Secure Transmission in Cooperative Networks with Weak Eavesdroppers

In this letter, we propose a scheme to improve the secrecy rate of cooperative networks using Analog Network Coding (ANC). ANC mixes the signals in the air; the desired signal is then separated out, from the mixed signals, at the legitimate receiver using techniques like self interference subtraction and signal nulling, thereby achieving better secrecy rates. Assuming global channel state information, memoryless adversaries and the decode-and-forward strategy, we seek to maximize the average secrecy rate between the source and the destination, subject to an overall power budget. Then, exploiting the structure of the optimization problem, we compute its optimal solution. Finally, we use numerical evaluations to compare our scheme with the conventional approaches.

Novel Relay Selection Rules for Average Interference-Constrained Cognitive AF Relay Networks

Cooperative relaying combined with selection exploits spatial diversity to significantly improve the performance of interference-constrained secondary users in an underlay cognitive radio (CR) network. However, unlike conventional relaying, the state of the links between the relay and the primary receiver affects the choice of the relay. Further, while the optimal amplify-and-forward (AF) relay selection rule for underlay CR is well understood for the peak interference-constraint, this is not so for the less conservative average interference constraint. For the latter, we present three novel AF relay selection (RS) rules, namely, symbol error probability (SEP)-optimal, inverse-of-affine (IOA), and linear rules. We analyze the SEPs of the IOA and linear rules and also develop a novel, accurate approximation technique for analyzing the performance of AF relays. Extensive numerical results show that all the three rules outperform several RS rules proposed in the literature and generalize the conventional AF RS rule.

Essays on economics networks

This thesis belongs to the growing field of economic networks. In particular, we develop three essays in which we study the problem of bargaining, discrete choice representation, and pricing in the context of networked markets. Despite analyzing very different problems, the three essays share the common feature of making use of a network representation to describe the market of interest.

In Chapter 1 we present an analysis of bargaining in networked markets. We make two contributions. First, we characterize market equilibria in a bargaining model, and find that players' equilibrium payoffs coincide with their degree of centrality in the network, as measured by Bonacich's centrality measure. This characterization allows us to map, in a simple way, network structures into market equilibrium outcomes, so that payoffs dispersion in networked markets is driven by players' network positions. Second, we show that the market equilibrium for our model converges to the so called eigenvector centrality measure. We show that the economic condition for reaching convergence is that the players' discount factor goes to one. In particular, we show how the discount factor, the matching technology, and the network structure interact in a very particular way in order to see the eigenvector centrality as the limiting case of our market equilibrium.

We point out that the eigenvector approach is a way of finding the most central or relevant players in terms of the “global” structure of the network, and to pay less attention to patterns that are more “local”. Mathematically, the eigenvector centrality captures the relevance of players in the bargaining process, using the eigenvector associated to the largest eigenvalue of the adjacency matrix of a given network. Thus our result may be viewed as an economic justification of the eigenvector approach in the context of bargaining in networked markets.

As an application, we analyze the special case of seller-buyer networks, showing how our framework may be useful for analyzing price dispersion as a function of sellers and buyers' network positions.

Finally, in Chapter 3 we study the problem of price competition and free entry in networked markets subject to congestion effects. In many environments, such as communication networks in which network flows are allocated, or transportation networks in which traffic is directed through the underlying road architecture, congestion plays an important role. In particular, we consider a network with multiple origins and a common destination node, where each link is owned by a firm that sets prices in order to maximize profits, whereas users want to minimize the total cost they face, which is given by the congestion cost plus the prices set by firms. In this environment, we introduce the notion of Markovian traffic equilibrium to establish the existence and uniqueness of a pure strategy price equilibrium, without assuming that the demand functions are concave nor imposing particular functional forms for the latency functions. We derive explicit conditions to guarantee existence and uniqueness of equilibria. Given this existence and uniqueness result, we apply our framework to study entry decisions and welfare, and establish that in congested markets with free entry, the number of firms exceeds the social optimum.

