18 research outputs found
Spectrum sensing for cognitive radio and radar systems
The use of the radio frequency spectrum is increasing at a rapid rate. Reliable and efficient operation in a crowded radio spectrum requires innovative solutions and techniques. Future wireless communication and radar systems should be aware of their surrounding radio environment in order to have the ability to adapt their operation to the effective situation. Spectrum sensing techniques such as detection, waveform recognition, and specific emitter identification are key sources of information for characterizing the surrounding radio environment and extracting valuable information, and consequently adjusting transceiver parameters for facilitating flexible, efficient, and reliable operation.
In this thesis, spectrum sensing algorithms for cognitive radios and radar intercept receivers are proposed. Single-user and collaborative cyclostationarity-based detection algorithms are proposed: Multicycle detectors and robust nonparametric spatial sign cyclic correlation based fixed sample size and sequential detectors are proposed. Asymptotic distributions of the test statistics under the null hypothesis are established. A censoring scheme in which only informative test statistics are transmitted to the fusion center is proposed for collaborative detection. The proposed detectors and methods have the following benefits: employing cyclostationarity enables distinction among different systems, collaboration mitigates the effects of shadowing and multipath fading, using multiple strong cyclic frequencies improves the performance, robust detection provides reliable performance in heavy-tailed non-Gaussian noise, sequential detection reduces the average detection time, and censoring improves energy efficiency.
In addition, a radar waveform recognition system for classifying common pulse compression waveforms is developed. The proposed supervised classification system classifies an intercepted radar pulse to one of eight different classes based on the pulse compression waveform: linear frequency modulation, Costas frequency codes, binary codes, as well as Frank, P1, P2, P3, and P4 polyphase codes.
A robust M-estimation based method for radar emitter identification is proposed as well. A common modulation profile from a group of intercepted pulses is estimated and used for identifying the radar emitter. The M-estimation based approach provides robustness against preprocessing errors and deviations from the assumed noise model
Wideband Autonomous Cognitive Radios: Spectrum Awareness and PHY/MAC Decision Making
The cognitive radios (CRs) have opened up new ways of better utilizing the scarce wireless spectrum resources. The CRs have been made feasible by recent advances in software-defined radios (SDRs), smart antennas, reconfigurable radio frequency (RF) front-ends, and full-duplex RF front-end architectures, to name a few. Generally, a CR is considered as a dynamically reconfigurable radio capable of adapting its operating parameters to the surrounding environment. Recent developments in spectrum policy and regulatory domains also allow more flexible and efficient utilization of wider RF spectrum range in the future. In line with the future directions of CRs, a new vision of a future autonomous CR device, called Radiobots, was previously proposed. The goals of the proposed Radiobot surpass the dynamic spectrum access (DSA) to achieve wideband operability and the main features of cognition. In order to ensure the practicality and robust operation of the Radiobot structure, the research focus of this dissertation includes the following aspects: 1) robust spectrum sensing and operability in a centralized CR network setup; 2) robust multivariate non-parametric quickest detection for dynamic spectrum usage tracking in an alien RF environment; 3) joint physical layer and medium access control layer (PHY/MAC) decision-making for wideband bandwidth aggregation (simultaneous operation over multiple modes/networks); and 4) autonomous spectrum sensing scheduling solutions in an alien ultra wideband RF environment. The major contribution of this dissertation is to investigate the feasibility of the autonomous CR operation in heterogeneous RF environments, and to provide novel solutions to the fundamental and crucial problems/challenges, including spectrum sensing, spectrum awareness, wideband operability, and autonomous PHY/MAC protocols, thus bringing the autonomous Radiobot one step closer to reality
Enhanced Spectrum Sensing for Cognitive Cellular Systems
This dissertation aims at improving spectrum sensing algorithms in order to effectively apply
them to cellular systems. In wireless communications, cellular systems occupy a significant
part of the spectrum. The spectrum usage for cellular systems are rapidly expanding due to the
increasing demand for wireless services in our society. This results in radio frequency spectrum
scarcity. Cellular systems can effectively handle this issue through cognitive mechanisms for
spectrum utilization. Spectrum sensing plays the first stage of cognitive cycles for the adaptation
to radio environments.
