hop Bluetooth networks. In our experimental evaluation, in two testbeds deployed in university buildings, we show that BlueFlood achieves 99.9% end-to-end delivery ratio with a duty-cycle of 0.4% for periodic dissemination of advertising packets of 38 bytes with 200 milliseconds intervals at 2 Mbps. Moreover, we show that BlueFlood can be received by off-the-shelf devices such as smartphones, paving a seamless integration with existing technologies.

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Application of UAV in Search and Rescue Actions in Underground Mine—A Specific Sound Detection in Noisy Acoustic Signal

Energies ◽

10.3390/en14133725 ◽

2021 ◽

Vol 14 (13) ◽

pp. 3725

Author(s):

Paweł Zimroz ◽

Paweł Trybała ◽

Adam Wróblewski ◽

Mateusz Góralczyk ◽

Jarosław Szrek ◽

...

Keyword(s):

Signal Processing ◽

Acoustic Signal ◽

Processing Technique ◽

Underground Mine ◽

Search And Rescue ◽

Reference Spectrum ◽

Signal Processing Technique ◽

Time Frequency ◽

Communication Device ◽

Frequency Representation

The possibility of the application of an unmanned aerial vehicle (UAV) in search and rescue activities in a deep underground mine has been investigated. In the presented case study, a UAV is searching for a lost or injured human who is able to call for help but is not able to move or use any communication device. A UAV capturing acoustic data while flying through underground corridors is used. The acoustic signal is very noisy since during the flight the UAV contributes high-energetic emission. The main goal of the paper is to present an automatic signal processing procedure for detection of a specific sound (supposed to contain voice activity) in presence of heavy, time-varying noise from UAV. The proposed acoustic signal processing technique is based on time-frequency representation and Euclidean distance measurement between reference spectrum (UAV noise only) and captured data. As both the UAV and “injured” person were equipped with synchronized microphones during the experiment, validation has been performed. Two experiments carried out in lab conditions, as well as one in an underground mine, provided very satisfactory results.

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Applications of Time-Frequency Signal Processing in Wireless Communications and Bioengineering

EURASIP Journal on Advances in Signal Processing ◽

10.1155/2010/879104 ◽

2011 ◽

Vol 2010 (1) ◽

Cited By ~ 2

Author(s):

LuisF Chaparro (EURASIP Member) ◽

Aydın Akan (EURASIP Member) ◽

SyedIsmail Shah ◽

Lutfiye Durak-Ata

Keyword(s):

Signal Processing ◽

Wireless Communications ◽

Frequency Signal ◽

Time Frequency

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A New Method for Phase Difference Estimation Based on Time-Varying Signal Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.333-335.650 ◽

2013 ◽

Vol 333-335 ◽

pp. 650-655

Author(s):

Peng Hui Niu ◽

Yin Lei Qin ◽

Shun Ping Qu ◽

Yang Lou

Keyword(s):

Signal Processing ◽

Real Time ◽

Phase Difference ◽

Time Signal ◽

Time Interval ◽

Time Varying ◽

Signal Model ◽

Time Frequency ◽

Mass Flowmeter ◽

Coriolis Mass Flowmeter

A new signal processing method for phase difference estimation was proposed based on time-varying signal model, whose frequency, amplitude and phase are time-varying. And then be applied Coriolis mass flowmeter signal. First, a bandpass filtering FIR filter was applied to filter the sensor output signal in order to improve SNR. Then, the signal frequency could be calculated based on short-time frequency estimation. Finally, by short window intercepting, the DTFT algorithm with negative frequency contribution was introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference obtained, the time interval of two signals was calculated. Simulation results show that the algorithms studied are efficient. Furthermore, the computation of algorithms studied is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.

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Compressive Sensing in Signal Processing: Algorithms and Transform Domain Formulations

Mathematical Problems in Engineering ◽

10.1155/2016/7616393 ◽

2016 ◽

Vol 2016 ◽

pp. 1-16 ◽

Cited By ~ 19

Author(s):

Irena Orović ◽

Vladan Papić ◽

Cornel Ioana ◽

Xiumei Li ◽

Srdjan Stanković

Keyword(s):

Signal Processing ◽

Fourier Transform ◽

Compressive Sensing ◽

Signal Reconstruction ◽

Signal Acquisition ◽

Transform Domain ◽

Hermite Transform ◽

Time Frequency ◽

Reconstruction Methods ◽

Fourier Transform Domain

Compressive sensing has emerged as an area that opens new perspectives in signal acquisition and processing. It appears as an alternative to the traditional sampling theory, endeavoring to reduce the required number of samples for successful signal reconstruction. In practice, compressive sensing aims to provide saving in sensing resources, transmission, and storage capacities and to facilitate signal processing in the circumstances when certain data are unavailable. To that end, compressive sensing relies on the mathematical algorithms solving the problem of data reconstruction from a greatly reduced number of measurements by exploring the properties of sparsity and incoherence. Therefore, this concept includes the optimization procedures aiming to provide the sparsest solution in a suitable representation domain. This work, therefore, offers a survey of the compressive sensing idea and prerequisites, together with the commonly used reconstruction methods. Moreover, the compressive sensing problem formulation is considered in signal processing applications assuming some of the commonly used transformation domains, namely, the Fourier transform domain, the polynomial Fourier transform domain, Hermite transform domain, and combined time-frequency domain.

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Time–frequency and time–scale analyses for structural health monitoring

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2006.1936 ◽

2006 ◽

Vol 365 (1851) ◽

pp. 449-477 ◽

Cited By ~ 67

Author(s):

Wiesław J Staszewski ◽

Amy N Robertson

Keyword(s):

Signal Processing ◽

Structural Health Monitoring ◽

Damage Detection ◽

Health Monitoring ◽

Time Scale ◽

Time Frequency ◽

Structural Health ◽

Variant Analysis

Signal processing is one of the most important elements of structural health monitoring. This paper documents applications of time-variant analysis for damage detection. Two main approaches, the time–frequency and the time–scale analyses are discussed. The discussion is illustrated by application examples relevant to damage detection.

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