A permutation coding and OFDM-MFSK modulation scheme for power-line communication

Power-line communication offers a networking communication over existing power lines and finds important applications in smart grid, home and business automation and automatic meter reading. However, the power-line channel is one of the harshest known communication channels currently in use and it requires robust forward error correction techniques. Powerful decoding algorithms tend to be complex and increase latency while robust modulation schemes offer lower data rates and reduced spectral efficiency. The presented research is a frequency domain error-correcting scheme that extends the existing narrowband power-line communication forward error correction concatenated scheme of Reed-Solomon and Convolutional codes in the OFDM framework. It introduces a combination of M-ary phase shift keying as an OFDM subcarrier modulation scheme and a permutation sequence encoding between subcarriers to combat narrowband interference and carrier frequency offsets by introducing frequency diversity. The scheme offers improved BER performance over OFDM and OFDM-MFSK in high narrowband disturbance and impulse noise probability channels and improves the performance of OFDM in the presence of carrier frequency offsets

Automatic classification of digital communication signal modulations

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityAutomatic modulation classification detects the modulation type of received communication signals. It has important applications in military scenarios to facilitate jamming, intelligence, surveillance, and threat analysis. The renewed interest from civilian scenes has been fuelled by the development of intelligent communications systems such as cognitive radio and software defined radio. More specifically, it is complementary to adaptive modulation and coding where a modulation can be deployed from a set of candidates according to the channel condition and system specification for improved spectrum efficiency and link reliability. In this research, we started by improving some existing methods for higher classification accuracy but lower complexity. Machine learning techniques such as k-nearest neighbour and support vector machine have been adopted for simplified decision making using known features. Logistic regression, genetic algorithm and genetic programming have been incorporated for improved classification performance through feature selection and combination. We have also developed a new distribution test based classifier which is tailored for modulation classification with the inspiration from Kolmogorov-Smirnov test. The proposed classifier is shown to have improved accuracy and robustness over the standard distribution test. For blind classification in imperfect channels, we developed the combination of minimum distance centroid estimator and non-parametric likelihood function for blind modulation classification without the prior knowledge on channel noise. The centroid estimator provides joint estimation of channel gain and carrier phase o set where both can be compensated in the following nonparametric likelihood function. The non-parametric likelihood function, in the meantime, provide likelihood evaluation without a specifically assumed noise model. The combination has shown to have higher robustness when different noise types are considered. To push modulation classification techniques into a more timely setting, we also developed the principle for blind classification in MIMO systems. The classification is achieved through expectation maximization channel estimation and likelihood based classification. Early results have shown bright prospect for the method while more work is needed to further optimize the method and to provide a more thorough validation.School of Engineering and Design Brunel University London, the Faculty of Engineering University of Liverpool, and the University of Liverpool Graduate Association (Hong Kong)

