Showing papers by "Nokia published in 2014"

Millimeter-Wave Enhanced Local Area Systems: A High-Data-Rate Approach for Future Wireless Networks

Abstract: Wireless data traffic is projected to skyrocket 10 000 fold within the next 20 years. To tackle this incredible increase in wireless data traffic, a first approach is to further improve spectrally efficient systems such as 4G LTE in bands below 6 GHz by using more advanced spectral efficiency techniques. However, the required substantial increase in system complexity along with fundamental limits on hardware implementation and channel conditions may limit the viability of this approach. Furthermore, the end result would be an extremely spectrally efficient system with little room for future improvement to meet the ever-growing wireless data usage. The second approach is to move up in frequency, into an unused nontraditional spectrum where enormous bandwidths are available, such as at millimeter wave (mmWave). The mmWave option enables the use of simple air interfaces since large bandwidths can be exploited (e.g., 2 GHz) to achieve high data rates rather than relying on highly complex techniques originally aimed at achieving a high spectral efficiency with smaller bandwidths. In addition, mmWave systems will easily evolve to even higher system capacities, because there will be plenty of margin to improve the spectral efficiency as data demands further increase. In this paper, a case is made for using mmWave for a fifth generation (5G) wireless system for ultradense networks by presenting an overview of enhanced local area (eLA) technology at mmWave with emphasis on 5G requirements, spectrum considerations, propagation and channel modeling, air-interface and multiantenna design, and network architecture solutions.

Method and apparatus for video coding and decoding

Abstract: A method comprises receiving a first sequence of access units and a second sequence of access units; decoding at least one access unit of the first sequence of access units; decoding a first decodable access unit of the second sequence of access units; determining whether a next decodable access unit in the second sequence of access units can be decoded before an output time of the next decodable access unit in the second sequence of access units; and skipping decoding of the next decodable access unit based on determining that the next decodable access unit cannot be decoded before the at least one of the decoding time and the output time of the next decodable access unit.

Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework

Abstract: We review algorithms developed for nonnegative matrix factorization (NMF) and nonnegative tensor factorization (NTF) from a unified view based on the block coordinate descent (BCD) framework. NMF and NTF are low-rank approximation methods for matrices and tensors in which the low-rank factors are constrained to have only nonnegative elements. The nonnegativity constraints have been shown to enable natural interpretations and allow better solutions in numerous applications including text analysis, computer vision, and bioinformatics. However, the computation of NMF and NTF remains challenging and expensive due the constraints. Numerous algorithmic approaches have been proposed to efficiently compute NMF and NTF. The BCD framework in constrained non-linear optimization readily explains the theoretical convergence properties of several efficient NMF and NTF algorithms, which are consistent with experimental observations reported in literature. In addition, we discuss algorithms that do not fit in the BCD framework contrasting them from those based on the BCD framework. With insights acquired from the unified perspective, we also propose efficient algorithms for updating NMF when there is a small change in the reduced dimension or in the data. The effectiveness of the proposed updating algorithms are validated experimentally with synthetic and real-world data sets.

Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary Algorithm Based on Decomposition

Abstract: Adaptive operator selection (AOS) is used to determine the application rates of different operators in an online manner based on their recent performances within an optimization process. This paper proposes a bandit-based AOS method, fitness-rate-rank-based multiarmed bandit (FRRMAB). In order to track the dynamics of the search process, it uses a sliding window to record the recent fitness improvement rates achieved by the operators, while employing a decaying mechanism to increase the selection probability of the best operator. Not much work has been done on AOS in multiobjective evolutionary computation since it is very difficult to measure the fitness improvements quantitatively in most Pareto-dominance-based multiobjective evolutionary algorithms. Multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes a multiobjective optimization problem into a number of scalar optimization subproblems and optimizes them simultaneously. Thus, it is natural and feasible to use AOS in MOEA/D. We investigate several important issues in using FRRMAB in MOEA/D. Our experimental results demonstrate that FRRMAB is robust and its operator selection is reasonable. Comparison experiments also indicate that FRRMAB can significantly improve the performance of MOEA/D.

