48,076 research outputs found
Generic Multiuser Coordinated Beamforming for Underlay Spectrum Sharing
The beamforming techniques have been recently studied as possible enablers
for underlay spectrum sharing. The existing beamforming techniques have several
common limitations: they are usually system model specific, cannot operate with
arbitrary number of transmit/receive antennas, and cannot serve arbitrary
number of users. Moreover, the beamforming techniques for underlay spectrum
sharing do not consider the interference originating from the incumbent primary
system. This work extends the common underlay sharing model by incorporating
the interference originating from the incumbent system into generic combined
beamforming design that can be applied on interference, broadcast or multiple
access channels. The paper proposes two novel multiuser beamforming algorithms
for user fairness and sum rate maximization, utilizing newly derived convex
optimization problems for transmit and receive beamformers calculation in a
recursive optimization. Both beamforming algorithms provide efficient operation
for the interference, broadcast and multiple access channels, as well as for
arbitrary number of antennas and secondary users in the system. Furthermore,
the paper proposes a successive transmit/receive optimization approach that
reduces the computational complexity of the proposed recursive algorithms. The
results show that the proposed complexity reduction significantly improves the
convergence rates and can facilitate their operation in scenarios which require
agile beamformers computation.Comment: 30 pages, 5 figure
Real Time Global Tests of the ALICE High Level Trigger Data Transport Framework
The High Level Trigger (HLT) system of the ALICE experiment is an online
event filter and trigger system designed for input bandwidths of up to 25 GB/s
at event rates of up to 1 kHz. The system is designed as a scalable PC cluster,
implementing several hundred nodes. The transport of data in the system is
handled by an object-oriented data flow framework operating on the basis of the
publisher-subscriber principle, being designed fully pipelined with lowest
processing overhead and communication latency in the cluster. In this paper, we
report the latest measurements where this framework has been operated on five
different sites over a global north-south link extending more than 10,000 km,
processing a ``real-time'' data flow.Comment: 8 pages 4 figure
When Things Matter: A Data-Centric View of the Internet of Things
With the recent advances in radio-frequency identification (RFID), low-cost
wireless sensor devices, and Web technologies, the Internet of Things (IoT)
approach has gained momentum in connecting everyday objects to the Internet and
facilitating machine-to-human and machine-to-machine communication with the
physical world. While IoT offers the capability to connect and integrate both
digital and physical entities, enabling a whole new class of applications and
services, several significant challenges need to be addressed before these
applications and services can be fully realized. A fundamental challenge
centers around managing IoT data, typically produced in dynamic and volatile
environments, which is not only extremely large in scale and volume, but also
noisy, and continuous. This article surveys the main techniques and
state-of-the-art research efforts in IoT from data-centric perspectives,
including data stream processing, data storage models, complex event
processing, and searching in IoT. Open research issues for IoT data management
are also discussed
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