Showing papers by "Bell Labs published in 2013"

Energy and Spectral Efficiency of Very Large Multiuser MIMO Systems

Abstract: A multiplicity of autonomous terminals simultaneously transmits data streams to a compact array of antennas. The array uses imperfect channel-state information derived from transmitted pilots to extract the individual data streams. The power radiated by the terminals can be made inversely proportional to the square-root of the number of base station antennas with no reduction in performance. In contrast if perfect channel-state information were available the power could be made inversely proportional to the number of antennas. Lower capacity bounds for maximum-ratio combining (MRC), zero-forcing (ZF) and minimum mean-square error (MMSE) detection are derived. An MRC receiver normally performs worse than ZF and MMSE. However as power levels are reduced, the cross-talk introduced by the inferior maximum-ratio receiver eventually falls below the noise level and this simple receiver becomes a viable option. The tradeoff between the energy efficiency (as measured in bits/J) and spectral efficiency (as measured in bits/channel use/terminal) is quantified for a channel model that includes small-scale fading but not large-scale fading. It is shown that the use of moderately large antenna arrays can improve the spectral and energy efficiency with orders of magnitude compared to a single-antenna system.

Massive MIMO in the UL/DL of Cellular Networks: How Many Antennas Do We Need?

Abstract: We consider the uplink (UL) and downlink (DL) of non-cooperative multi-cellular time-division duplexing (TDD) systems, assuming that the number N of antennas per base station (BS) and the number K of user terminals (UTs) per cell are large. Our system model accounts for channel estimation, pilot contamination, and an arbitrary path loss and antenna correlation for each link. We derive approximations of achievable rates with several linear precoders and detectors which are proven to be asymptotically tight, but accurate for realistic system dimensions, as shown by simulations. It is known from previous work assuming uncorrelated channels, that as N→∞ while K is fixed, the system performance is limited by pilot contamination, the simplest precoders/detectors, i.e., eigenbeamforming (BF) and matched filter (MF), are optimal, and the transmit power can be made arbitrarily small. We analyze to which extent these conclusions hold in the more realistic setting where N is not extremely large compared to K. In particular, we derive how many antennas per UT are needed to achieve η% of the ultimate performance limit with infinitely many antennas and how many more antennas are needed with MF and BF to achieve the performance of minimum mean-square error (MMSE) detection and regularized zero-forcing (RZF), respectively.

Information diffusion in online social networks: a survey

Abstract: Online social networks play a major role in the spread of information at very large scale. A lot of effort have been made in order to understand this phenomenon, ranging from popular topic detection to information diffusion modeling, including influential spreaders identification. In this article, we present a survey of representative methods dealing with these issues and propose a taxonomy that summarizes the state-of-the-art. The objective is to provide a comprehensive analysis and guide of existing efforts around information diffusion in social networks. This survey is intended to help researchers in quickly understanding existing works and possible improvements to bring.

Software Engineering for Self-Adaptive Systems : A Second Research Roadmap

Abstract: The goal of this roadmap paper is to summarize the state-of-the-art and identify research challenges when developing, deploying and managing self-adaptive software systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-adaptive solutions, software engineering processes for self-adaptive systems, from centralized to decentralized control, and practical run-time verification & validation for self-adaptive systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-adaptive systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.

Energy-Optimal Mobile Cloud Computing under Stochastic Wireless Channel

Abstract: This paper provides a theoretical framework of energy-optimal mobile cloud computing under stochastic wireless channel. Our objective is to conserve energy for the mobile device, by optimally executing mobile applications in the mobile device (i.e., mobile execution) or offloading to the cloud (i.e., cloud execution). One can, in the former case sequentially reconfigure the CPU frequency; or in the latter case dynamically vary the data transmission rate to the cloud, in response to the stochastic channel condition. We formulate both scheduling problems as constrained optimization problems, and obtain closed-form solutions for optimal scheduling policies. Furthermore, for the energy-optimal execution strategy of applications with small output data (e.g., CloudAV), we derive a threshold policy, which states that the data consumption rate, defined as the ratio between the data size (L) and the delay constraint (T), is compared to a threshold which depends on both the energy consumption model and the wireless channel model. Finally, numerical results suggest that a significant amount of energy can be saved for the mobile device by optimally offloading mobile applications to the cloud in some cases. Our theoretical framework and numerical investigations will shed lights on system implementation of mobile cloud computing under stochastic wireless channel.