Spectrum Sharing for Device-to-Device Communication in Cellular Networks

Abstract: This paper addresses two fundamental and interrelated issues in device-to-device (D2D) enhanced cellular networks. The first issue is how D2D users should access spectrum, and we consider two choices: overlay (orthogonal spectrum between D2D and cellular UEs) and underlay (non-orthogonal). The second issue is how D2D users should choose between communicating directly or via the base station, a choice that depends on distance between the potential D2D transmitter and receiver. We propose a tractable hybrid network model where the positions of mobiles are modeled by random spatial Poisson point process, with which we present a general analytical approach that allows a unified performance evaluation for these questions. Then, we derive analytical rate expressions and apply them to optimize the two D2D spectrum sharing scenarios under a weighted proportional fair utility function. We find that as the proportion of potential D2D mobiles increases, the optimal spectrum partition in the overlay is almost invariant (when D2D mode selection threshold is large) while the optimal spectrum access factor in the underlay decreases. Further, from a coverage perspective, we reveal a tradeoff between the spectrum access factor and the D2D mode selection threshold in the underlay: as more D2D links are allowed (due to a more relaxed mode selection threshold), the network should actually make less spectrum available to them to limit their interference.

Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, autofocusing, moving targets, and compressed sensing

Abstract: This article presents a survey of recent research on sparsity-driven synthetic aperture radar (SAR) imaging. In particular, it reviews 1) the analysis and synthesis-based sparse signal representation formulations for SAR image formation together with the associated imaging results, 2) sparsity-based methods for wide-angle SAR imaging and anisotropy characterization, 3) sparsity-based methods for joint imaging and autofocusing from data with phase errors, 4) techniques for exploiting sparsity for SAR imaging of scenes containing moving objects, and 5) recent work on compressed sensing (CS)-based analysis and design of SAR sensing missions.

Enabling the coexistence of LTE and Wi-Fi in unlicensed bands

Abstract: The expansion of wireless broadband access network deployments is resulting in increased scarcity of available radio spectrum. It is very likely that in the near future, cellular technologies and wireless local area networks will need to coexist in the same unlicensed bands. However, the two most prominent technologies, LTE and Wi-Fi, were designed to work in different bands and not to coexist in a shared band. In this article, we discuss the issues that arise from the concurrent operation of LTE and Wi-Fi in the same unlicensed bands from the point of view of radio resource management. We show that Wi-Fi is severely impacted by LTE transmissions; hence, the coexistence of LTE and Wi-Fi needs to be carefully investigated. We discuss some possible coexistence mechanisms and future research directions that may lead to successful joint deployment of LTE and Wi-Fi in the same unlicensed band.

Mining Mobile User Preferences for Personalized Context-Aware Recommendation

Abstract: Recent advances in mobile devices and their sensing capabilities have enabled the collection of rich contextual information and mobile device usage records through the device logs. These context-rich logs open a venue for mining the personal preferences of mobile users under varying contexts and thus enabling the development of personalized context-aware recommendation and other related services, such as mobile online advertising. In this article, we illustrate how to extract personal context-aware preferences from the context-rich device logs, or context logs for short, and exploit these identified preferences for building personalized context-aware recommender systems. A critical challenge along this line is that the context log of each individual user may not contain sufficient data for mining his or her context-aware preferences. Therefore, we propose to first learn common context-aware preferences from the context logs of many users. Then, the preference of each user can be represented as a distribution of these common context-aware preferences. Specifically, we develop two approaches for mining common context-aware preferences based on two different assumptions, namely, context-independent and context-dependent assumptions, which can fit into different application scenarios. Finally, extensive experiments on a real-world dataset show that both approaches are effective and outperform baselines with respect to mining personal context-aware preferences for mobile users.

A college admissions game for uplink user association in wireless small cell networks

Abstract: In this paper, the problem of uplink user association in small cell networks, which involves interactions between users, small cell base stations, and macro-cell stations, having often conflicting objectives, is considered. The problem is formulated as a college admissions game with transfers in which a number of colleges, i.e., small cell and macro-cell stations seek to recruit a number of students, i.e., users. In this game, the users and access points (small cells and macro-cells) rank one another based on preference functions that capture the users' need to optimize their utilities which are functions of packet success rate (PSR) and delay as well as the small cells' incentive to extend the macro-cell coverage (e.g., via cell biasing/range expansion) while maintaining the users' quality-of-service. A distributed algorithm that combines notions from matching theory and coalitional games is proposed to solve the game. The convergence of the algorithm is shown and the properties of the resulting assignments are discussed. Simulation results show that the proposed approach yields a performance improvement, in terms of the average utility per user, reaching up to 23% relative to a conventional, best-PSR algorithm. I. INTRODUCTION Meeting the stringent quality-of-service (QoS) requirements of emerging wireless services warrants substantial changes in current cellular infrastructure. In this respect, the introduction of small cell base stations (SCBSs) (picocells, microcells, fem-

