abstract: The problem of cooperative radar and communications signaling is investigated. Each system typically considers the other system a source of interference. Consequently, the tradition is to have them operate in orthogonal frequency bands. By considering the radar and communications operations to be a single joint system, performance bounds on a receiver that observes communications and radar return in the same frequency allocation are derived. Bounds in performance of the joint system is measured in terms of data information rate for communications and radar estimation information rate for the radar. Inner bounds on performance are constructed. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2014

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.

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2005. / Includes bibliographical references. Also available in electronic version.

No description available.

Abstract Visual world is naturally correlated both spatially and temporally. The correlations are used in vision to enhance performance of neurons. For gaining maximal neural performance of the visual neurons, the experiments, from stimulus to the analysis, should be designed to take advantage of the correlations. In this thesis methods for generating and analyzing natural stimuli were examined by using computations and algorithms. For analyzing responses to natural stimuli in visual neurons, a method with only a few assumptions was developed for estimating information rate in long responses. The novel method gave a good agreement with Shannon information rate with linear system and Gaussian input but was able to handle also nonlinear processing and non-Gaussian data. Secondly, a computer controlled 3D virtual environment with a spherical screen was developed, with a large visual field. The image of the world was projected to the screen with a DLP projector, giving good enough temporal performance for insect vision research. A track-ball was used in closed loop experiments. Thirdly, properties of single photon (“bump”) information transfer at various light levels were investigated in cockroach photoreceptor with a coarse computational model. At dim light (< 10 ph/s), where single bump responses were visible, shot noise was dominant. At higher light levels latency distribution of the bump decreased the information rate, but amplitude distribution of bump did not have an effect. Fourthly, the contribution of K⁺ channels to information rate and energy consumption was investigated by creating a database of computation models with varying channel compositions. The information rate has a maximum as a function of mean conductance, which was a sum of the average K⁺ conductance and the leak conductance. This maximum was fine-tuned by the K⁺ channel composition, which had high so-called novel contribution and relatively low amount of other conductances.

In this paper, we use the forward recursion BCJR algorithm to estimate the symmetric information rate for Two Dimensional Magnetic Recording (TDMR) channels. In particular, we consider a TDMR read/write channel whose all components, including recording medium, write and readback processes are modeled in software. Since the primary source of noise in TDMR arises from irregularities in the recording medium and leads to highly colored and data-dependent jitter, the pattern dependent noise predictive (PDNP) algorithm is implemented to improve the accuracy and performance of SIR estimation. Furthermore, we study the performance gain of using the PDNP algorithm in SIR estimation through simulations over the Voronoi based media model for different TDMR channel configurations.

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.

Magnetic recording systems have reached a point where the grain size can no longer be reduced due to energy stability constraints. As a new magnetic recording paradigm, two-dimensional magnetic recording (TDMR) relies on sophisticated signal processing and coding algorithms, a much less expensive alternative to radically altering the media or the read/write head as required for the other technologies. Due to 1) the significant reduction of grains per bit, and 2) the aggressive shingled writing, TDMR faces several formidable challenges. Firstly, severe interference is introduced in both down-track and cross-track directions due to the read/write head dimensions. Secondly, reduction in the number of grains per bit results in variations of bit boundaries which consequently lead to data-dependent jitter noise. Moreover, the bit to grain ratio reduction will cause some bits not to be properly magnetized or to be overwritten which introduces write errors to the system. The nature of write and read processes in TDMR necessitates that the information storage be viewed as a two-dimensional (2D) system. The challenges in TDMR signal processing are 1) an accurate read channel model, 2) mitigating the effect of inter-track interference (ITI) and inter-symbol interference (ISI) by using an equalizer, 3) developing 2D modulation/error correcting codes matching the TDMR channel model, 4) design of truly 2D detectors, and 5) computing the lower bounds on capacity of TDMR channel. The work is concerned with several objectives in regard to the challenges in TDMR systems. 1. TDMR Channel Modeling: As one of the challenges of the project, the 2D Microcell model is introduced as a read channel model for TDMR. This model captures the data-dependent properties of the media noise and it is well suited in regard to detector design. In line with what has been already done in TDMR channel models, improvements can be made to tune the 2D Microcell model for different bit to grain densities. Furthermore, the 2D Microcell model can be modified to take into account dependency between adjacent microtrack borders positions. This assumption will lead to more accurate model in term of closeness to the Voronoi model. 2. Detector Design: The need for 2D detection is not unique to TDMR systems. However, it is still largely an open problem to develop detectors that are close to optimal maximum likelihood (ML) detection for the 2D case. As one of the important blocks of the TDMR system, the generalized belief propagation (GBP) detector is developed and introduced as a near ML detector. Furthermore, this detector is tuned to improve the performance for the TDMR channel model. 3. Channel Capacity Estimation: Two dimensional magnetic recording (TDMR) is a new paradigm in data storage which envisions densities up to 10 Tb/in² as a result of drastically reducing bit to grain ratio. In order to reach this goal aggressive write (shingled writing) and read process are used in TDMR. Kavcic et al. proposed a simple magnetic grain model called the granular tiling model which captures the essence of read/write process in TDMR. Capacity bounds for this model indicate that 0.6 user bit per grain densities are possible, however, previous attempt to reach capacities are not close to the channel capacity. We provide a truly two-dimensional detection scheme for the granular tiling model based on generalized belief propagation (GBP). Factor graph interpretation of the detection problem is provided and formulated in this section. Then, GBP is employed to compute marginal a posteriori probabilities for the constructed factor graph. Simulation results show huge improvements in detection. A lower bound on the mutual information rate (MIR) is also derived for this model based on GBP detector. Moreover, for the Voronoi channel model, the MIR is estimated for the case of constrained and unconstrained input. 4. Modulation Codes: Constrained codes also known as modulation codes are a key component in the digital magnetic recording systems. The constrained code forbids particular input data patterns which lead to some of the dominant error events or higher media noise. The goal of the dissertation in regard to modulation codes is to construct a 2D modulation code for the TDMR channel which improves the overall performance of the TDMR system. Furthermore, we implement an algorithm to estimate the capacity of the 2D modulation codes based on generalized belief propagation (GBP) algorithm. The capacity is also calculated in presence of white and colored noise which is the case for TDMR channel. 5. Joint Detection and Decoding Schemes: In data recording systems, a concatenated approach toward the constrained code and error-correcting code (ECC) is typically used and the decoding is done independently. We show the improvement in combining the decoding of the constrained code and the ECC using GBP algorithm. We consider the performance of a combined modulation constraints and the ECC on a binary-input additive white Gaussian noise (AWGN) channel (BIAWGNC) and also over one-dimensional (1D) and 2D ISI channels. We will show that combining the detection, demodulation and decoding results in a superior performance compared to concatenated schemes.