Towards an elastic distributed SDN controller

Abstract: Distributed controllers have been proposed for Software Defined Networking to address the issues of scalability and reliability that a centralized controller suffers from. One key limitation of the distributed controllers is that the mapping between a switch and a controller is statically configured, which may result in uneven load distribution among the controllers. To address this problem, we propose ElastiCon, an elastic distributed controller architecture in which the controller pool is dynamically grown or shrunk according to traffic conditions and the load is dynamically shifted across controllers. We propose a novel switch migration protocol for enabling such load shifting, which conforms with the Openflow standard. We also build a prototype to demonstrate the efficacy of our design.

Traffic engineering in software defined networks

Abstract: Software Defined Networking is a new networking paradigm that separates the network control plane from the packet forwarding plane and provides applications with an abstracted centralized view of the distributed network state. A logically centralized controller that has a global network view is responsible for all the control decisions and it communicates with the network-wide distributed forwarding elements via standardized interfaces. Google recently announced [5] that it is using a Software Defined Network (SDN) to interconnect its data centers due to the ease, efficiency and flexibility in performing traffic engineering functions. It expects the SDN architecture to result in better network capacity utilization and improved delay and loss performance. The contribution of this paper is on the effective use of SDNs for traffic engineering especially when SDNs are incrementally introduced into an existing network. In particular, we show how to leverage the centralized controller to get significant improvements in network utilization as well as to reduce packet losses and delays. We show that these improvements are possible even in cases where there is only a partial deployment of SDN capability in a network. We formulate the SDN controller's optimization problem for traffic engineering with partial deployment and develop fast Fully Polynomial Time Approximation Schemes (FPTAS) for solving these problems. We show, by both analysis and ns-2 simulations, the performance gains that are achievable using these algorithms even with an incrementally deployed SDN.

SoftRAN: software defined radio access network

Abstract: An important piece of the cellular network infrastructure is the radio access network (RAN) that provides wide-area wireless connectivity to mobile devices. The fundamental problem the RAN solves is figuring out how best to use and manage limited spectrum to achieve this connectivity. In a dense wireless deployment with mobile nodes and limited spectrum, it becomes a difficult task to allocate radio resources, implement handovers, manage interference, balance load between cells, etc.We argue that LTE's current distributed control plane is suboptimal in achieving the above objective. We propose SoftRAN, a fundamental rethink of the radio access layer. SoftRAN is a software defined centralized control plane for radio access networks that abstracts all base stations in a local geographical area as a virtual big-base station comprised of a central controller and radio elements (individual physical base stations). In defining such an architecture, we create a framework through which a local geographical network can effectively perform load balancing and interference management, as well as maximize throughput, global utility, or any other objective.

Universal-filtered multi-carrier technique for wireless systems beyond LTE

Abstract: In this paper, we propose a multi-carrier transmission scheme to overcome the problem of intercarrier interference (ICI) in orthogonal frequency division multiplexing (OFDM) systems. In the proposed scheme, called universal-filtered multi-carrier (UFMC), a filtering operation is applied to a group of consecutive subcarriers (e.g. a given allocation of a single user) in order to reduce out-of-band sidelobe levels and subsequently minimize the potential ICI between adjacent users in case of asynchronous transmissions. We consider a coordinated multi-point (CoMP) reception technique, where a number of base stations (BSs) send the received signals from user equipments (UEs) to a CoMP central unit (CCU) for joint detection and processing. We examine the impact of carrier frequency offset (CFO) on the performance of the proposed scheme and compare the results with the performance of cyclic prefix based orthogonal frequency division multiplexing (CP-OFDM) systems. We use computer experiments to illustrate the efficiency of the proposed multi-carrier scheme. The results indicate that the UFMC scheme outperforms the OFDM for both perfect and non-perfect frequency synchronization between the UEs and BSs.