Performance Analysis of Group-Synchronized DCF for Dense IEEE 802.11 Networks

Abstract: In dense IEEE 802.11 networks, improving the efficiency of contention-based media access control is an important and challenging issue. Recently, the IEEE802.11ah Task Group has discussed a group-synchronized distributed coordination function (GS-DCF) for densely deployed wireless networks with a large number of stations. By using the restricted access window (RAW) and RAW slots, the GS-DCF is anticipated to improve the throughput substantially, primarily due to relieving the channel contention. However, optimizing the MAC configurations for the RAW, i.e., the number and duration of RAW slots, is still an open issue. In this paper, we first build an analytical model to track the performance of the GS-DCF in saturated 802.11 networks. Then, we study and compare the GS-DCF throughput using both centralized and decentralized grouping schemes. The accuracy of our model has been validated with simulation results. It is observed that the GS-DCF obtains a throughput gain of seven times or more over DCF in a network of 512 or more stations. Moreover, it is demonstrated that the decentralized grouping scheme can be implemented with a small throughput loss when compared with the centralized grouping scheme.

Channel modelling for the fifth generation mobile communications

Abstract: The main objective of this paper is to present major challenges regarding the fifth generation (5G) mobile communications propagation modelling work in the European 7 th framework project METIS (Mobile and wireless communications Enablers for the Twenty-twenty Information Society). The goal of the propagation work in METIS is to provide adequate propagation models for 5G. For this purpose corresponding deficiencies of present commonly used models are identified. Further, the lack of available channel models for several propagation scenarios has been assessed. Based on this assessment the framework of 5G channel modelling is sketched. As propagation measurement campaigns are a crucial part of this work they are illustrated with a few examples.

Networking solutions for connecting bluetooth low energy enabled machines to the internet of things

Abstract: The next wave driving the expansion of the Internet will come from the Internet of Things. Bluetooth LE is a rapidly emerging ultra-low-power radio technology expected to be incorporated in billions of IoT devices in the next few years. Consequently, it is particularly important to specify Internet connectivity solutions for Bluetooth LE. In this article we present such solutions based on the ongoing standardization work in the IETF and Bluetooth Special Interest Group. We prove the feasibility of a complete IP-based protocol stack on constrained devices and illustrate its performance, highlighting key trade-offs. In addition, we discuss gateway operation covering global IPv6 connectivity and proxy-cache functionality.

Multichannel audio calibration method and apparatus

Abstract: A method comprising: generating at least one audio signal to be output by at least one speaker for a multi-speaker system; receiving at least two output signals, the at least two output signals provided by at least two microphones and based on the at least one acoustic wave output by the at least one speaker in response to the at least one audio signal; determining a directional component associated with the at least two output signals; and comparing the directional component with an expected location of the at least one speaker.

Reference-frame-independent quantum-key-distribution server with a telecom tether for an on-chip client.

Abstract: We demonstrate a client-server quantum key distribution (QKD) scheme. Large resources such as laser and detectors are situated at the server side, which is accessible via telecom fiber to a client requiring only an on-chip polarization rotator, which may be integrated into a handheld device. The detrimental effects of unstable fiber birefringence are overcome by employing the reference-frame-independent QKD protocol for polarization qubits in polarization maintaining fiber, where standard QKD protocols fail, as we show for comparison. This opens the way for quantum enhanced secure communications between companies and members of the general public equipped with handheld mobile devices, via telecom-fiber tethering.

Smart mobility management for D2D communications in 5G networks

Abstract: Direct device-to-device (D2D) communications is regarded as a promising technology to provide low-power, high-data rate and low-latency services between end-users in the future 5G networks. However, it may not always be feasible to provide low-latency reliable communication between end-users due to the nature of mobility. For instance, the latency could be increased when several controlling nodes have to exchange D2D related information among each other. Moreover, the introduced signaling overhead due to D2D operation need to be minimized. Therefore, in this paper, we propose several mobility management solutions with their technical challenges and expected gains under the assumptions of 5G small cell networks.

Highly reproducible printable graphite strain gauges for flexible devices

Abstract: A growing area for the electronics industry is the development of flexible components for novel devices. Controlling the flexibility of such devices requires the precise and reliable measurement of strains in a manner compatible with the form and function of the device. In this article, we demonstrate the fabrication and characterization of printed strain gauges with a gauge factor as high as 19.3 ± 1.4, fast signal response and high reproducibility. The device is made of graphite ink deposited by screen printing on a plastic substrate. The flexible printed sensor is capable of precisely measuring repetitive tensile and compressive bending strain changes. An approach for eliminating the temperature-induced errors of strain gauges based on neutral axis engineering is also described.

