219 research outputs found
Applications of nonuniform sampling in wideband multichannel communication systems
This research is an investigation into utilising randomised sampling in communication systems to ease the sampling rate requirements of digitally processing narrowband signals residing within a wide range of overseen frequencies. By harnessing the aliasing suppression capabilities of such sampling schemes, it is shown that certain processing tasks, namely spectrum sensing, can be performed at significantly low sampling rates compared to those demanded by uniform-sampling-based digital signal processing. The latter imposes sampling frequencies of at least twice the monitored bandwidth regardless of the spectral activity within. Aliasing can otherwise result in irresolvable processing problems, as the spectral support of the present signal is a priori unknown. Lower sampling rates exploit the processing module(s) resources (such as power) more efficiently and avoid the possible need for premium specialised high-cost DSP, especially if the handled bandwidth is considerably wide.
A number of randomised sampling schemes are examined and appropriate spectral analysis tools are used to furnish their salient features. The adopted periodogram-type estimators are tailored to each of the schemes and their statistical characteristics are assessed for stationary, and cyclostationary signals. Their ability to alleviate the bandwidth limitation of uniform sampling is demonstrated and the smeared-aliasing defect that accompanies randomised sampling is also quantified.
In employing the aforementioned analysis tools a novel wideband spectrum sensing approach is introduced. It permits the simultaneous sensing of a number of nonoverlapping spectral subbands constituting a wide range of monitored frequencies. The
operational sampling rates of the sensing procedure are not limited or dictated by the overseen bandwidth antithetical to uniform-sampling-based techniques. Prescriptive guidelines are developed to ensure that the proposed technique satisfies certain detection probabilities predefined by the user. These recommendations address the trade-off between the required sampling rate and the length of the signal observation window (sensing time) in a given scenario. Various aspects of the introduced multiband spectrum sensing approach are investigated and its applicability highlighted
Wideband Spectrum Sensing for Dynamic Spectrum Sharing
The proliferation of wireless devices grows exponentially, demanding more and more data
communication capacity over wireless links. Radio spectrum is a scarce resource, and traditional
wireless networks deployed by Mobile Network Operators (MNO) are based on an exclusive
spectrum band allocation. However, underutilization of some licensed bands in time and geographic
domains has been reported, especially in rural areas or areas away from high population density
zones. This coexistence of increasingly high data communication needs and spectrum
underutilization is an incomprehensible scenario. A more rational and efficient use of the spectrum
is the possibility of Licensed Users (known as Primary Users – PU) to lease the spectrum, when
not in use, to Unlicensed Users (known as Secondary Users – SU), or allowing the SU to
opportunistically use the spectrum after sensing and verifying that the PU is idle. In this latter
case, the SU must stop transmitting when the PU becomes active.
This thesis addresses the spectrum sensing task, which is essential to provide dynamic spectrum
sharing between PUs and SUs. We show that the Spectral Correlation Function (SCF) and the
Spectral Coherence Function (SCoF) can provide a robust signal detection algorithm by exploiting
the cyclostationary characteristics of the data communication signal. We enhance the most used
algorithm to compute de SCF - the FAM (FFT Accumulation Method) algorithm – to efficiently
compute the SCF in a local/zoomed region of the support ( ; ) plane (frequency/cycle frequency
plane). This will provide the quick identification of spectral bands in use by PUs or free, in a
wideband sampling scenario.
Further, the characterization of the probability density of the estimates of the SCF and SCoF
when only noise is present, using the FAM algorithm, will allow the definition of an adaptive
threshold to develop a blind (with respect to the noise statistics) Constant False Alarm Rate
(CFAR) detector (using the SCoF) and also a CFAR and a Constant Detection Rate (CDR)
detector when that characterization is used to obtain an estimate of the background noise variance
(using the SCF).A proliferação de dispositivos sem fios cresce de forma exponencial, exigindo cada vez mais
capacidade de comunicação de dados através de ligações sem fios. O espectro radioelétrico é um
recurso escasso, e as redes sem fios tradicionais implantadas pelos Operadores de Redes Móveis
baseiam-se numa atribuição exclusiva de bandas do espectro. No entanto, tem sido relatada a
subutilização de algumas bandas licenciadas quer ao longo do tempo, quer na sua localização
geográfica, especialmente em áreas rurais, e em áreas longe de zonas de elevada densidade
populacional. A coexistência da necessidade cada vez maior de comunicação de dados, e a
subutilização do espectro é um cenário incompreensÃvel. Uma utilização mais racional e eficiente
do espectro pressupõe a possibilidade dos Utilizadores Licenciados (conhecidos como Utilizadores
Primários – Primary Users - PU) alugarem o espectro, quando este não está a ser utilizado, a
Utilizadores Não Licenciados (conhecidos como Utilizadores Secundários – Secondary Users - SU),
ou permitir ao SU utilizar oportunisticamente o espectro após a deteção e verificação de que o PU
está inativo. Neste último caso, o SU deverá parar de transmitir quando o PU ficar ativo.