Advanced Coding And Modulation For Ultra-wideband And Impulsive Noises

The ever-growing demand for higher quality and faster multimedia content delivery over short distances in home environments drives the quest for higher data rates in wireless personal area networks (WPANs). One of the candidate IEEE 802.15.3a WPAN proposals support data rates up to 480 Mbps by using punctured convolutional codes with quadrature phase shift keying (QPSK) modulation for a multi-band orthogonal frequency-division multiplexing (MB-OFDM) system over ultra wideband (UWB) channels. In the first part of this dissertation, we combine more powerful near-Shannon-limit turbo codes with bandwidth efficient trellis coded modulation, i.e., turbo trellis coded modulation (TTCM), to further improve the data rates up to 1.2 Gbps. A modified iterative decoder for this TTCM coded MB-OFDM system is proposed and its bit error rate performance under various impulsive noises over both Gaussian and UWB channel is extensively investigated, especially in mismatched scenarios. A robust decoder which is immune to noise mismatch is provided based on comparison of impulsive noises in time domain and frequency domain. The accurate estimation of the dynamic noise model could be very difficult or impossible at the receiver, thus a significant performance degradation may occur due to noise mismatch. In the second part of this dissertation, we prove that the minimax decoder in \cite, which instead of minimizing the average bit error probability aims at minimizing the worst bit error probability, is optimal and robust to certain noise model with unknown prior probabilities in two and higher dimensions. Besides turbo codes, another kind of error correcting codes which approach the Shannon capacity is low-density parity-check (LDPC) codes. In the last part of this dissertation, we extend the density evolution method for sum-product decoding using mismatched noises. We will prove that as long as the true noise type and the estimated noise type used in the decoder are both binary-input memoryless output symmetric channels, the output from mismatched log-likelihood ratio (LLR) computation is also symmetric. We will show the Shannon capacity can be evaluated for mismatched LLR computation and it can be reduced if the mismatched LLR computation is not an one-to-one mapping function. We will derive the Shannon capacity, threshold and stable condition of LDPC codes for mismatched BIAWGN and BIL noise types. The results show that the noise variance estimation errors will not affect the Shannon capacity and stable condition, but the errors do reduce the threshold. The mismatch in noise type will only reduce Shannon capacity when LLR computation is based on BIL

Design and Analysis of OFDM System for Powerline Based Communication

Research on digital communication systems has been greatly developed in the past few years and offers a high quality of transmission in both wired and wireless communication environments. Coupled with advances in new modulation techniques, Orthogonal Frequency Division Multiplexing (OFDM) is a well-known digital multicarrier communication technique and one of the best methods of digital data transmission over a limited bandwidth. The main aim of this research is to design an OFDM modem for powerline-based communication in order to propose and examine a novel approach in comparing the different modulation order, different modulation type, application of Forward Error Correction (FEC) scheme and also application of different noise types and applying them to the two modelled channels, Additive White Gaussian Noise (AWGN) and Powerline modelled channel. This is an attempt to understand and recognise the most suitable technique for the transmission of message or image within a communication system. In doing so, MATLAB and embedded Digital Signal Processing (DSP) systems are used to simulate the operation of virtual transmitter and receiver. The simulation results presented in this project suggest that lower order modulation formats (Binary Phase Shift Keying (BPSK) and 4-Quadrature Amplitude Modulation (QAM)), are the most preferred modulation techniques (in both type and order) for their considerable performance. The results also indicated that, Convolutional Channel Encoding (CCE)-Soft and Block Channel Encoding (BCE)-Soft are by far the best encoding techniques (in FEC type) for their best performance in error detection and correction. Indeed, applying these techniques to the two modelled channels has proven very successful and will be accounted as a novel approach for the transmission of message or image within a powerline based communication system

Band sharing and satellite diversity techniques for CDMA.

High levels of interference between satellite constellation systems, fading and shadowing are a major problem for the successful performance of communication systems using the allocated L/S frequency bands for Non-Geostationary Earth Orbit (NGEO) satellites. As free spectrum is nonexistent, new systems wishing to operate in this band must co-exist with other users, both satellite and terrestrial. This research is mainly concerned with two subjects. Firstly, band sharing between different systems Code Division Multiple Access (CDMA) and Time Division Multiple Access (TDMA) has been evaluated for maximizing capacity and optimising efficiency of using the spectrum available. For the case of widened channel bandwidth of the CDMA channel, the overlapping was tested under different degrees of channel overlap and different orders of filters. The best result shows that at the optimum degree of channel overlap, capacity increases by up to 21%. For the case of fixed channel bandwidth, the optimum overlapping between CDMA systems depends on the filtering Roll-off factor and achieves an improvement of the spectrum efficiency of up to 13.4%. Also, for a number of narrowband signal users sharing a CDMA channel, the best location of narrowband signals to share spectrum with a CDMA system was found to be at the edge of the CDMA channel. Simulation models have been constructed and developed which show the combination of DS- CDMA techniques, forward error correction (FEC) code techniques and satellite diversity with Rake receiver for improving performance of interference, fading and shadowing under different environments. Voice activity factor has been considered to reduce the effect of multiple access interference (MAI). The results have shown that satellite diversity has a significant effect on the system performance and satellite diversity gain achieves an improvement up to 6dB. Further improvements have been achieved by including concatenated codes to provide different BER for different services. Sharing the frequency band between a number of Low Earth Orbit (LEO) satellite constellation systems is feasible and very useful but only for a limited number of LEOS satellite CDMA based constellations. Furthermore, satellite diversity is an essential factor to achieve a satisfactory level of service availability, especially for urban and suburban environments