Les modulations à phase continue (CPMs) sont des méthodes de modulations robuste à la noncohérence du canal de propagation. Dans un contexte spatial, les CPM sont utilisées dans la chaîne de transmission de télémesure de la fusée. Depuis les années 70, la modulation la plus usitée dans les systèmes de télémesures est la modulation CPFSK continuous phase frequency shift keying filtrée. Historiquement, ce type de modulation est concaténée avec un code ReedSolomon (RS) afin d'améliorer le processus de décodage. Côté récepteur, les séquences CPM non-cohérentes sont démodulées par un détecteur Viterbi à sortie dure et un décodeur RS. Néanmoins, le gain du code RS n'est pas aussi satisfaisant que des techniques de codage moderne capables d'atteindre la limite de Shannon. Actualiser la chaîne de communication avec des codes atteignant la limite de Shannon tels que les codes en graphe creux, implique deremanier l’architecture du récepteur usuel pour un détecteur à sortie souple. Ainsi, on propose dans cette étude d' élaborer un détecteur treillis à sortie souple pour démoduler les séquences CPM non-cohérentes. Dans un deuxième temps, on concevra des schémas de pré-codages améliorant le comportement asymptotique du récepteur non-cohérent et dans une dernière étape on élabora des codes de parité à faible densité (LDPC) approchant la limite de Shannon. / Continuous phase modulations (CPM) are modulation methods robust to the non-coherency of propagation channels. In a space context, CPMs are used in the communication link between the rocket and the base stations. Since the 70's, the most popular telemetry modulation is the filtered continuous phase frequency shift keying (CPFSK). Traditionally, the CPFSK scheme isconcatenated with a Reed-Solomon (RS) code to enhance the decoding process. At the receiver side, the non-coherent CPM sequences are demodulated through a hard Viterbi detector and a RS decoder. However, the RS's coding gain is no more satisfactory when directly compared to modern coding schemes enable to reach the Shannon limit. Updating the communication link to capacity achieving codes, as sparse graph codes, implies to redesign the receiver architecture to soft detector. In that respect, we propose in this study to design a trellis-based soft detector to demodulate non-coherent CPM sequences. In a second part, we will elaborate precoding schemes to improve the asymptotic behaviour of the non-coherent receiver and in a last step we will build low density parity check codes approaching the Shannon limit.