This dissertation focuses on maximizing the reliability of spectrum sensing to satisfy
regulation requirements with respect to high spectrum sensing performance and an acceptable
error rate. To overcome these challenges, characteristics of noise and manmade signals are
exploited for spectrum sensing. Moreover, this dissertation considers system constraints, the
compatibility with the current and the trends of future generations. Newly proposed and existing
algorithms were evaluated in simulations in the context of cellular systems. Based on a prototype
of cognitive cellular systems (CCSs), the proposed algorithms were assessed in realistic scenarios.
These algorithms can be applied to CCSs for the awareness of desired signals in licensed and
unlicensed bands.
For orthogonal frequency-division multiplexing (OFDM) signals, this dissertation exploits
the characteristics of pilot patterns and preambles for new algorithms. The new algorithms
outperform the existing ones, which also utilize pilot patterns. Additionally, the new algorithms
can work with short observation durations, which is not possible with the existing algorithms. The
Digital Video Broadcasting - Terrestrial (DVB-T) standard is taken as an example application for
the algorithms. The algorithms can also be developed for filter bank multicarrier (FBMC) signals,
which are a potential candidate for multiplexing techniques in the next cellular generations. The
experimental results give insights for the reliability of the algorithms, taking system constraints
v
into account. Another new sensing algorithm, based on a preamble, is proposed for the DVBT2
standard, which is the second generation of of DVB system. DVB-T2 systems have been
deployed in worldwide regions. This algorithm can detect DVB-T2 signals in a very short
observation interval, which is helpful for the in-band sensing mode, to protect primary users (in
nearly real-time) from the secondary transmission.
An enhanced spectrum sensing algorithm based on cyclostationary signatures is proposed
to detect desired signals in very low signal-to-noise ratios (SNRs). This algorithm can be
developed to detect the single-carrier frequency division multiple access (SC-FDMA) signal,
which is adopted for the uplink of long-term evolution (LTE) systems. This detector substantially
outperforms the existing detection algorithms with the marginal complexity of some scalar
multiplications. The test statistics are explicitly formulated in mathematical formulas, which
were not presented in the previous work. The formulas and simulation results provide a useful
strategy for cyclostationarity-based detection with different modulation types.
For multiband spectrum sensing, an effective scheme is proposed not only to detect but
also to classify LTE signals in multiple channels in a wide frequency range. To the best of our
knowledge, no scheme had previously been described to perform the sensing tasks. The scheme is
reliable and flexible for implementation, and there is almost no performance degradation caused
by the scheme compared to single-channel spectrum sensing. The multiband sensing scheme was experimentally assessed in scenarios where the existing infrastructures are interrupted to
provide mobile communications.
The proposed algorithms and scheme facilitate cognitive capabilities to be applied to real
cellular communications. This enables the significantly improved spectrum utilization of CCSs
Space time transceiver design over multipath fading channels
Imperial Users onl
Space-time processing for wireless mobile communications
Intersymbol interference (ISI) and co-channel interference (CCI) are two major
obstacles to high speed data transmission in wireless cellular communications
systems. Unlike thermal noise, their effects cannot be removed by
increasing the signal power and are time-varying due to the relative motion
between the transmitters and receivers. Space-time processing offers a signal
processing framework to optimally integrate the spatial and temporal properties
of the signal for maximal signal reception and at the same time, mitigate
the ISI and CCI impairments. In this thesis, we focus on the development of
this emerging technology to combat the undesirable effects of ISI and CCL
We first develop a convenient mathematical model to parameterize the
space-time multipath channel based on signal path power, directions and
times of arrival. Starting from the continuous time-domain, we derive compact
expressions of the vector space-time channel model that lead to the
notion of block space-time manifold, Under certain identifiability conditions,
the noiseless vector-channel outputs will lie on a subspace constructed from
a set. of basis belonging to the block space-time manifold. This is an important
observation as many high resolution array processing algorithms Can be
applied directly to estimate the multi path channel parameters.
