NTT DoCoMo

About: NTT DoCoMo is a based out in . It is known for research contribution in the topics: Base station & Mobile station. The organization has 4032 authors who have published 8655 publications receiving 160533 citations.

A semantic Web services architecture

Abstract: The semantic Web services initiative architecture (SWSA) committee has created a set of architectural and protocol abstractions that serve as a foundation for semantic Web service technologies. This article summarizes the committee's findings, emphasizing its review of requirements gathered from several different environments. We also identify the scope and potential requirements for a semantic Web services architecture.

Certificate-Based Encryption and the Certificate Revocation Problem

Abstract: We introduce the notion of certificate-based encryption. In this model, a certificate - or, more generally, a signature - acts not only as a certificate but also as a decryption key. To decrypt a message, a keyholder needs both its secret key and an up-to-date certificate from its CA (or a signature from an authorizer). Certificate-based encryption combines the best aspects of identity-based encryption (implicit certification) and public key encryption (no escrow). We demonstrate how certificate-based encryption can be used to construct an efficient PKI requiring less infrastructure than previous proposals, including Micali's Novomodo, Naor-Nissim and Aiello-Lodha-Ostrovsky.

Intra Prediction by Template Matching

Abstract: Intra prediction is an effective method for reducing the coded information of an image or an intra frame within a video sequence. The conventional method today is to create a sample predictor block by extrapolating the reconstructed pixels surrounding the target block to be coded. The sample predictor block is subtracted from the target block and the resulting residual coded using transformation, quantization and entropy coding. This is an effective method for sample predictor block creation in most sequences. However the extrapolation method is not able to represent sample prediction blocks with complex texture. Furthermore, pixels that are far from the surrounding pixels are usually badly predicted. In this paper, a new method for sample predictor creation by template matching in a region of reconstructed pixels is presented. Improvements in coding efficiency by more than 11 % in bitrate were achieved.

Flexible power modeling of LTE base stations

Abstract: With the explosion of wireless communications in number of users and data rates, the reduction of network power consumption becomes more and more critical. This is especially true for base stations which represent a dominant share of the total power in cellular networks. In order to study power reduction techniques, a convenient power model is required, providing estimates of the power consumption in different scenarios. This paper proposes such a model, accurate but simple to use. It evaluates the base station power consumption for different types of cells supporting the 3GPP LTE standard. It is flexible enough to enable comparisons between state-of-the-art and advanced configurations, and an easy adaptation to various scenarios. The model is based on a combination of base station components and sub-components as well as power scaling rules as functions of the main system parameters.

NLOS Identification and Mitigation for UWB Localization Systems

Abstract: Non-line-of-sight (NLOS) identification and mitigation carries significant importance in wireless positioning systems. In this paper, the authors propose a novel NLOS identification technique based on the multipath channel statistics such as the kurtosis, the mean excess delay spread, and the root mean square delay spread. In particular, the IEEE 802.15.4a ultrawideband channel models are used as examples and the above statistics are found to be well modeled by log-normal random variables. Subsequently, a joint likelihood ratio test is developed for LOS/NLOS identification. Simulation results show that correct identification can be achieved with over 90% of the realizations for most channel models. A weighted least squares localization algorithm is also developed using the NLOS information, and accuracy gains with respect to a conventional least squares algorithm are demonstrated via Monte-Carlo simulations.