Conservatoire national des arts et métiers

About: Conservatoire national des arts et métiers is a education organization based out in Paris, France. It is known for research contribution in the topics: Population & Orthogonal frequency-division multiplexing. The organization has 3573 authors who have published 7127 publications receiving 141430 citations. The organization is also known as: CNAM & Conservatoire des arts et métiers.

OFDM and FBMC transmission techniques: a compatible high performance proposal for broadband power line communications

Abstract: A filter bank multicarrier (FBMC) system having a high level of compatibility with the IEEE P1901 OFDM scheme is proposed. In order to reach the level of robustness, selectivity and performance required by the broadband power line, the approach is based on near perfect reconstruction (NPR) filters combined with OQAM modulation. A key feature of the approach is the fractionally-spaced sub-channel equalizer, which is able to compensate the channel distortions and cope with residual timing offsets. The system initialization procedure and the results of OFDM are exploited by FBMC and an efficient and accurate technique is described for the derivation of the sub-channel equalizer coefficients from the OFDM frequency domain equalizer coefficients. Then, the impact of the filter impulse response on the efficiency in packet transmission is minimized. Finally, the impact of the sub-channel spacing is investigated and, in a comparison on similar basis, it appears that the proposed FBMC system can reach 228 Mbit/s in maximum bit rate, versus 197 Mbit/s for OFDM, while providing a higher level of tone protection and robustness to jammers.

RoSeS: a continuous content-based query engine for RSS feeds

Abstract: In this paper we present RoSeS (Really Open Simple and Efficient Syndication), a generic framework for content-based RSS feed querying and aggregation. RoSeS is based on a data-centric approach, using a combination of standard database concepts like declarative query languages, views and multiquery optimization. Users create personalized feeds by defining and composing content-based filtering and aggregation queries on collections of RSS feeds. Publishing these queries corresponds to defining views which can then be used for building new queries / feeds. This naturally reflects the publish-subscribe nature of RSS applications. The contributions presented in this paper are a declarative RSS feed aggregation language, an extensible stream algebra for building efficient continuous multi-query execution plans for RSS aggregation views, a multiquery optimization strategy for these plans and a running prototype based on a multi-threaded asynchronous execution engine.