Advanced DSP Techniques for High-Capacity and Energy-Efficient Optical Fiber Communications

The rapid proliferation of the Internet has been driving communication networks closer and closer to their limits, while available bandwidth is disappearing due to an ever-increasing network load. Over the past decade, optical fiber communication technology has increased per fiber data rate from 10 Tb/s to exceeding 10 Pb/s. The major explosion came after the maturity of coherent detection and advanced digital signal processing (DSP). DSP has played a critical role in accommodating channel impairments mitigation, enabling advanced modulation formats for spectral efficiency transmission and realizing flexible bandwidth. This book aims to explore novel, advanced DSP techniques to enable multi-Tb/s/channel optical transmission to address pressing bandwidth and power-efficiency demands. It provides state-of-the-art advances and future perspectives of DSP as well

Adaptive implementation of turbo multi-user detection architecture

MULTI-access techniques have been adopted widely for communications in underwater acoustic channels, which present many challenges to the development of reliable and practical systems. In such an environment, the unpredictable and complex ocean conditions cause the acoustic waves to be affected by many factors such as limited bandwidth, large propagation losses, time variations and long latency, which limit the usefulness of such techniques. Additionally, multiple access interference (MAI) signals and poor estimation of the unknown channel parameters in the presence of limited training sequences are two of the major problems that degrade the performance of such technologies. In this thesis, two different single-element multi-access schemes, interleave division multiple access (IDMA) and code division multiple access (CDMA), employing decision feedback equalization (DFE) and soft Rake-based architectures, are proposed for multi-user underwater communication applications. By using either multiplexing pilots or continuous pilots, these adaptive turbo architectures with carrier phase tracking are jointly optimized based on the minimum mean square error (MMSE) criterion and adapted iteratively by exchanging soft information in terms of Log-Likelihood Ratio (LLR) estimates with the single-user’s channel decoders. The soft-Rake receivers utilize developed channel estimation and the detection is implemented using parallel interference cancellation (PIC) to remove MAI effects between users. These architectures are investigated and applied to simulated data and data obtained from realistic underwater communication trials using off-line processing of signals acquired during sea-trials in the North Sea. The results of different scenarios demonstrate the penalty in performance as the fading induces irreducible error rates that increase with channel delay spread and emphasize the benefits of using coherent direct adaptive receivers in such reverberant channels. The convergence behaviour of the detectors is evaluated using EXIT chart analyses and issues such as the adaptation parameters and their effects on the performance are also investigated. However, in some cases the receivers with partial knowledge of the interleavers’ patterns or codes can still achieve performance comparable to those with full knowledge. Furthermore, the thesis describes implementation issues of these algorithms using digital signal processors (DSPs), such as computational complexity and provides valuable guidelines for the design of real time underwater communication systems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Adaptive implementation of turbo multi-user detection architecture

MULTI-access techniques have been adopted widely for communications in underwater acoustic channels, which present many challenges to the development of reliable and practical systems. In such an environment, the unpredictable and complex ocean conditions cause the acoustic waves to be affected by many factors such as limited bandwidth, large propagation losses, time variations and long latency, which limit the usefulness of such techniques. Additionally, multiple access interference (MAI) signals and poor estimation of the unknown channel parameters in the presence of limited training sequences are two of the major problems that degrade the performance of such technologies. In this thesis, two different single-element multi-access schemes, interleave division multiple access (IDMA) and code division multiple access (CDMA), employing decision feedback equalization (DFE) and soft Rake-based architectures, are proposed for multi-user underwater communication applications. By using either multiplexing pilots or continuous pilots, these adaptive turbo architectures with carrier phase tracking are jointly optimized based on the minimum mean square error (MMSE) criterion and adapted iteratively by exchanging soft information in terms of Log-Likelihood Ratio (LLR) estimates with the single-user’s channel decoders. The soft-Rake receivers utilize developed channel estimation and the detection is implemented using parallel interference cancellation (PIC) to remove MAI effects between users. These architectures are investigated and applied to simulated data and data obtained from realistic underwater communication trials using off-line processing of signals acquired during sea-trials in the North Sea. The results of different scenarios demonstrate the penalty in performance as the fading induces irreducible error rates that increase with channel delay spread and emphasize the benefits of using coherent direct adaptive receivers in such reverberant channels. The convergence behaviour of the detectors is evaluated using EXIT chart analyses and issues such as the adaptation parameters and their effects on the performance are also investigated. However, in some cases the receivers with partial knowledge of the interleavers’ patterns or codes can still achieve performance comparable to those with full knowledge. Furthermore, the thesis describes implementation issues of these algorithms using digital signal processors (DSPs), such as computational complexity and provides valuable guidelines for the design of real time underwater communication systems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Blind detection in channels with intersymbol interference

In high speed digital transmission over bandlimited channels, one of the principal impairments, besides additive white Gaussian noise, is intersymbol interference. For unknown channels, adaptive equalization is used to mitigate the interference. Different types of equalizers were proposed in the literature such as linear, decision feedback equalizers and maximum likelihood sequence estimation. The transmitter embeds sequences with the data regularly to help the equalizer adapt to the unknown channel parameters. It is not always appropriate or feasible to send training sequences; in such cases, self adaptive or blind equalizers are used. The past ten years have witnessed an interest in the topic. Most of this interest, however, was devoted to linear equalization In this dissertation we concentrate on blind decision feedback equalization and blind maximum likelihood sequence estimation. We propose a new algorithm: the decorrelation algorithm, for controlling the blind decision feedback equalizer. We investigate properties such as convergence and probability of error. A new algorithm is also proposed for blind maximum likelihood sequence estimation. We use two trellises: one for the data and the other for the channel parameters. The Viterbi algorithm is used to search the two trellises for the best channel and data sequence estimates. We derive an upper bound for this scheme. We also address the problem of ill convergence of the constant modulus algorithm and propose a technique to improve its convergence. Using this technique, global convergence is guaranteed as long as the channel gain exceeds a certain critical value. The question of the Viterbi algorithm\u27s complexity is important for both conventional and blind maximum likelihood sequence estimation. Therefore, in this dissertation, the problem of reducing the complexity of the Viterbi algorithm is also addressed. We introduce the concept of state partitioning and use it to reduce the number of states of the Viterbi algorithm. This technique offers a better complexity/performance tradeoff than previously proposed techniques

