2,460 research outputs found
Application of hidden markov models to blind channel estimation and data detection in a gsm environment
In this paper, we present an algorithm based on the Hidden Markov Models (HMM) theory to solve the problem of blind channel estimation and sequence detection in mobile digital communications. The environment in which the algorithm is tested is the Paneuropean Mobile Radio System, also known as GSM. In this system, a large part in each burst is devoted to allocate a training sequence used to obtain a channel estimate. The algorithm presented would not require this sequence, and that would imply an increase of the system capacity. Performance, evaluated for standard test channels, is close to that of non-blind algorithms.Peer ReviewedPostprint (published version
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
Error models for digital channels and applications to wireless communication systems
Digital wireless channels are extremely prone to errors that appear in bursts or clusters.
Error models characterise the statistical behaviour of bursty profiles derived from
digital wireless channels. Generative error models also utilise those bursty profiles in
order to create alternatives, which are more efficient for experimental purposes. Error
models have a tremendous value for wireless systems. They are useful for the design
and performance evaluation of error control schemes, in addition to higher layer protocols
in which the statistical properties of the bursty profiles are greatly functional.
Furthermore, underlying wireless digital channels can be substituted by generated
error profiles. Consequently, computational load and simulation time can be significantly
reduced when executing experiments and performing evaluation simulations
for higher layer communications protocols and error control strategies.
The burst error statistics are the characterisation metrics of error models. These
statistics include: error-free run distribution; error-free burst distribution; error burst
distribution; error cluster distribution; gap distribution; block error probability distribution;
block burst probability distribution; bit error correlation function; normalised
covariance function; gap correlation function; and multigap distribution. These burst
error statistics scrutinise the error models and differentiate between them, with regards
to accuracy. Moreover, some of them are advantageous for the design of digital
components in wireless communication systems.
This PhD thesis aims to develop accurate and efficient error models and to find applications
for them. A thorough investigation has been conducted on the burst error
statistics. A breakdown of this thesis is presented as follows.
Firstly, an understanding of the different types of generative error models, namely,
Markovian based generative models, context-free grammars based generative models,
chaotic models, and deterministic process based generative models, has been presented.
The most widely used models amongst the generative models have been
compared with each other consulting the majority of burst error statistics. In order
to study generative error models, error burst profiles were obtained mainly from the
Enhanced General Packet Radio Service (EGPRS) system and also the Long Term
Evolution (LTE) system.
Secondly, more accurate and efficient generative error models have been proposed.
Double embedded processes based hidden Markov model and three-layered processes
based hidden Markov model have been developed. The two types of error profiles,
particularly the bit-level and packet-level error profiles were considered.
Thirdly, the deterministic process based generative models’ parameters have been
tuned or modified in order to generate packet error sequences rather than only bit
error sequences. Moreover, a modification procedure has been introduced to the same
models to enhance their generation process and to make them more desirable.
Fourthly, adaptive generative error models have been built in order to accommodate
widely used generative error models to different digital wireless channels with different
channel conditions. Only a few reference error profiles have been required in order to
produce additional error profiles in various conditions that are beneficial for the design
and performance evaluation of error control schemes and higher layer protocols.
Finally, the impact of the Hybrid Automatic Repeat reQuest (HARQ) on the burst
error statistics of physical layer error profiles has been studied. Moreover, a model that
can generate predicted error sequences with burst error statistics similar to those of
error profiles when HARQ is included has been proposed. This model is constructive
in predicting the behaviour of the HARQ in terms of a set of higher order statistics
rather than only predicting a first order statistic. Moreover, the whole physical layer
is replaced by adaptively generated error profiles in order to check the performance
of the HARQ protocol.
The developed generative error models as well as the developed adaptive generative
error models are expected to benefit future research towards the testing of many
digital components in the physical layer as well as the wireless protocols of the link
and transport layers for many existing and emerging systems in the field of wireless
communications
Evaluation of cross-layer reliability mechanisms for satellite digital multimedia broadcast
This paper presents a study of some reliability mechanisms which may be put at work in the context of Satellite Digital Multimedia Broadcasting (SDMB) to mobile devices such as handheld phones. These mechanisms include error correcting codes, interleaving at the physical layer, erasure codes at
intermediate layers and error concealment on the video decoder. The evaluation is made on a realistic satellite channel and takes into account practical constraints such as the maximum zapping time and the user mobility at several speeds. The evaluation is done by simulating different scenarii with complete protocol stacks. The simulations indicate that, under the assumptions taken here, the scenario using highly compressed video protected by erasure codes at intermediate layers seems to be the best solution
on this kind of channel
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