Inter-Cell Interference in Noncooperative TDD Large Scale Antenna Systems

Abstract: In this paper we study the performance of cellular networks when their base stations have an unlimited number of antennas. In previous work, the asymptotic behavior of the signal to interference plus nose ratio (SINR) was obtained. We revisit these results by deriving the rigorous expression for the SINR of both downlink and uplink in the scenario of infinite number of antennas. We show that the contamination of the channel estimates happens whenever a pilot sequence is received at a base station simultaneously with non-orthogonal signals coming from other users. We propose a method to avoid such simultaneous transmissions from adjacent cells, thus significantly decreasing interference. We also investigate the effects of power allocation in this interference-limited scenario, and show that it results in gains of over 15dB in the signal to interference ratio for the scenario simulated here. The combination of these two techniques results in rate gains of about 18 times in our simulations.

Sensing Trending Topics in Twitter

Abstract: Online social and news media generate rich and timely information about real-world events of all kinds. However, the huge amount of data available, along with the breadth of the user base, requires a substantial effort of information filtering to successfully drill down to relevant topics and events. Trending topic detection is therefore a fundamental building block to monitor and summarize information originating from social sources. There are a wide variety of methods and variables and they greatly affect the quality of results. We compare six topic detection methods on three Twitter datasets related to major events, which differ in their time scale and topic churn rate. We observe how the nature of the event considered, the volume of activity over time, the sampling procedure and the pre-processing of the data all greatly affect the quality of detected topics, which also depends on the type of detection method used. We find that standard natural language processing techniques can perform well for social streams on very focused topics, but novel techniques designed to mine the temporal distribution of concepts are needed to handle more heterogeneous streams containing multiple stories evolving in parallel. One of the novel topic detection methods we propose, based on -grams cooccurrence and topic ranking, consistently achieves the best performance across all these conditions, thus being more reliable than other state-of-the-art techniques.

A Survey on OFDM-Based Elastic Core Optical Networking

Abstract: Orthogonal frequency-division multiplexing (OFDM) is a modulation technology that has been widely adopted in many new and emerging broadband wireless and wireline communication systems. Due to its capability to transmit a high-speed data stream using multiple spectral-overlapped lower-speed subcarriers, OFDM technology offers superior advantages of high spectrum efficiency, robustness against inter-carrier and inter-symbol interference, adaptability to server channel conditions, etc. In recent years, there have been intensive studies on optical OFDM (O-OFDM) transmission technologies, and it is considered a promising technology for future ultra-high-speed optical transmission. Based on O-OFDM technology, a novel elastic optical network architecture with immense flexibility and scalability in spectrum allocation and data rate accommodation could be built to support diverse services and the rapid growth of Internet traffic in the future. In this paper, we present a comprehensive survey on OFDM-based elastic optical network technologies, including basic principles of OFDM, O-OFDM technologies, the architectures of OFDM-based elastic core optical networks, and related key enabling technologies. The main advantages and issues of OFDM-based elastic core optical networks that are under research are also discussed.

