Investigation of coding and equalization for the digital HDTV terrestrial broadcast channel

Includes bibliographical references (p. 241-248).Supported by the Advanced Telecommunications Research Program.Julien J. Nicolas

Analysis of OFDM-based intensity modulation techniques for optical wireless communications

Optical wireless communication (OWC) is a promising alternative to radio frequency (RF) communication with a significantly larger and unregulated spectrum. Impairments in the physical layer, such as the non-linear transfer characteristic of the transmitter, the dispersive optical wireless channel and the additive white Gaussian noise (AWGN) at the receiver, reduce the capacity of the OWC system. Single-carrier multi-level pulse position modulation (M-PPM) and multilevel pulse amplitude modulation (M-PAM) suffer from inter-symbol interference (ISI) in the dispersive channel which reduces their capacity even after channel equalization. Multi-carrier modulation such as optical orthogonal frequency division multiplexing (O-OFDM) with multilevel quadrature amplitude modulation (M-QAM) is known to maximize the channel capacity through bit and power loading. There are two general signal structures: bipolar Gaussian signal with a direct current (DC) bias, i.e. DC-biased O-OFDM (DCO-OFDM), or unipolar half- Gaussian signal, employing only the odd subcarriers, i.e. asymmetrically clipped O-OFDM (ACO-OFDM). In this thesis, the signal distortion from the transmitter nonlinearity is minimized through pre-distortion, optimum signal scaling and DC-biasing. The optical front-ends impose minimum, average and maximum optical power constraints, as well as an average electrical power constraint, on the information-carrying signals. In this thesis, the optical signals are conditioned within these constraints through optimum signal scaling and DC-biasing. The presented analysis of the optical-to-electrical (O/E) conversion enables the derivation of the electrical signal-to-noise ratio (SNR) at the receiver, including or excluding the additional DC bias power, which is translated into bit-error rate (BER) performance. In addition, a generalized piecewise polynomial model for the non-linear transfer characteristic of the transmitter is proposed. The non-linear distortion in O-OFDM is translated by means of the Bussgang theorem and the central limit theorem (CLT) into attenuation of the data-carrying subcarriers at the receiver plus zero-mean complex-valued Gaussian noise. The attenuation factor and the variance of the non-linear distortion noise are derived in closed form, and they are accounted towards the received electrical SNR. Through pre-distortion with the inverse of the proposed piecewise polynomial function, the linear dynamic range of the transmitter is maximized, reducing the non-linear distortion to double-sided signal clipping. Finally, the OWC schemes are compared in terms of spectral efficiency and electrical SNR requirement as the signal bandwidth exceeds the coherence bandwidth of the optical wireless channel for a practical 10 dB linear dynamic range. Through optimum signal scaling and DCbiasing, DCO-OFDM is found to achieve the highest spectral efficiency for a target SNR, neglecting the additional DC bias power. When the DC bias power is counted towards the signal power, DCO-OFDM outperforms PAM with linear equalization, approaching the performance of the more computationally intensive PAM with non-linear equalization. In addition, the average optical power in O-OFDM is varied over dynamic ranges of 10 dB, 20 dB and 30 dB. When the additional DC bias power is neglected, DCO-OFDM is shown to achieve the Shannon capacity, while ACO-OFDM exhibits a 3 dB gap which grows with higher SNR targets. When the DC bias power is included, DCO-OFDM outperforms ACO-OFDM for the majority of average optical power levels with the increase of the SNR target or the dynamic range

Maximum likelihood sequence estimation from the lattice viewpoint.