Techniques of detection, estimation and coding for fading channels

The thesis describes techniques of detection, coding and estimation, for use in high speed serial modems operating over fading channels such as HF radio and land mobile radio links. The performance of the various systems that employ the above techniques are obtained via computer simulation tests. A review of the characteristics of HF radio channels is first presented, leading to the development of an appropriate channel model which imposes Rayleigh fading on the transmitted signal. Detection processes for a 4.8 kbit/s HF radio modem are then discussed, the emphasis, here, being on variants of the maximum likelihood detector that is implemented by the Viterbi algorithm. The performance of these detectors are compared with that of a nonlinear equalizer operating under the same conditions, and the detector which offers the best compromise between performance and complexity is chosen for further tests. Forward error correction, in the form of trellis coded modulation, is next introduced. An appropriate 8-PSK coded modulation scheme is discussed, and its operation over the above mentioned HF radio modem is evaluated. Performance comparisons are made of the coded and uncoded systems. Channel estimation techniques for fast fading channels akin to cellular land mobile radio links, are next discussed. A suitable model for a fast fading channel is developed, and some novel estimators are tested over this channel. Computer simulation tests are also used to study the feasibility of the simultaneous transmission of two 4-level QAM signals occupying the same frequency band, when each of these signals are transmitted at 24 kbit/s over two independently fading channels, to a single receiver. A novel combined detector/estimator is developed for this purpose. Finally, the performance of the complete 4.8 kbit/s HF radio modem is obtained, when all the functions of detection, estimation and prefiltering are present, where the prefilter and associated processor use a recently developed technique for the adjustment of its tap gains and for the estimation of the minimum phase sampled impulse response

Sequential Monte Carlo Methods With Applications To Communication Channels

Estimating the state of a system from noisy measurements is a problem which arises in a variety of scientific and industrial areas which include signal processing, communications, statistics and econometrics. Recursive filtering is one way to achieve this by incorporating noisy observations as they become available with prior knowledge of the system model. Bayesian methods provide a general framework for dynamic state estimation problems. The central idea behind this recursive Bayesian estimation is computing the probability density function of the state vector of the system conditioned on the measurements. However, the optimal solution to this problem is often intractable because it requires high-dimensional integration. Although we can use the Kalman lter in the case of a linear state space model with Gaussian noise, this method is not optimum for a non-linear and non-Gaussian system model. There are many new methods of filtering for the general case. The main emphasis of this thesis is on one such recently developed filter, the particle lter [2,3,6]. In this thesis, a detailed introduction to particle filters is provided as well as some guidelines for the efficient implementation of the particle lter. The application of particle lters to various communication channels like detection of symbols over the channels, capacity calculation of the channel are discussed

Proceedings of the Mobile Satellite Conference

A satellite-based mobile communications system provides voice and data communications to mobile users over a vast geographic area. The technical and service characteristics of mobile satellite systems (MSSs) are presented and form an in-depth view of the current MSS status at the system and subsystem levels. Major emphasis is placed on developments, current and future, in the following critical MSS technology areas: vehicle antennas, networking, modulation and coding, speech compression, channel characterization, space segment technology and MSS experiments. Also, the mobile satellite communications needs of government agencies are addressed, as is the MSS potential to fulfill them