Mobile App Classification with Enriched Contextual Information

Abstract: The study of the use of mobile Apps plays an important role in understanding the user preferences, and thus provides the opportunities for intelligent personalized context-based services. A key step for the mobile App usage analysis is to classify Apps into some predefined categories. However, it is a nontrivial task to effectively classify mobile Apps due to the limited contextual information available for the analysis. For instance, there is limited contextual information about mobile Apps in their names. However, this contextual information is usually incomplete and ambiguous. To this end, in this paper, we propose an approach for first enriching the contextual information of mobile Apps by exploiting the additional Web knowledge from the Web search engine. Then, inspired by the observation that different types of mobile Apps may be relevant to different real-world contexts , we also extract some contextual features for mobile Apps from the context-rich device logs of mobile users. Finally, we combine all the enriched contextual information into the Maximum Entropy model for training a mobile App classifier. To validate the proposed method, we conduct extensive experiments on 443 mobile users’ device logs to show both the effectiveness and efficiency of the proposed approach. The experimental results clearly show that our approach outperforms two state-of-the-art benchmark methods with a significant margin.

Experimental mm wave 5G cellular system

Abstract: Bolstered by the ever increasing processing power of smart devices and combined with the new innovative applications, cellular data traffic demand is expected to increase a 10000x by 2025. Simultaneously, the telecommunication industry is converging on a common set of 5G requirements specifying 10x peak rates, 10x reductions in latency and 100x increases in cell edge rates over 4G cellular. Researchers are now looking to higher frequencies to meet demand and achieve the new requirements. This paper describes an experimental 5G system designed to operate at 73.5 GHz with a 1 GHz BW. The system communicates using a 28 dB gain antenna having a narrow 3 degree half-power beamwidth serving fully mobile user devices moving at pedestrian speeds. This experimental system is implemented in collaboration with Nokia and NTT DOCOMO [1][2].

An apparatus and method of providing an apparatus comprising a bendable portion

Abstract: According to various, but not necessarily all examples of the disclosure, there may be provided an apparatus and method wherein the apparatus comprises: a substrate configured to support a bendable display wherein the substrate comprises at least one bendable portion configured to enable the substrate to be moved between an open configuration and a closed configuration; and wherein the at least one bendable portion comprises a plurality of rod members and the rod members comprise interlocking portions wherein the interlocking portions comprise a projection configured to fit into a corresponding recess on an adjacent rod member so as to restrict relative movement of the rod members when the substrate is in the closed configuration.

Method, apparatus, and computer program product for wireless network cluster discovery and concurrency management

Abstract: Embodiments enable discovery of networks in a wireless communications medium. In example embodiments, a method comprises identifying, by an apparatus, a plurality of wireless network clusters by receiving wireless synchronization messages from one or more member devices of each of the plurality of wireless network clusters; calculating, by the apparatus, a cluster grade for each of the plurality of identified wireless network clusters based on information of the received wireless synchronization messages; selecting, by the apparatus, a wireless network cluster from the plurality of identified wireless network clusters, having a highest cluster grade for joining and operating in said wireless network cluster; and ranking, by the apparatus, non-selected wireless network clusters based on predefined criteria applied to information received by the apparatus characterizing the non-selected wireless network clusters.

Distributed object detection with linear SVMs.

Abstract: In vision and learning, low computational complexity and high generalization are two important goals for video object detection. Low computational complexity here means not only fast speed but also less energy consumption. The sliding window object detection method with linear support vector machines (SVMs) is a general object detection framework. The computational cost is herein mainly paid in complex feature extraction and innerproduct-based classification. This paper first develops a distributed object detection framework (DOD) by making the best use of spatial-temporal correlation, where the process of feature extraction and classification is distributed in the current frame and several previous frames. In each framework, only subfeature vectors are extracted and the response of partial linear classifier (i.e., subdecision value) is computed. To reduce the dimension of traditional block-based histograms of oriented gradients (BHOG) feature vector, this paper proposes a cell-based HOG (CHOG) algorithm, where the features in one cell are not shared with overlapping blocks. Using CHOG as feature descriptor, we develop CHOG-DOD as an instance of DOD framework. Experimental results on detection of hand, face, and pedestrian in video show the superiority of the proposed method.