Nesta tese é abordada a tarefa de deteção espectral, que é essencial para proporcionar a partilha
dinâmica do espectro entre PUs e SUs. Mostra-se que a Função de Correlação Espectral (Spectral
Correlation Function - SCF) e a Função de Coerência Espectral (Spectral Coherence Function -
SCoF) permitem o desenvolvimento de um algoritmo robusto de deteção de sinal, explorando as
caracterÃsticas ciclo-estacionárias dos sinais de comunicação de dados. Propõe-se uma melhoria ao
algoritmo mais utilizado para cálculo da SCF – o método FAM (FFT Accumulation Method) -
para permitir o cálculo mais eficiente da SCF numa região local/ampliada do plano de suporte
/ (plano de frequência/frequência de ciclo). Esta melhoria permite a identificação rápida de
bandas espectrais em uso por PUs ou livres, num cenário de amostragem de banda larga.
Adicionalmente, é feita a caracterização da densidade de probabilidade das estimativas da SCF e
SCoF quando apenas o ruÃdo está presente, o que permite a definição de um limiar adaptativo,
para desenvolver um detetor de Taxa de Falso Alarme Constante (Constant False Alarm Rate –
CFAR) sem conhecimento do ruÃdo de fundo (usando a SCoF) e também um detetor CFAR e Taxa
de Deteção Constante (Constant Detection Rate – CDR), quando se utiliza aquela caracterização
para obter uma estimativa da variância do ruÃdo de fundo (usando a SCF)
Novel DEMON Spectra Analysis Techniques and Empirical Knowledge Based Reference Criterion for Acoustic Signal Classification
This paper presents some novel methods to estimate a vessel’s number of shafts, course, speed and classify it using the underwater acoustic noise it generates. A classification framework as well as a set of reference parameters for comparison are put forth. Identifying marine traffic in surroundings is an important task for vessels in an open sea. Vessels in vicinity can be identified using their signatures. One of the typical signatures emitted by a vessel is its acoustic measurements. The raw sonar data consisting of the acoustic signatures is generally observed manually by sonar operators for suggesting class of query vessel. The valuable information that can be extracted from the recorded acoustic signature includes shaft revolutions per minute (SRPM), number of blades (NOB), number of shafts, course and speed etc. Expert sonar operators use their empirical knowledge to estimate a vessel’s SRPM and NOB. Based on this information vessel classification is performed. Empirical knowledge comes with experience, and the manual process is prone to human error. To make the process systematic, calculation of the parameters of the received acoustic samples can be visually analyzed using Detection of Envelope Modulation on Noise (DEMON) spectra. Reported research mostly focuses on SRPM and NOB. Parameters such as number of shafts and vessel course and speed can effectively aid the vessel classification process. This paper makes three novel contributions in this area. Firstly, some novel DEMON spectra analysis techniques are proposed to estimate a water vessel’s number of shafts, speed, and relative course. Secondly, this paper presents a classification framework that uses the features extracted from DEMON spectra and compares them with a reference set. Thirdly, a novel set of reference parameters are provided that aid classification into categories of large merchant ship type 1, large merchant ship type 2, large merchant ship type 3, medium merchant ship, oiler, car carrier, cruise ship, fishing boat and fishing trawler. The proposed analysis and classification techniques were assessed through trials with 877 real acoustic signatures recorded under varying conditions of ship’s speed and sea state. The classification trials revealed a high accuracy of 94.7%
A Linear Subspace Approach to Burst Communication Signal Processing
This dissertation focuses on the topic of burst signal communications in a high interference environment. It derives new signal processing algorithms from a mathematical linear subspace approach instead of the common stationary or cyclostationary approach. The research developed new algorithms that have well-known optimality criteria associated with them. The investigation demonstrated a unique class of multisensor filters having a lower mean square error than all other known filters, a maximum likelihood time difference of arrival estimator that outperformed previously optimal estimators, and a signal presence detector having a selectivity unparalleled in burst interference environments. It was further shown that these improvements resulted in a greater ability to communicate, to locate electronic transmitters, and to mitigate the effects of a growing interference environment
- …