SoftCell: scalable and flexible cellular core network architecture

Abstract: Cellular core networks suffer from inflexible and expensive equipment, as well as from complex control-plane protocols. To address these challenges, we present SoftCell, a scalable architecture that supports fine-grained policies for mobile devices in cellular core networks, using commodity switches and servers. SoftCell enables operators to realize high-level service policies that direct traffic through sequences of middleboxes based on subscriber attributes and applications. To minimize the size of the forwarding tables, SoftCell aggregates traffic along multiple dimensions---the service policy, the base station, and the mobile device---at different switches in the network. Since most traffic originates from mobile devices, SoftCell performs fine-grained packet classification at the access switches, next to the base stations, where software switches can easily handle the state and bandwidth requirements. SoftCell guarantees that packets belonging to the same connection traverse the same sequence of middleboxes in both directions, even in the presence of mobility. We demonstrate that SoftCell improves the scalability and flexibility of cellular core networks by analyzing real LTE workloads, performing micro-benchmarks on our prototype controller as well as large-scale simulations.

Phase-conjugated twin waves for communication beyond the Kerr nonlinearity limit

Abstract: The transmission of a pair of phase-conjugated beams is shown to mitigate nonlinear distortion during optical fibre communication, allowing a 400 Gbit s−1 superchannel to be sent over 12,800 km of optical fibre.

The Multicell Multiuser MIMO Uplink with Very Large Antenna Arrays and a Finite-Dimensional Channel

Abstract: We consider multicell multiuser MIMO systems with a very large number of antennas at the base station (BS). We assume that the channel is estimated by using uplink training. We further consider a physical channel model where the angular domain is separated into a finite number of distinct directions. We analyze the so-called pilot contamination effect discovered in previous work, and show that this effect persists under the finite-dimensional channel model that we consider. In particular, we consider a uniform array at the BS. For this scenario, we show that when the number of BS antennas goes to infinity, the system performance under a finite-dimensional channel model with P angular bins is the same as the performance under an uncorrelated channel model with P antennas. We further derive a lower bound on the achievable rate of uplink data transmission with a linear detector at the BS. We then specialize this lower bound to the cases of maximum-ratio combining (MRC) and zero-forcing (ZF) receivers, for a finite and an infinite number of BS antennas. Numerical results corroborate our analysis and show a comparison between the performances of MRC and ZF in terms of sum-rate.

Nonlinear Propagation in Multimode and Multicore Fibers: Generalization of the Manakov Equations

Abstract: We investigate theoretically nonlinear transmission in space-division multiplexed (SDM) systems using multimode fibers exhibiting rapidly varying birefringence. A primary objective is to generalize the Manakov equations, well known in the case of single-mode fibers. We first investigate the case where linear coupling among spatial modes of the fiber is weak and derive new Manakov equations after averaging over random birefringence fluctuations. Such an averaging reduces the number of intermodal nonlinear terms drastically since all four-wave-mixing terms vanish. Cross-phase modulation terms still affect multimode transmission but their effectiveness is reduced. We verify the accuracy of new Manakov equations by simulating the transmission of multiple 114-Gb/s bit streams in the PDM-QPSK format over different modes of a multimode fiber and comparing the numerical results with those obtained by solving the full stochastic equations. The agreement is excellent in all cases studied. A major benefit of the new Manakov equations is that they typically reduce the computation time by more than a factor of 10. Our results show that birefringence fluctuations improve system performance by reducing the impact of fiber nonlinearities. The extent of improvement depends on the fiber design and how many spatial modes are used for SDM transmission. We also consider the case where all spatial modes experience strong random linear coupling modeled using a random matrix. We derive new Manakov equations in this regime and show that the impact of some nonlinear effects can be reduced relatively to single-modes fibers. Finally, we extend our analysis to multicore fibers and show that the Manakov equations obtained in the strong- and weak-coupling regimes can still be used depending on the extent of coupling among fiber cores.