Next we focus on the development of semi-blind channel identification
and equalization algorithms for fast time-varying multi path channels. Specifically.
we develop space-time processing algorithms for wireless TDMA networks that use short burst data formats with extremely short training data.
sequences. Due to the latter, the estimated channel parameters are extremely
unreliable for equalization with conventional adaptive methods. We approach
the channel acquisition, tracking and equalization problems jointly, and exploit
the richness of the inherent structural relationship between the channel
parameters and the data sequence by repeated use of available data through a forward- backward optimization procedure. This enables the fuller exploitation
of the available data. Our simulation studies show that significant performance
gains are achieved over conventional methods.
In the final part of this thesis, we address the problem identifying and
equalizing multi path communication channels in the presence of strong CCl.
By considering CCI as stochasic processes, we find that temporal diversity
can be gained by observing the channel outputs from a tapped delay line. Together with the assertion that the finite alphabet property of the information
sequences can offer additional information about the channel parameters and
the noise-plus-covariance matrix, we develop a spatial temporal algorithm,
iterative reweighting alternating minimization, to estimate the channel parameters
and information sequence in a weighted least squares framework.
The proposed algorithm is robust as it does not require knowledge of the
number of CCI nor their structural information. Simulation studies demonstrate
its efficacy over many reported methods
Classification and modeling of power line noise using machine learning techniques
A thesis submitted in ful lment of the requirements
for the degree of Doctor of Philosophy
in the
School of Electrical and Information Engineering
Faculty of Engineering and Built Environment
June 2017The realization of robust, reliable and e cient data transmission have been the theme of
recent research, most importantly in real channel such as the noisy, fading prone power
line communication (PLC) channel. The focus is to exploit old techniques or create new
techniques capable of improving the transmission reliability and also increasing the transmission
capacity of the real communication channels. Multi-carrier modulation scheme such
as Orthogonal Frequency Division Multiplexing (OFDM) utilizing conventional single-carrier
modulation is developed to facilitate a robust data transmission, increasing transmission capacity
(e cient bandwidth usage) and further reducing design complexity in PLC systems.
On the contrary, the reliability of data transmission is subjected to several inhibiting factors
as a result of the varying nature of the PLC channel. These inhibiting factors include noise,
perturbation and disturbances. Contrary to the Additive White Gaussian noise (AWGN)
model often assumed in several communication systems, this noise model fails to capture
the attributes of noise encountered on the PLC channel. This is because periodic noise or
random noise pulses injected by power electronic appliances on the network is a deviation
from the AWGN. The nature of the noise is categorized as non-white non-Gaussian and
unstable due to its impulsive attributes, thus, it is labeled as Non-additive White Gaussian
Noise (NAWGN). These noise and disturbances results into long burst errors that corrupts
signals being transmitted, thus, the PLC is labeled as a horrible or burst error channel.
The e cient and optimal performance of a conventional linear receiver in the white Gaussian
noise environment can therefore be made to drastically degrade in this NAWGN environment.
Therefore, transmission reliability in such environment can be greatly enhanced if we
know and exploit the knowledge of the channel's statistical attributes, thus, the need for
developing statistical channel model based on empirical data. In this thesis, attention is
focused on developing a recon gurable software de ned un-coded single-carrier and multicarrier
PLC transceiver as a tool for realizing an optimized channel model for the narrowband
PLC (NB-PLC) channel.
First, a novel recon gurable software de ned un-coded single-carrier and multi-carrier PLC
transceiver is developed for real-time NB-PLC transmission. The transceivers can be adapted
to implement di erent waveforms for several real-time scenarios and performance evaluation.
Due to the varying noise parameters obtained from country to country as a result of
the dependence of noise impairment on mains voltages, topology of power line, place and
time, the developed transceivers is capable of facilitating constant measurement campaigns
to capture these varying noise parameters before statistical and mathematically inclined
channel models are derived.