by Mow Wai Ho.Thesis (M.Phil.)--Chinese University of Hong Kong, 1991.Bibliographies: leaves 98-104.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Channel Model and Other Basic Assumptions --- p.5Chapter 1.2 --- Complexity Measure --- p.8Chapter 1.3 --- Maximum Likelihood Sequence Estimator --- p.9Chapter 1.4 --- The Viterbi Algorithm ´ؤ An Implementation of MLSE --- p.11Chapter 1.5 --- Error Performance of the Viterbi Algorithm --- p.14Chapter 1.6 --- Suboptimal Viterbi-like Algorithms --- p.17Chapter 1.7 --- Trends of Digital Transmission and MLSE --- p.19Chapter 2 --- New Formulation of MLSE --- p.21Chapter 2.1 --- The Truncated Viterbi Algorithm --- p.21Chapter 2.2 --- Choice of Truncation Depth --- p.23Chapter 2.3 --- Decomposition of MLSE --- p.26Chapter 2.4 --- Lattice Interpretation of MLSE --- p.29Chapter 3 --- The Closest Vector Problem --- p.34Chapter 3.1 --- Basic Definitions and Facts About Lattices --- p.37Chapter 3.2 --- Lattice Basis Reduction --- p.40Chapter 3.2.1 --- Weakly Reduced Bases --- p.41Chapter 3.2.2 --- Derivation of the LLL-reduction Algorithm --- p.43Chapter 3.2.3 --- Improved Algorithm for LLL-reduced Bases --- p.52Chapter 3.3 --- Enumeration Algorithm --- p.57Chapter 3.3.1 --- Lattice and Isometric Mapping --- p.58Chapter 3.3.2 --- Enumerating Points in a Parallelepiped --- p.59Chapter 3.3.3 --- Enumerating Points in a Cube --- p.63Chapter 3.3.4 --- Enumerating Points in a Sphere --- p.64Chapter 3.3.5 --- Comparisons of Three Enumeration Algorithms --- p.66Chapter 3.3.6 --- Improved Enumeration Algorithm for the CVP and the SVP --- p.67Chapter 3.4 --- CVP Algorithm Using the Reduce-and-Enumerate Approach --- p.71Chapter 3.5 --- CVP Algorithm with Improved Average-Case Complexity --- p.72Chapter 3.5.1 --- CVP Algorithm for Norms Induced by Orthogonalization --- p.73Chapter 3.5.2 --- Improved CVP Algorithm using Norm Approximation --- p.76Chapter 4 --- MLSE Algorithm --- p.79Chapter 4.1 --- MLSE Algorithm for PAM Systems --- p.79Chapter 4.2 --- MLSE Algorithm for Unimodular Channel --- p.82Chapter 4.3 --- Reducing the Boundary Effect for PAM Systems --- p.83Chapter 4.4 --- Simulation Results and Performance Investigation for Example Channels --- p.86Chapter 4.5 --- MLSE Algorithm for Other Lattice-Type Modulation Systems --- p.91Chapter 4.6 --- Some Potential Applications --- p.92Chapter 4.7 --- Further Research Directions --- p.94Chapter 5 --- Conclusion --- p.96Bibliography --- p.10

Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years

Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions

MIMO Systems

In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Estimation and detection techniques for doubly-selective channels in wireless communications

A fundamental problem in communications is the estimation of the channel. The signal transmitted through a communications channel undergoes distortions so that it is often received in an unrecognizable form at the receiver. The receiver must expend significant signal processing effort in order to be able to decode the transmit signal from this received signal. This signal processing requires knowledge of how the channel distorts the transmit signal, i.e. channel knowledge. To maintain a reliable link, the channel must be estimated and tracked by the receiver. The estimation of the channel at the receiver often proceeds by transmission of a signal called the 'pilot' which is known a priori to the receiver. The receiver forms its estimate of the transmitted signal based on how this known signal is distorted by the channel, i.e. it estimates the channel from the received signal and the pilot. This design of the pilot is a function of the modulation, the type of training and the channel. [Continues.