Interacting single atoms with nanophotonics for chip-integrated quantum networks

Underlying matter and light are their building blocks of tiny atoms and photons. The ability to control and utilize matter-light interactions down to the elementary single atom and photon level at the nano-scale opens up exciting studies at the frontiers of science with applications in medicine, energy, and information technology. Of these, an intriguing front is the development of quantum networks where N >> 1 single-atom nodes are coherently linked by single photons, forming a collective quantum entity potentially capable of performing quantum computations and simulations. Here, a promising approach is to use optical cavities within the setting of cavity quantum electrodynamics (QED). However, since its first realization in 1992 by Kimble et al., current proof-of-principle experiments have involved just one or two conventional cavities. To move beyond to N >> 1 nodes, in this thesis we investigate a platform born from the marriage of cavity QED and nanophotonics, where single atoms at ~100 nm near the surfaces of lithographically fabricated dielectric photonic devices can strongly interact with single photons, on a chip. Particularly, we experimentally investigate three main types of devices: microtoroidal optical cavities, optical nanofibers, and nanophotonic crystal based structures. With a microtoroidal cavity, we realized a robust and efficient photon router where single photons are extracted from an incident coherent state of light and redirected to a separate output with high efficiency. We achieved strong single atom-photon coupling with atoms located ~100 nm near the surface of a microtoroid, which revealed important aspects in the atom dynamics and QED of these systems including atom-surface interaction effects. We present a method to achieve state-insensitive atom trapping near optical nanofibers, critical in nanophotonic systems where electromagnetic fields are tightly confined. We developed a system that fabricates high quality nanofibers with high controllability, with which we experimentally demonstrate a state-insensitive atom trap. We present initial investigations on nanophotonic crystal based structures as a platform for strong atom-photon interactions. The experimental advances and theoretical investigations carried out in this thesis provide a framework for and open the door to strong single atom-photon interactions using nanophotonics for chip-integrated quantum networks.

Fiber-optic integration and efficient detection schemes for optomechanical resonators

With the advent of the laser in the year 1960, the field of optics experienced a renaissance from what was considered to be a dull, solved subject to an active area of development, with applications and discoveries which are yet to be exhausted 55 years later. Light is now nearly ubiquitous not only in cutting-edge research in physics, chemistry, and biology, but also in modern technology and infrastructure. One quality of light, that of the imparted radiation pressure force upon reflection from an object, has attracted intense interest from researchers seeking to precisely monitor and control the motional degrees of freedom of an object using light. These optomechanical interactions have inspired myriad proposals, ranging from quantum memories and transducers in quantum information networks to precision metrology of classical forces. Alongside advances in micro- and nano-fabrication, the burgeoning field of optomechanics has yielded a class of highly engineered systems designed to produce strong interactions between light and motion.

Optomechanical crystals are one such system in which the patterning of periodic holes in thin dielectric films traps both light and sound waves to a micro-scale volume. These devices feature strong radiation pressure coupling between high-quality optical cavity modes and internal nanomechanical resonances. Whether for applications in the quantum or classical domain, the utility of optomechanical crystals hinges on the degree to which light radiating from the device, having interacted with mechanical motion, can be collected and detected in an experimental apparatus consisting of conventional optical components such as lenses and optical fibers. While several efficient methods of optical coupling exist to meet this task, most are unsuitable for the cryogenic or vacuum integration required for many applications. The first portion of this dissertation will detail the development of robust and efficient methods of optically coupling optomechanical resonators to optical fibers, with an emphasis on fabrication processes and optical characterization.

I will then proceed to describe a few experiments enabled by the fiber couplers. The first studies the performance of an optomechanical resonator as a precise sensor for continuous position measurement. The sensitivity of the measurement, limited by the detection efficiency of intracavity photons, is compared to the standard quantum limit imposed by the quantum properties of the laser probe light. The added noise of the measurement is seen to fall within a factor of 3 of the standard quantum limit, representing an order of magnitude improvement over previous experiments utilizing optomechanical crystals, and matching the performance of similar measurements in the microwave domain.