Furthermore, the single-carrier (Binary Phase Shift Keying (BPSK), Di erential BPSK
(DBPSK), Quadrature Phase Shift Keying (QPSK) and Di erential QPSK (DQPSK)) PLC
transceiver system developed is used to facilitate a First-Order semi-hidden Fritchman
Markov modeling (SHFMM) of the NB-PLC channel utilizing the e cient iterative Baum-
Welch algorithm (BWA) for parameter estimation. The performance of each modulation
scheme is evaluated in a mildly and heavily disturbed scenarios for both residential and
laboratory site considered. The First-Order estimated error statistics of the realized First-
Order SHFMM have been analytically validated in terms of performance metrics such as:
log-likelihood ratio (LLR), error-free run distribution (EFRD), error probabilities, mean
square error (MSE) and Chi-square ( 2) test. The reliability of the model results is also
con rmed by an excellent match between the empirically obtained error sequence and the
SHFMM regenerated error sequence as shown by the error-free run distribution plot.
This thesis also reports a novel development of a low cost, low complexity Frequency-shift
keying (FSK) - On-o keying (OOK) in-house hybrid PLC and VLC system. The functionality
of this hybrid PLC-VLC transceiver system was ascertained at both residential and
laboratory site at three di erent times of the day: morning, afternoon and evening. A First
and Second-Order SHFMM of the hybrid system is realized. The error statistics of the realized
First and Second-Order SHFMMs have been analytically validated in terms of LLR,
EFRD, error probabilities, MSE and Chi-square ( 2). The Second-Order SHFMMs have
also been analytically validated to be superior to the First-Order SHFMMs although at the
expense of added computational complexity. The reliability of both First and Second-Order
SHFMM results is con rmed by an excellent match between the empirical error sequences
and SHFMM re-generated error sequences as shown by the EFRD plot.
In addition, the multi-carrier (QPSK-OFDM, Di erential QPSK (DQPSK)-OFDM) and
Di erential 8-PSK (D8PSK)-OFDM) PLC transceiver system developed is used to facilitate
a First and Second-Order modeling of the NB-PLC system using the SHFMM and BWA
for parameter estimation. The performance of each OFDM modulation scheme in evaluated
and compared taking into consideration the mildly and heavily disturbed noise scenarios
for the two measurement sites considered. The estimated error statistics of the realized
SHFMMs have been analytically validated in terms of LLR, EFRD, error probabilities, MSE
and Chi-square ( 2) test. The estimated Second-Order SHFMMs have been analytically
validated to be outperform the First-Order SHFMMs although with added computational
complexity. The reliability of the models is con rmed by an excellent match between the
empirical data and SHFMM generated data as shown by the EFRD plot.
The statistical models obtained using Baum-Welch to adjust the parameters of the adopted
SHFMM are often locally maximized. To solve this problem, a novel Metropolis-Hastings
algorithm, a Bayesian inference approach based on Markov Chain Monte Carlo (MCMC)
is developed to optimize the parameters of the adopted SHFMM. The algorithm is used to
optimize the model results obtained from the single-carrier and multi-carrier PLC systems
as well as that of the hybrid PLC-VLC system. Consequently, as deduced from the results,
the models obtained utilizing the novel Metropolis-Hastings algorithm are more precise, near
optimal model with parameter sets that are closer to the global maxima.
Generally, the model results obtained in this thesis are relevant in enhancing transmission
reliability on the PLC channel through the use of the models to improve the adopted modulation
schemes, create adaptive modulation techniques, develop and evaluate forward error
correction (FEC) codes such as a concatenation of Reed-Solomon and Permutation codes and
other robust codes suitable for exploiting and mitigating noise impairments encountered on
the low voltage NB-PLC channel. Furthermore, the recon gurable software de ned NB-PLC
transceiver test-bed developed can be utilized for future measurement campaign as well as
adapted for multiple-input and multiple-output (MIMO) PLC applications.MT201
Classification and modeling of power line noise using machine learning techniques
A thesis submitted in ful lment of the requirements
for the degree of Doctor of Philosophy
in the
School of Electrical and Information Engineering
Faculty of Engineering and Built Environment
June 2017The realization of robust, reliable and e cient data transmission have been the theme of
recent research, most importantly in real channel such as the noisy, fading prone power
line communication (PLC) channel. The focus is to exploit old techniques or create new
techniques capable of improving the transmission reliability and also increasing the transmission
capacity of the real communication channels. Multi-carrier modulation scheme such
as Orthogonal Frequency Division Multiplexing (OFDM) utilizing conventional single-carrier
modulation is developed to facilitate a robust data transmission, increasing transmission capacity
(e cient bandwidth usage) and further reducing design complexity in PLC systems.