Adaptive Equalisation for Impulsive Noise Environments

This thesis addresses the problem of adaptive channel equalisation in environments where the interfering noise exhibits non–Gaussian behaviour due to impulsive phenomena. The family of alpha-stable distributions has proved to be a suitable and flexible tool for the modelling of signals with impulsive nature. However,non–Gaussian alpha–stable signals have infinite variance, and signal processing techniques based on second order moments are meaningless in such environments. In order to exploit the flexibility of the stable family and still take advantage of the existing signal processing tools, a novel framework for the integration of the stable model in a communications context is proposed, based on a finite dynamic range receiver. The performance of traditional signal processing algorithms designed under the Gaussian assumption may degrade seriously in impulsive environments. When this degradation cannot be tolerated, the traditional signal processing methods must be revisited and redesigned taking into account the non–Gaussian noise statistics. In this direction, the optimum feed–forward and decision feedback Bayesian symbol–by–symbol equalisers for stable noise environments are derived. Then, new analytical tools for the evaluation of systems in infinite variance environments are presented. For the centers estimation of the proposed Bayesian equaliser, a unified framework for a family of robust recursive linear estimation techniques is presented and the underlying relationships between them are identified. Furthermore, the direct clustering technique is studied and robust variants of the existing algorithms are proposed. A novel clustering algorithm is also derived based on robust location estimation. The problem of estimating the stable parameters has been addressed in the literature and a variety of algorithms can be found. Some of these algorithms are assessed in terms of efficiency, simplicity and performance and the most suitable is chosen for the equalisation problem. All the building components of an adaptive Bayesian equaliser are then put together and the performance of the equaliser is evaluated experimentally. The simulation results suggest that the proposed adaptive equaliser offers a significant performance benefit compared with a traditional equaliser, designed under the Gaussian assumption. The implementation of the proposed Bayesian equaliser is simple but the computational complexity can be unaffordable. However, this thesis proposes certain approximations which enable the computationally efficient implementation of the optimum equaliser with negligible loss in performance

Time diversity solutions to cope with lost packets

A dissertation submitted to Departamento de Engenharia Electrotécnica of Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Engenharia Electrotécnica e de ComputadoresModern broadband wireless systems require high throughputs and can also have very high Quality-of-Service (QoS) requirements, namely small error rates and short delays. A high spectral efficiency is needed to meet these requirements. Lost packets, either due to errors or collisions, are usually discarded and need to be retransmitted, leading to performance degradation. An alternative to simple retransmission that can improve both power and spectral efficiency is to combine the signals associated to different transmission attempts. This thesis analyses two time diversity approaches to cope with lost packets that are relatively similar at physical layer but handle different packet loss causes. The first is a lowcomplexity Diversity-Combining (DC) Automatic Repeat reQuest (ARQ) scheme employed in a Time Division Multiple Access (TDMA) architecture, adapted for channels dedicated to a single user. The second is a Network-assisted Diversity Multiple Access (NDMA) scheme, which is a multi-packet detection approach able to separate multiple mobile terminals transmitting simultaneously in one slot using temporal diversity. This thesis combines these techniques with Single Carrier with Frequency Division Equalizer (SC-FDE) systems, which are widely recognized as the best candidates for the uplink of future broadband wireless systems. It proposes a new NDMA scheme capable of handling more Mobile Terminals (MTs) than the user separation capacity of the receiver. This thesis also proposes a set of analytical tools that can be used to analyse and optimize the use of these two systems. These tools are then employed to compare both approaches in terms of error rate, throughput and delay performances, and taking the implementation complexity into consideration. Finally, it is shown that both approaches represent viable solutions for future broadband wireless communications complementing each other.Fundação para a Ciência e Tecnologia - PhD grant(SFRH/BD/41515/2007); CTS multi-annual funding project PEst-OE/EEI/UI0066/2011, IT pluri-annual funding project PEst-OE/EEI/LA0008/2011, U-BOAT project PTDC/EEATEL/ 67066/2006, MPSat project PTDC/EEA-TEL/099074/2008 and OPPORTUNISTICCR project PTDC/EEA-TEL/115981/200