The next experiment uses single photon counting to detect individual phonon emission and absorption events within the nanomechanical oscillator. The scattering of laser light from mechanical motion produces correlated photon-phonon pairs, and detection of the emitted photon corresponds to an effective phonon counting scheme. In the process of scattering, the coherence properties of the mechanical oscillation are mapped onto the reflected light. Intensity interferometry of the reflected light then allows measurement of the temporal coherence of the acoustic field. These correlations are measured for a range of experimental conditions, including the optomechanical amplification of the mechanics to a self-oscillation regime, and comparisons are drawn to a laser system for phonons. Finally, prospects for using phonon counting and intensity interferometry to produce non-classical mechanical states are detailed following recent proposals in literature.

Non-conventional advertising on TV

Non-Conventional ways of advertising TV Networks and advertisers have come up with in order to tackle proliferation of the media and discretion of the viewer from the TV experience.

High-current adaptive impedance matching in narrowband power-line communication systems

This paper proposes a high current impedance matching method for narrowband power-line communication (NPLC) systems. The impedance of the power-line channel is time and location variant; therefore, coupling circuitry and the channel are not usually matched. This not only results in poor signal integrity at the receiving end, but also leads to a higher transmission power requirement to secure the communication process. To offset this negative effect, a high-current adaptive impedance circuit to enable impedance matching in power-line networks is reported. The approach taken is to match the channel impedance of N-PLC systems is based on the General Impedance Converter (GIC). In order to achieve high current a special coupler in which the inductive impedance can be altered by adjusting a microcontroller controlled digital resistor is demonstrated. It is shown that the coupler works well with heavy load current in power line networks. It works in both low and high transmitting current modes, a current as high as 760 mA has been obtained. Besides, compared with other adaptive impedance couplers, the advantages include higher matching resolution and a simple control interface. Experimental results are presented to demonstrate the operation of the coupler. © 2011 IEEE.

Transmission performance of adaptively modulated optical OFDM modems using subcarrier modulation over SMF IMDD links for access and metropolitan area networks.

Detailed investigations are undertaken, for the first time, of the transmission performance of recently proposed novel Adaptively Modulated Optical OFDM (AMOOFDM) modems using Subcarrier Modulation (AMOOFDM-SCM) in single-channel, SMF-based IMDD links without optical amplification and chromatic dispersion compensation. The cross-talk effect induced by beatings among subcarriers of various types is a crucial factor limiting the maximum achievable AMOOFDM-SCM performance. By applying single sideband modulation and/or spectral gapping to AMOOFDM-SCM, three AMOOFDM-SCM designs of varying complexity are proposed, which achieve >60Gb/s signal transmission over 20 km, 40 km and 60 km. Such performances are >1.5 times higher than those supported by conventional AMOOFDM modems.

Robust pairwise matching of interest points with complex wavelets

We present a matching framework to find robust correspondences between image features by considering the spatial information between them. To achieve this, we define spatial constraints on the relative orientation and change in scale between pairs of features. A pairwise similarity score, which measures the similarity of features based on these spatial constraints, is considered. The pairwise similarity scores for all pairs of candidate correspondences are then accumulated in a 2-D similarity space. Robust correspondences can be found by searching for clusters in the similarity space, since actual correspondences are expected to form clusters that satisfy similar spatial constraints in this space. As it is difficult to achieve reliable and consistent estimates of scale and orientation, an additional contribution is that these parameters do not need to be determined at the interest point detection stage, which differs from conventional methods. Polar matching of dual-tree complex wavelet transform features is used, since it fits naturally into the framework with the defined spatial constraints. Our tests show that the proposed framework is capable of producing robust correspondences with higher correspondence ratios and reasonable computational efficiency, compared to other well-known algorithms. © 1992-2012 IEEE.