On the contrary, the reliability of data transmission is subjected to several inhibiting factors
as a result of the varying nature of the PLC channel. These inhibiting factors include noise,
perturbation and disturbances. Contrary to the Additive White Gaussian noise (AWGN)
model often assumed in several communication systems, this noise model fails to capture
the attributes of noise encountered on the PLC channel. This is because periodic noise or
random noise pulses injected by power electronic appliances on the network is a deviation
from the AWGN. The nature of the noise is categorized as non-white non-Gaussian and
unstable due to its impulsive attributes, thus, it is labeled as Non-additive White Gaussian
Noise (NAWGN). These noise and disturbances results into long burst errors that corrupts
signals being transmitted, thus, the PLC is labeled as a horrible or burst error channel.
The e cient and optimal performance of a conventional linear receiver in the white Gaussian
noise environment can therefore be made to drastically degrade in this NAWGN environment.
Therefore, transmission reliability in such environment can be greatly enhanced if we
know and exploit the knowledge of the channel's statistical attributes, thus, the need for
developing statistical channel model based on empirical data. In this thesis, attention is
focused on developing a recon gurable software de ned un-coded single-carrier and multicarrier
PLC transceiver as a tool for realizing an optimized channel model for the narrowband
PLC (NB-PLC) channel.
First, a novel recon gurable software de ned un-coded single-carrier and multi-carrier PLC
transceiver is developed for real-time NB-PLC transmission. The transceivers can be adapted
to implement di erent waveforms for several real-time scenarios and performance evaluation.
Due to the varying noise parameters obtained from country to country as a result of
the dependence of noise impairment on mains voltages, topology of power line, place and
time, the developed transceivers is capable of facilitating constant measurement campaigns
to capture these varying noise parameters before statistical and mathematically inclined
channel models are derived.
Furthermore, the single-carrier (Binary Phase Shift Keying (BPSK), Di erential BPSK
(DBPSK), Quadrature Phase Shift Keying (QPSK) and Di erential QPSK (DQPSK)) PLC
transceiver system developed is used to facilitate a First-Order semi-hidden Fritchman
Markov modeling (SHFMM) of the NB-PLC channel utilizing the e cient iterative Baum-
Welch algorithm (BWA) for parameter estimation. The performance of each modulation
scheme is evaluated in a mildly and heavily disturbed scenarios for both residential and
laboratory site considered. The First-Order estimated error statistics of the realized First-
Order SHFMM have been analytically validated in terms of performance metrics such as:
log-likelihood ratio (LLR), error-free run distribution (EFRD), error probabilities, mean
square error (MSE) and Chi-square ( 2) test. The reliability of the model results is also
con rmed by an excellent match between the empirically obtained error sequence and the
SHFMM regenerated error sequence as shown by the error-free run distribution plot.
This thesis also reports a novel development of a low cost, low complexity Frequency-shift
keying (FSK) - On-o keying (OOK) in-house hybrid PLC and VLC system. The functionality
of this hybrid PLC-VLC transceiver system was ascertained at both residential and
laboratory site at three di erent times of the day: morning, afternoon and evening. A First
and Second-Order SHFMM of the hybrid system is realized. The error statistics of the realized
First and Second-Order SHFMMs have been analytically validated in terms of LLR,
EFRD, error probabilities, MSE and Chi-square ( 2). The Second-Order SHFMMs have
also been analytically validated to be superior to the First-Order SHFMMs although at the
expense of added computational complexity. The reliability of both First and Second-Order
SHFMM results is con rmed by an excellent match between the empirical error sequences
and SHFMM re-generated error sequences as shown by the EFRD plot.