Direct-form adaptive equalization for underwater acoustic communication

Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2012Adaptive equalization is an important aspect of communication systems in various environments. It is particularly important in underwater acoustic communication systems, as the channel has a long delay spread and is subject to the effects of time- varying multipath fading and Doppler spreading. The design of the adaptation algorithm has a profound influence on the performance of the system. In this thesis, we explore this aspect of the system. The emphasis of the work presented is on applying concepts from inference and decision theory and information theory to provide an approach to deriving and analyzing adaptation algorithms. Limited work has been done so far on rigorously devising adaptation algorithms to suit a particular situation, and the aim of this thesis is to concretize such efforts and possibly to provide a mathematical basis for expanding it to other applications. We derive an algorithm for the adaptation of the coefficients of an equalizer when the receiver has limited or no information about the transmitted symbols, which we term the Soft-Decision Directed Recursive Least Squares algorithm. We will demonstrate connections between the Expectation-Maximization (EM) algorithm and the Recursive Least Squares algorithm, and show how to derive a computationally efficient, purely recursive algorithm from the optimal EM algorithm. Then, we use our understanding of Markov processes to analyze the performance of the RLS algorithm in hard-decision directed mode, as well as of the Soft-Decision Directed RLS algorithm. We demonstrate scenarios in which the adaptation procedures fail catastrophically, and discuss why this happens. The lessons from the analysis guide us on the choice of models for the adaptation procedure. We then demonstrate how to use the algorithm derived in a practical system for underwater communication using turbo equalization. As the algorithm naturally incorporates soft information into the adaptation process, it becomes easy to fit it into a turbo equalization framework. We thus provide an instance of how to use the information of a turbo equalizer in an adaptation procedure, which has not been very well explored in the past. Experimental data is used to prove the value of the algorithm in a practical context.Support from the agencies that funded this research- the Academic Programs Office at WHOI and the Office of Naval Research (through ONR Grant #N00014-07-10738 and #N00014-10-10259)

UNDERWATER COMMUNICATIONS WITH ACOUSTIC STEGANOGRAPHY: RECOVERY ANALYSIS AND MODELING

In the modern warfare environment, communication is a cornerstone of combat competence. However, the increasing threat of communications-denied environments highlights the need for communications systems with low probability of intercept and detection. This is doubly true in the subsurface environment, where communications and sonar systems can reveal the tactical location of platforms and capabilities, subverting their covert mission set. A steganographic communication scheme that leverages existing technologies and unexpected data carriers is a feasible means of increasing assurance of communications, even in denied environments. This research works toward a covert communication system by determining and comparing novel symbol recovery schemes to extract data from a signal transmitted under a steganographic technique and interfered with by a simulated underwater acoustic channel. We apply techniques for reliably extracting imperceptible information from unremarkable acoustic events robust to the variability of the hostile operating environment. The system is evaluated based on performance metrics, such as transmission rate and bit error rate, and we show that our scheme is sufficient to conduct covert communications through acoustic transmissions, though we do not solve the problems of synchronization or equalization.Lieutenant, United States NavyApproved for public release. Distribution is unlimited

Adaptive Channel Equalization using Radial Basis Function Networks and MLP

One of the major practical problems in digital communication systems is channel distortion which causes errors due to intersymbol interference. Since the source signal is in general broadband, the various frequency components experience different steady state amplitude and phase changes as they pass through the channel, causing distortion in the received message. This distortion translates into errors in the received sequence. Our problem as communication engineers is to restore the transmitted sequence or, equivalently, to identify the inverse of the channel, given the observed sequence at the channel output. This task is accomplished by adaptive equalizers. Typically, adaptive equalizers used in digital communications require an initial training period, during which a known data sequence is transmitted. A replica of this sequence is made available at the receiver in proper synchronism with the transmitter, thereby making it possible for adjustments to be made to the equalizer coefficients in accordance with the adaptive filtering algorithm employed in the equalizer design. When the training is completed, the equalizer is switched to its decision directed mode. Decision feedback equalizers are used extensively in practical communication systems. They are more powerful than linear equalizers especially for severe inter-symbol interference (ISI) channels without as much noise enhancement as the linear equalizers. This thesis addresses the problem of adaptive channel equalization in environments where the interfering noise exhibits Gaussian behavior. In this thesis, radial basis function (RBF) network is used to implement DFE. Advantages and problems of this system are discussed and its results are then compared with DFE using multi layer perceptron net (MLP).Results indicate that the implemented system outperforms both the least-mean square(LMS) algorithm and MLP, given the same signal-to-noise ratio as it offers minimum mean square error. The learning rate of the implemented system is also faster than both LMS and the multilayered case

Review of Recent Trends

This work was partially supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Centre (CENTRO 2020) of the Portugal 2020 framework, through projects SOCA (CENTRO-01-0145-FEDER-000010) and ORCIP (CENTRO-01-0145-FEDER-022141). Fernando P. Guiomar acknowledges a fellowship from “la Caixa” Foundation (ID100010434), code LCF/BQ/PR20/11770015. Houda Harkat acknowledges the financial support of the Programmatic Financing of the CTS R&D Unit (UIDP/00066/2020).MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.publishersversionpublishe