La communication humaine vise principalement à transmettre de l'information par le biais de l'utilisation de langues. Plusieurs chercheurs ont soutenu l'hypothèse selon laquelle les limites de la capacité du canal de transmission amènent les locuteurs de chaque langue à encoder l'information de manière à obtenir une répartition uniforme de l'information entre les unités linguistiques utilisées. Dans nos recherches, la stratégie d'encodage de l'information en communication parlée est connue comme résultant de l'interaction complexe de facteurs neuro-cognitifs, linguistiques, et sociolinguistiques et nos travaux s'inscrivent donc dans le cadre des systèmes adaptatifs complexes. Plus précisément, cette thèse vise à mettre en évidence les tendances générales, translinguistiques, guidant l'encodage de l'information en tenant compte de la structure des langues à trois niveaux d'analyse (macrosystémique, mésosystémique, et microsystémique). Notre étude s'appuie ainsi sur des corpus oraux et textuels multilingues dans une double perspective quantitative et typologique. Dans cette recherche, la langue est définie comme un système adaptatif complexe, régulé par le phénomène d'auto-organisation, qui motive une première question de recherche : "Comment les langues présentant des débits de parole et des densités d'information variés transmettent-elles les informations en moyenne ?". L'hypothèse défendue propose que la densité moyenne d'information par unité linguistique varie au cours de la communication, mais est compensée par le débit moyen de la parole. Plusieurs notions issues de la théorie de l'information ont inspiré notre manière de quantifier le contenu de l'information et le résultat de la première étude montre que le débit moyen d'information (i.e. la quantité moyenne d'information transmise par seconde) est relativement stable dans une fourchette limitée de variation parmi les 18 langues étudiées. Alors que la première étude propose une analyse de l'auto-organisation au niveau macro- systémique, la deuxième étude porte sur des sous-systèmes linguistiques tels que la phonologie et la morphologie : elle relève donc d'une analyse au niveau mésosystémique. Elle porte sur les interactions entre les modules morphologique et phonologique en utilisant les mesures de la complexité linguistique de ces modules. L'objectif est de tester l'hypothèse d'uniformité de la complexité globale au niveau mésosystémique. Les résultats révèlent une corrélation négative entre la complexité morphologique et la complexité phonologique dans les 14 langues et vont dans le sens de l'hypothèse de l'uniformité de la complexité globale d'un point de vue typologique holistique. La troisième étude analyse l'organisation interne des sous-systèmes phonologiques au moyen de la notion de charge fonctionnelle (FL) au niveau microsystémique. Les contributions relatives des sous-systèmes phonologiques (segments, accents, et tons) sont évaluées quantitativement en estimant leur rôle dans les stratégies lexicales. Elles sont aussi comparées entre 2 langues tonales et 7 langues non-tonales. En outre, la distribution interne de la charge fonctionnelle à travers les sous-systèmes vocaliques et consonantiques est analysée de façon translinguistique dans les 9 langues. Les résultats soulignent l'importance du système tonal dans les distinctions lexicales et indiquent que seuls quelques contrastes dotés d'une charge fonctionnelle élevée sont observés dans les distributions inégales de charge fonctionnelle des sous-systèmes dans les 9 langues. Cette thèse présente donc des études empiriques et quantitatives réalisées à trois niveaux d'analyse, qui permettent de décrire des tendances générales parmi les langues et apportent des éclaircissements sur le phénomène d'auto-organisation. / The main goal of using language is to transmit information. One of the fundamental questions in linguistics concerns the way how information is conveyed by means of language in human communication. So far many researchers have supported the uniform information density (UID) hypothesis asserting that due to channel capacity, speakers tend to encode information strategically in order to achieve uniform rate of information conveyed per linguistic unit. In this study, it is assumed that the encoding strategy of information during speech communication results from complex interaction among neurocognitive, linguistic, and sociolinguistic factors in the framework of complex adaptive system. In particular, this thesis aims to find general cross-language tendencies of information encoding and language structure at three different levels of analysis (i.e. macrosystemic, mesosystemic, and microsystemic levels), by using multilingual parallel oral and text corpora from a quantitative and typological perspective. In this study, language is defined as a complex adaptive system which is regulated by the phenomenon of self-organization, where the first research question comes from : "How do languages exhibiting various speech rates and information density transmit information on average ?". It is assumed that the average information density per linguistic unit varies during communication but would be compensated by the average speech rate. Several notions of the Information theory are used as measures for quantifying information content and the result of the first study shows that the average information rate (i.e. the average amount of information conveyed per second) is relatively stable within a limited range of variation among the 18 languages studied. While the first study corresponds to an analysis of self-organization at the macrosystemic level, the second study deals with linguistic subsystems such as phonology and morphology and thus, covers an analysis at the mesosystemic level. It investigates interactions between phonological and morphological modules by means of the measures of linguistic complexity of these modules. The goal is to examine whether the equal complexity hypothesis holds true at the mesosystemic level. The result exhibits a negative correlation between morphological and phonological complexity in the 14 languages and supports the equal complexity hypothesis from a holistic typological perspective. The third study investigates the internal organization of phonological subsystems by means of functional load (FL) at the microsystemic level. The relative contributions of phonological subsystems (segments, stress, and tones) are quantitatively computed by estimating their role of lexical strategies and are compared in 2 tonal and 7 non-tonal languages. Furthermore, the internal FL distribution of vocalic and consonantal subsystems is analyzed cross-linguistically in the 9 languages. The result highlights the importance of tone system in lexical distinctions and indicates that only a few salient high-FL contrasts are observed in the uneven FL distributions of subsystems in the 9 languages. This thesis therefore attempts to provide empirical and quantitative studies at the three different levels of analysis, which exhibit general tendencies among languages and provide insight into the phenomenon of self-organization.