In addition, the multi-carrier (QPSK-OFDM, Di erential QPSK (DQPSK)-OFDM) and
Di erential 8-PSK (D8PSK)-OFDM) PLC transceiver system developed is used to facilitate
a First and Second-Order modeling of the NB-PLC system using the SHFMM and BWA
for parameter estimation. The performance of each OFDM modulation scheme in evaluated
and compared taking into consideration the mildly and heavily disturbed noise scenarios
for the two measurement sites considered. The estimated error statistics of the realized
SHFMMs have been analytically validated in terms of LLR, EFRD, error probabilities, MSE
and Chi-square ( 2) test. The estimated Second-Order SHFMMs have been analytically
validated to be outperform the First-Order SHFMMs although with added computational
complexity. The reliability of the models is con rmed by an excellent match between the
empirical data and SHFMM generated data as shown by the EFRD plot.
The statistical models obtained using Baum-Welch to adjust the parameters of the adopted
SHFMM are often locally maximized. To solve this problem, a novel Metropolis-Hastings
algorithm, a Bayesian inference approach based on Markov Chain Monte Carlo (MCMC)
is developed to optimize the parameters of the adopted SHFMM. The algorithm is used to
optimize the model results obtained from the single-carrier and multi-carrier PLC systems
as well as that of the hybrid PLC-VLC system. Consequently, as deduced from the results,
the models obtained utilizing the novel Metropolis-Hastings algorithm are more precise, near
optimal model with parameter sets that are closer to the global maxima.
Generally, the model results obtained in this thesis are relevant in enhancing transmission
reliability on the PLC channel through the use of the models to improve the adopted modulation
schemes, create adaptive modulation techniques, develop and evaluate forward error
correction (FEC) codes such as a concatenation of Reed-Solomon and Permutation codes and
other robust codes suitable for exploiting and mitigating noise impairments encountered on
the low voltage NB-PLC channel. Furthermore, the recon gurable software de ned NB-PLC
transceiver test-bed developed can be utilized for future measurement campaign as well as
adapted for multiple-input and multiple-output (MIMO) PLC applications.MT201
Compressive Sensing of Multiband Spectrum towards Real-World Wideband Applications.
PhD Theses.Spectrum scarcity is a major challenge in wireless communication systems with their
rapid evolutions towards more capacity and bandwidth. The fact that the real-world
spectrum, as a nite resource, is sparsely utilized in certain bands spurs the proposal
of spectrum sharing. In wideband scenarios, accurate real-time spectrum sensing, as an
enabler of spectrum sharing, can become ine cient as it naturally requires the sampling
rate of the analog-to-digital conversion to exceed the Nyquist rate, which is resourcecostly
and energy-consuming. Compressive sensing techniques have been applied in
wideband spectrum sensing to achieve sub-Nyquist-rate sampling of frequency sparse
signals to alleviate such burdens.
A major challenge of compressive spectrum sensing (CSS) is the complexity of the sparse
recovery algorithm. Greedy algorithms achieve sparse recovery with low complexity but
the required prior knowledge of the signal sparsity. A practical spectrum sparsity estimation
scheme is proposed. Furthermore, the dimension of the sparse recovery problem
is proposed to be reduced, which further reduces the complexity and achieves signal
denoising that promotes recovery delity. The robust detection of incumbent radio is
also a fundamental problem of CSS. To address the energy detection problem in CSS,
the spectrum statistics of the recovered signals are investigated and a practical threshold
adaption scheme for energy detection is proposed. Moreover, it is of particular interest to
seek the challenges and opportunities to implement real-world CSS for systems with large
bandwidth. Initial research on the practical issues towards the real-world realization of
wideband CSS system based on the multicoset sampler architecture is presented.
In all, this thesis provides insights into two critical challenges - low-complexity sparse
recovery and robust energy detection - in the general CSS context, while also looks
into some particular issues towards the real-world CSS implementation based on the
i
multicoset sampler
Efficient symbol-spreading strategies for wireless communication
Includes bibliographical references (p. 76-78).Supported by AT&TBell Laboratories. Supported by the Dept. of the Navy, Office of the Chief of Naval Research. N00014-93-1-0686 Supported by the Advanced Research Projects Agency's RASSP program. Supported by the Air Force Office of Scientific Research. AFOSR-91-0034Gregory W. Wornell
Vibration Monitoring: Gearbox identification and faults detection
L'abstract è presente nell'allegato / the abstract is in the attachmen