Method, apparatus, and computer program product for hop count usage in cluster selection

Abstract: Embodiments enable access to a wireless communications medium. In example embodiments, a method comprises receiving first synchronization messages from a wireless device transmitting synchronization messages in a first neighbor awareness network cluster, the first synchronization messages including a first hop count value to a first anchor master in the first cluster and information describing a first master rank value of the first anchor master; receiving second synchronization messages from a wireless device transmitting synchronization messages in a second neighbor awareness network cluster, the second synchronization messages including a second hop count value to a second anchor master in the second cluster and information describing a second master rank value of the second anchor master; and selecting the first neighbor awareness network cluster or the second neighbor awareness network cluster, based on at least one of the first and second hop count values and the first and second master rank values.

System and Method to Monitor and Assist Individual's Sleep

Abstract: A sleep assist system to monitor and assist the user's sleep, comprising a bedside device positioned near the user's bed, the bedside device comprising a loudspeaker and a light source and optionally a microphone, a light sensor, a temperature sensor, a control unit, an air quality sensor, a display unit, a user interface. The sleep assist system further comprises a first sensing unit positioned in the user's bed and comprising one or more sensors adapted to sense at least pressure and/or changes in pressure exerted by the user lying in the bed. The system monitors the user's sleep, assesses the user's sleep cycles and the phase of sleep cycle, and provides the user with at least one light and sound program, the light and sound program being based on the assessment of the user's sleep cycles and the phase of sleep cycle.

Communication System And Method

Abstract: The invention relates to a communication system which comprises at least one user equipment having a plurality of identities associated therewith. The user equipment has means for storing at least one of the identities. Storage means are provided for storing at least one of the plurality of identities and means for receiving identity information from the user equipment, for obtaining from the storage means at least one identity associated with the received identity information and for sending to the user equipment the at least one obtained from the storage means.

Ranking user authority with relevant knowledge categories for expert finding

Abstract: The problem of expert finding targets on identifying experts with special skills or knowledge for some particular knowledge categories, i.e. knowledge domains, by ranking user authority. In recent years, this problem has become increasingly important with the popularity of knowledge sharing social networks. While many previous studies have examined authority ranking for expert finding, they have a focus on leveraging only the information in the target category for expert finding. It is not clear how to exploit the information in the relevant categories of a target category for improving the quality of authority ranking. To that end, in this paper, we propose an expert finding framework based on the authority information in the target category as well as the relevant categories. Along this line, we develop a scalable method for measuring the relevancies between categories through topic models, which takes consideration of both content and user interaction based category similarities. Also, we provide a topical link analysis approach, which is multiple-category-sensitive, for ranking user authority by considering the information in both the target category and the relevant categories. Finally, in terms of validation, we evaluate the proposed expert finding framework in two large-scale real-world data sets collected from two major commercial Question Answering (Q&A) web sites. The results show that the proposed method outperforms the baseline methods with a significant margin.

Method and apparatus for joining together multiple functional layers of a flexible display

Abstract: The present invention may relate to provision of a mechanism to join together the various substrate layers of a flexible display with optically clear adhesives that permit improved flexibility of the substrate layer stack and may also optically guide images to locations on a display surface that are not aligned with the display layer of a substrate layer stack. Embodiments of the present invention may provide for an improved user interface which may include enhanced flexibility and enhanced optical characteristics.

Video encoding and decoding

Abstract: There are disclosed various methods, apparatuses and computer program products for video encoding. In some embodiments pictures are encoded into a bitstream. The bitstream comprises at least two scalability layers and pictures being associated with access units. A first indication and a second indication are encoded into the bitstream. The first indication is configured to indicate an output layer. And the second indication is configured to indicate at least one alternative output layer. A first picture of said at least one alternative output layer is output by a decoding process of the bitstream when no picture of the output layer is in an access unit containing said first picture of said at least one alternative output layer.

Liquid Software Manifesto: The Era of Multiple Device Ownership and Its Implications for Software Architecture

Abstract: Today, the digital life of people in developed markets is dominated by PCs and smart phones. Yet, as successful as PCs and smart phones are, the dominant era of PCs and smart phones is about to come to an end. Device shipment trends indicate that the number of web-enabled devices other than PCs and smart phones will grow rapidly. In the near future, people will commonly use various types of internet-connected devices in their daily lives. Unlike today, no single device will dominate the user's digital life. The transition to a world of multiple device ownership is still rife with problems. Since devices are mostly standalone and only stay in sync in limited ways, the users will have to spend a lot of time managing them. These device management chores become much more tedious as the number of devices in a person's life increases. In this paper we look at the ongoing paradigm shift towards multiple device ownership and its implications for software architecture. We argue that the transition to multiple device ownership will eventually lead us to liquid software - an approach that will allow data and applications to seamlessly move between multiple devices and screens. The new era will imply significant changes in the development, deployment and use of software, opening up new opportunities in software engineering research as well.