Quantum key distribution for 10 Gb/s dense wavelength division multiplexing networks

We demonstrate quantum key distribution (QKD) with bidirectional 10 Gb/s classical data channels in a single fiber using dense wavelength division multiplexing. Record secure key rates of 2.38 Mbps and fiber distances up to 70km are achieved. Data channels are simultaneously monitored for error-free operation. The robustness of QKD is further demonstrated with a secure key rate of 445 kbps over 25km, obtained in the presence of data lasers launching conventional 0 dBm power. We discuss the fundamental limit for the QKD performance in the multiplexing environment. © 2014 AIP Publishing LLC.

Model-based compressive Harmonic-Aware Matching Pursuit: An evaluation

This paper addresses devising a reliable model-based Harmonic-Aware Matching Pursuit (HAMP) for reconstructing sparse harmonic signals from their compressed samples. The performance guarantees of HAMP are provided; they illustrate that the introduced HAMP requires less data measurements and has lower computational cost compared with other greedy techniques. The complexity of formulating a structured sparse approximation algorithm is highlighted and the inapplicability of the conventional thresholding operator to the harmonic signal model is demonstrated. The harmonic sequential deletion algorithm is subsequently proposed and other sparse approximation methods are evaluated. The superior performance of HAMP is depicted in the presented experiments. © 2013 IEEE.

Research on color matching of LED backlight for large-color-gamut LCD application - art. no. 68410Y

Comparing with the conventional CCFL (Cold Cathode Fluorescent Lamp) backlight, three-basic-color LEDs backlight has some advantages such as good color reproduction, long life and lead free etc. Theoretically, the color gamut is determined by x, y coordinates of the three basic colors in CIE chromaticity diagram, and the x, y coordinates of each basic color can derived from the relative spectrum distribution (RSD) of the LED. In this paper, the red, green and blue LEDs' RSD models are established to calculate and analyze the color gamut of a backlight. By simulating those models, the relationships that the color gamut of a LED backlight varies with each color are analyzed, and the optimum combination of three colors is obtained within the given wavelengths ranges. Moreover, the combinations of three colors for the gamut of 115% NTSC and 110% NTSC are plotted in pictures, respectively.

Cancer classification based on direction-basis-function neural networks

Automatic molecular classification of cancer based on DNA microarray has many advantages over conventional classification based on morphological appearance of the tumor. Using artificial neural networks is a general approach for automatic classification. In this paper, Direction-Basis-Function neuron and Priority-Ordered algorithm are applied to neural networks. And the leukemia gene expression dataset is used as an example to testify the classifier. The result of our method is compared to that of SVM. It shows that our method makes a better performance than SVM.

Fast Locking and High Accurate Current Matching Phase-Locked Loop

In this paper, a charge-pump based phase-locked loop (CPLL) that can achieve fast locking and tiny deviation is proposed and analyzed. A lock-aid circuit is added to achieve fast locking of the CPLL. Besides, a novel differential charge pump which has good current matching characteristics and a PFD with delay cell has been used in this PLL. The proposed PILL circuit is designed based on the 0.35um 2P4M CMOS process with 3.3V/5V supply voltage. HSPICE simulation shows that the lock time of the proposed CPLL can be reduced by over 72% in comparison to the conventional PILL and its charge pump sink and source current mismatch is only 0.008%.

A power-saving scheme for IEEE 802.11 Ad hoc networks

In the Wireless Local Area Networks (WLANs), the terminals are often powered by battery, so the power-saving performance of the wireless network card is a very important issue. For IEEE 802.11 Ad hoc networks, a power-saving scheme is presented in Medium Access Control (MAC) layer to reduce the power consumption by allowing the nodes enter into the sleep mode, but the scheme is based on Time-Drive Scheme (TDS) whose power-saving efficiency becomes lower and lower with the network load increasing. This paper presented a novel energy-saving mechanism, called as Hybrid-Drive Scheme (HDS), which introduces into a Message.-Drive Scheme (MDS) and combines MDS with the conventional TDS. The MDS, could obtain high efficiency when the load is heavy; meanwhile the TDS has high efficiency when the network load is small. The analysis shows that the proposed HDS could obtain high energy-efficiency whether the network load is light or heavy and have higher energy-saving efficiency than conventional scheme in the IEEE 802.11 standard.