12,891 research outputs found
Fronthaul-Constrained Cloud Radio Access Networks: Insights and Challenges
As a promising paradigm for fifth generation (5G) wireless communication
systems, cloud radio access networks (C-RANs) have been shown to reduce both
capital and operating expenditures, as well as to provide high spectral
efficiency (SE) and energy efficiency (EE). The fronthaul in such networks,
defined as the transmission link between a baseband unit (BBU) and a remote
radio head (RRH), requires high capacity, but is often constrained. This
article comprehensively surveys recent advances in fronthaul-constrained
C-RANs, including system architectures and key techniques. In particular, key
techniques for alleviating the impact of constrained fronthaul on SE/EE and
quality of service for users, including compression and quantization,
large-scale coordinated processing and clustering, and resource allocation
optimization, are discussed. Open issues in terms of software-defined
networking, network function virtualization, and partial centralization are
also identified.Comment: 5 Figures, accepted by IEEE Wireless Communications. arXiv admin
note: text overlap with arXiv:1407.3855 by other author
A Project Based Approach to Statistics and Data Science
In an increasingly data-driven world, facility with statistics is more
important than ever for our students. At institutions without a statistician,
it often falls to the mathematics faculty to teach statistics courses. This
paper presents a model that a mathematician asked to teach statistics can
follow. This model entails connecting with faculty from numerous departments on
campus to develop a list of topics, building a repository of real-world
datasets from these faculty, and creating projects where students interface
with these datasets to write lab reports aimed at consumers of statistics in
other disciplines. The end result is students who are well prepared for
interdisciplinary research, who are accustomed to coping with the
idiosyncrasies of real data, and who have sharpened their technical writing and
speaking skills
Curriculum Guidelines for Undergraduate Programs in Data Science
The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program
met for the purpose of composing guidelines for undergraduate programs in Data
Science. The group consisted of 25 undergraduate faculty from a variety of
institutions in the U.S., primarily from the disciplines of mathematics,
statistics and computer science. These guidelines are meant to provide some
structure for institutions planning for or revising a major in Data Science
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