When cellular meets WiFi in wireless small cell networks

Abstract: The deployment of small cell base stations, SCBSs, overlaid on existing macrocellular systems is seen as a key solution for offloading traffic, optimizing coverage, and boosting the capacity of future cellular wireless systems. The next generation of SCBSs is envisioned to be multimode (i.e., capable of transmitting simultaneously on both licensed and unlicensed bands). This constitutes a cost-effective integration of both WiFi and cellular radio access technologies that can efficiently cope with peak wireless data traffic and heterogeneous quality of service requirements. To leverage the advantage of such multimode SCBSs, we discuss the novel proposed paradigm of cross-system learning by means of which SCBSs self-organize and autonomously steer their traffic flows across different RATs. Cross-system learning allows the SCBSs to leverage the advantage of both the WiFi and cellular worlds. For example, the SCBSs can offload delay-tolerant data traffic to WiFi, while simultaneously learning the probability distribution function of their transmission strategy over the licensed cellular band. This article first introduces the basic building blocks of cross-system learning and then provides preliminary performance evaluation in a Long-Term Evolution simulator overlaid with WiFi hotspots. Remarkably, it is shown that the proposed cross-system learning approach significantly outperforms a number of benchmark traffic steering policies.

Quantitative analysis of split base station processing and determination of advantageous architectures for LTE

Abstract: Centralization of the baseband processing in radio access networks may reduce radio site operations costs, reduce capital costs, and ease implementation of multi-site coordination mechanisms such as coordinated multipoint transmission and reception (CoMP). However, the initial architecture proposals for a centralized Long Term Evolution (LTE) deployment using transport of radio samples require a high-bandwidth, low-latency interconnection network. This may be uneconomical, or it may only be cost effective for a limited number of sites. To mitigate that deficiency without sacrificing the benefits of centralized processing, we identified alternative interfacing options between central and remote units. To do so we analyzed possible splits of the Long Term Evolution (LTE) baseband processing chain for their bandwidth and latency requirements. Next, we analyzed the operational impacts of potential splits based on a number of criteria including ease of CoMP introduction, the possibility of realizing pooling gains, and the ability to update the system and introduce new features. Based on our results, we propose architectures that can leverage the benefits of centralization at a much-reduced cost.

The Internet of Things: The Next Technological Revolution

Abstract: A wide range of researchers from academia and industry, as well as businesses, government agencies, and cities, are exploring the technologies comprising the Internet of Things from three main perspectives: scientific theory, engineering design, and the user experience.

Making smart use of excess antennas: Massive MIMO, small cells, and TDD

Abstract: In this paper, we present a vision beyond the conventional Long Term Evolution Fourth Generation (LTE-4G) evolution path and suggest that time division duplexing (TDD) could be a key enabler for a new heterogeneous network architecture with the potential to provide ubiquitous coverage and unprecedented spectral area efficiencies. This architecture is based on a cochannel deployment of macro base stations (BSs) with very large antenna arrays and a secondary tier of small cells (SCs) with a few antennas each. Both tiers employ a TDD protocol in a synchronized fashion. The resulting channel reciprocity enables not only the estimation of large-dimensional channels at the BSs, but also an implicit coordination between both tiers without the need to exchange user data or channel state information (CSI) over the backhaul. In particular, during the uplink (UL), the BSs and SCs can locally estimate the dominant interference sub-space. This knowledge can be leveraged for downlink (DL) precoding to reduce intra- and inter-tier interference. In other words, the BSs and SCs “sacrifice” some of their degrees of freedom for interference rejection. Our simulation results demonstrate that the proposed architecture and precoding scheme can achieve a very attractive rate region compared to several baseline scenarios. For example, with 100 antennas at each BS and four antennas at each SC, we observe an aggregate area throughput of 7.63 Gb/s/km2 (DL) and 8.93 Gb/s/km2 (UL) on a 20 MHz band shared by about 100 mobile devices.

