Nokia

About: Nokia is a company organization based out in Espoo, Finland. It is known for research contribution in the topics: Signal & Mobile station. The organization has 16625 authors who have published 28347 publications receiving 695725 citations. The organization is also known as: Nokia Oyj & Oy Nokia Ab.

Square-matrix embeddable space-time block codes for complex signal constellations

Abstract: Space-time block codes for providing transmit diversity in wireless communication systems are considered. Based on the principles of linearity and unitarity, a complete classification of linear codes is given in the case when the symbol constellations are complex, and the code is based on a square matrix or restriction of such by deleting columns (antennas). Maximal rate delay optimal codes are constructed within this category. The maximal rates allowed by linearity and unitarity fall off exponentially with the number of transmit antennas.

Mobile mesh ad-hoc networking

Abstract: An architectural solution in which standalone ad-hoc network cells are used as an extension of the backbone infrastructure in terms of network architecture or/and its service capabilities is provided. These Ad-Hoc networks will integrate to the Internet via cellular and other access networks. This integration brings new possibilities to network operators and ISP's. In its extended architecture, it is envisaged that the mobility issues are handled by utilizing the IP mobility capabilities, taking into account the mobile mesh Ad-Hoc specific requirements.

Cassini plasma spectrometer investigation

Abstract: The Cassini Plasma Spectrometer (CAPS) will make comprehensive three-dimensional mass-resolved measurements of the full variety of plasma phenomena found in Saturn’s magnetosphere. Our fundamental scientific goals are to understand the nature of saturnian plasmas primarily their sources of ionization, and the means by which they are accelerated, transported, and lost. In so doing the CAPS investigation will contribute to understanding Saturn’s magnetosphere and its complex interactions with Titan, the icy satellites and rings, Saturn’s ionosphere and aurora, and the solar wind. Our design approach meets these goals by emphasizing two complementary types of measurements: high-time resolution velocity distributions of electrons and all major ion species; and lower-time resolution, high-mass resolution spectra of all ion species. The CAPS instrument is made up of three sensors: the Electron Spectrometer (ELS), the Ion Beam Spectrometer (IBS), and the Ion Mass Spectrometer (IMS). The ELS measures the velocity distribution of electrons from 0.6 eV to 28,250 keV, a range that permits coverage of thermal electrons found at Titan and near the ring plane as well as more energetic trapped electrons and auroral particles. The IBS measures ion velocity distributions with very high angular and energy resolution from 1 eV to 49,800 keV. It is specially designed

Mode Selection for Device-To-Device Communication Underlaying an LTE-Advanced Network

Abstract: Device-to-Device communication underlaying a cellular network enables local services with limited interference to the cellular network. In this paper we study the optimal selection of possible resource sharing modes with the cellular network in a single cell. Based on the learning from the single cell studies we propose a mode selection procedure for a multi-cell environment. Our evaluation results of the proposed procedure show that it enables a much more reliable device-to-device communication with limited interference to the cellular network compared to simpler mode selection procedures. A well performing and practical mode selection is critical to enable the adoption of underlay device-to-device communication in cellular networks.

City-scale landmark identification on mobile devices

Abstract: With recent advances in mobile computing, the demand for visual localization or landmark identification on mobile devices is gaining interest. We advance the state of the art in this area by fusing two popular representations of street-level image data — facade-aligned and viewpoint-aligned — and show that they contain complementary information that can be exploited to significantly improve the recall rates on the city scale. We also improve feature detection in low contrast parts of the street-level data, and discuss how to incorporate priors on a user's position (e.g. given by noisy GPS readings or network cells), which previous approaches often ignore. Finally, and maybe most importantly, we present our results according to a carefully designed, repeatable evaluation scheme and make publicly available a set of 1.7 million images with ground truth labels, geotags, and calibration data, as well as a difficult set of cell phone query images. We provide these resources as a benchmark to facilitate further research in the area.