Immersion Condensation on Oil-Infused Heterogeneous Surfaces for Enhanced Heat Transfer

Abstract: Enhancing condensation heat transfer is important for broad applications from power generation to water harvesting systems Significant efforts have focused on easy removal of the condensate, yet the other desired properties of low contact angles and high nucleation densities for high heat transfer performance have been typically neglected In this work, we demonstrate immersion condensation on oil-infused micro and nanostructured surfaces with heterogeneous coatings, where water droplets nucleate immersed within the oil The combination of surface energy heterogeneity, reduced oil-water interfacial energy, and surface structuring enabled drastically increased nucleation densities while maintaining easy condensate removal and low contact angles Accordingly, on oil-infused heterogeneous nanostructured copper oxide surfaces, we demonstrated approximately 100% increase in heat transfer coefficient compared to state-of-the-art dropwise condensation surfaces in the presence of non-condensable gases This work offers a distinct approach utilizing surface chemistry and structuring together with liquid-infusion for enhanced condensation heat transfer

Total energy efficiency of cellular large scale antenna system multiple access mobile networks

Abstract: Energy efficiency and spectral efficiency of a Large Scale Antenna System in both dense urban and suburban multi-macro-cellular scenarios are quantified using a new total energy efficiency model, which consists of a rigorous capacity lower bound and a power model accounting for RF generation, LSAS critical computing and a per antenna internal power consumption for other analog electronics and A/D and D/A converters that are associated with each LSAS service antenna. Based on our model, in dense urban, an LSAS with sixty-four OdB gain service antennas per cell, each service antenna consuming an internal power of 128 mW above the power required for RF generation and for LSAS critical computing, can simultaneously serve 15 users with a total energy efficiency almost 1000 times greater than that of a typical LTE base station and at the same time more than quadruple the aggregate spectral efficiency.

Immersion Condensation on Oil-Infused Heterogeneous Surfaces for Enhanced Heat Transfer

Abstract: Enhancing condensation heat transfer is important for broad applications from power generation to water harvesting systems Significant efforts have focused on easy removal of the condensate, yet the other desired properties of low contact angles and high nucleation densities for high heat transfer performance have been typically neglected In this work, we demonstrate immersion condensation on oil-infused micro and nanostructured surfaces with heterogeneous coatings, where water droplets nucleate immersed within the oil The combination of surface energy heterogeneity, reduced oil-water interfacial energy, and surface structuring enabled drastically increased nucleation densities while maintaining easy condensate removal and low contact angles Accordingly, on oil-infused heterogeneous nanostructured copper oxide surfaces, we demonstrated approximately 100% increase in heat transfer coefficient compared to state-of-the-art dropwise condensation surfaces in the presence of non-condensable gases This work offers a distinct approach utilizing surface chemistry and structuring together with liquid-infusion for enhanced condensation heat transfer

Demonstration of a heterogeneously integrated III-V/SOI single wavelength tunable laser

Abstract: A heterogeneously integrated III-V-on-silicon laser is reported, integrating a III-V gain section, a silicon ring resonator for wavelength selection and two silicon Bragg grating reflectors as back and front mirrors. Single wavelength operation with a side mode suppression ratio higher than 45 dB is obtained. An output power up to 10 mW at 20 °C and a thermo-optic wavelength tuning range of 8 nm are achieved. The laser linewidth is found to be 1.7 MHz.

Electrostatic charging of jumping droplets

Abstract: With the broad interest in and development of superhydrophobic surfaces for self-cleaning, condensation heat transfer enhancement and anti-icing applications, more detailed insights on droplet interactions on these surfaces have emerged. Specifically, when two droplets coalesce, they can spontaneously jump away from a superhydrophobic surface due to the release of excess surface energy. Here we show that jumping droplets gain a net positive charge that causes them to repel each other mid-flight. We used electric fields to quantify the charge on the droplets and identified the mechanism for the charge accumulation, which is associated with the formation of the electric double layer at the droplet-surface interface. The observation of droplet charge accumulation provides insight into jumping droplet physics as well as processes involving charged liquid droplets. Furthermore, this work is a starting point for more advanced approaches for enhancing jumping droplet surface performance by using external electric fields to control droplet jumping.

SignalSLAM: Simultaneous localization and mapping with mixed WiFi, Bluetooth, LTE and magnetic signals

Abstract: Indoor localization typically relies on measuring a collection of RF signals, such as Received Signal Strength (RSS) from WiFi, in conjunction with spatial maps of signal fingerprints. A new technology for localization could arise with the use of 4G LTE telephony small cells, with limited range but with rich signal strength information, namely Reference Signal Received Power (RSRP). In this paper, we propose to combine an ensemble of available sources of RF signals to build multi-modal signal maps that can be used for localization or for network deployment optimization. We primarily rely on Simultaneous Localization and Mapping (SLAM), which provides a solution to the challenge of building a map of observations without knowing the location of the observer. SLAM has recently been extended to incorporate signal strength from WiFi in the so-called WiFi-SLAM. In parallel to WiFi-SLAM, other localization algorithms have been developed that exploit the inertial motion sensors and a known map of either WiFi RSS or of magnetic field magnitude. In our study, we use all the measurements that can be acquired by an off-the-shelf smartphone and crowd-source the data collection from several experimenters walking freely through a building, collecting time-stamped WiFi and Bluetooth RSS, 4G LTE RSRP, magnetic field magnitude, GPS reference points when outdoors, Near-Field Communication (NFC) readings at specific landmarks and pedestrian dead reckoning based on inertial data. We resolve the location of all the users using a modified version of Graph-SLAM optimization of the users poses with a collection of absolute location and pairwise constraints that incorporates multi-modal signal similarity. We demonstrate that we can recover the user positions and thus simultaneously generate dense signal maps for each WiFi access point and 4G LTE small cell, “from the pocket”. Finally, we demonstrate the localization performance using selected single modalities, such as only WiFi and the WiFi signal maps that we generated.

Electrostatic charging of jumping droplets

Abstract: United States. Dept. of Energy. Office of Basic Energy Sciences (Solid-State Solar-Thermal Energy Conversion Center Award DE-FG02-09ER46577)

Electric-Field-Enhanced Condensation on Superhydrophobic Nanostructured Surfaces

Abstract: When condensed droplets coalesce on a superhydrophobic nanostructured surface, the resulting droplet can jump due to the conversion of excess surface energy into kinetic energy. This phenomenon has...

Experimental Investigation of Inter-Modal Four-Wave Mixing in Few-Mode Fibers

Abstract: We experimentally demonstrate nondegenerate four-wave mixing (FWM) between waves belonging to different spatial modes of a 5-km-long few-mode fiber (FMF). Of the three inter-modal FWM (IM-FWM) processes possible, two have been experimentally observed. These IM-FWM processes are found to be phase-matched over very large frequency separations of several Terahertz between the waves. In contrast to FWM in single-mode fibers that require operating near the zero-dispersion wavelength to achieve phase matching, IM-FWM in a FMF can be fully phase matched in the presence of large chromatic dispersion in each spatial mode.

Support Recovery With Sparsely Sampled Free Random Matrices

Abstract: Consider a Bernoulli-Gaussian complex n-vector whose components are Vi = XiBi, with Xi ~ C N(0, Px) and binary Bi mutually independent and iid across i. This random q-sparse vector is multiplied by a square random matrix U, and a randomly chosen subset, of average size n p, p ∈ [0,1], of the resulting vector components is then observed in additive Gaussian noise. We extend the scope of conventional noisy compressive sampling models where U is typically a matrix with iid components, to allow U satisfying a certain freeness condition. This class of matrices encompasses Haar matrices and other unitarily invariant matrices. We use the replica method and the decoupling principle of Guo and Verdu, as well as a number of information-theoretic bounds, to study the input-output mutual information and the support recovery error rate in the limit of n → ∞. We also extend the scope of the large deviation approach of Rangan and characterize the performance of a class of estimators encompassing thresholded linear MMSE and l1 relaxation.