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From:
Mariya Zheleva <[log in to unmask]>
Reply To:
Mariya Zheleva <[log in to unmask]>
Date:
Sat, 17 Dec 2016 06:01:12 -0500
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Apologies for cross-listing

========================================
IEEE DySPAN 2017
========================================
*IEEE DySPAN'17 TUTORIALS*
6 March 2017
Baltimore, MD, USA
http://dyspan2017.ieee-dyspan.org/program/tutorials

IEEE DySPAN'17 will host five tutorials. From spectrum access systems to
emerging research problems and software tools to tackle them. More
information below and on our Tutorials webpage
http://dyspan2017.ieee-dyspan.org/program/tutorials.

*Monday, March 6, 2017*
*8:00am-12:00pm*

   - Economics of Database-Assisted Spectrum Sharing
   - Spectrum Access Systems

*1:30pm-5:30pm*

   - Impact of RF Front End Nonlinearity on Dynamic Spectrum Access Networks
   - Open Source Signal Processing in the GNU Radio Ecosystem
   - Wireless Prototyping and Implementation with USRP and Other
   Software-defined Radios using MATLAB and Simulink

*Economics of Database-Assisted Spectrum Sharing*
March 6, 2017, 8:00am-12:00pm (Noon)
*Organizers: *Jianwei Huang, Lin Gao, Yuan Luo, Chinese University of Hong
Kong, Hong Kong, China

Database-assisted spectrum sharing network is a promising paradigm of
dynamic spectrum sharing, and can effectively improve the spectrum
utilization and alleviate the spectrum scarcity, via the centralized
control of databases residing in the cloud. In this tutorial, we discuss
the business modeling for database-assisted spectrum sharing network, which
is very important for the wide commercialization of this promising
technology. Motivated by several recent business practices, we will discuss
two types of different business models: spectrum market and information
market. In the spectrum market model, spectrum licensees, through spectrum
brokers acted by databases, lease the under-utilized (licensed) spectrum to
unlicensed wireless devices for secondary utilization. In the information
market model, databases sell the advanced information regarding
(unlicensed) spectrum to unlicensed wireless devices in order to enhance
the secondary spectrum utilization performance. We will discuss the trading
mechanism for both market models, and evaluate the feasibility and
performance of both models through theoretical and numerical studies. This
tutorial is partially based on the book "Economics of Database-Assisted
Spectrum Sharing" co-authored by the tutorial speakers (
http://www.springer.com/la/book/9783319432304).

*Spectrum Access Systems*
March 6, 2017, 8:00am-12:00pm (Noon)
*Organizers:* Eric Nelson (NTIA), Andrew Clegg (Google), Preston Marshall
(Google), Kurt Schaubach (Federated Wireless), Mark Gibson (Comsearch), and
Seppo Yrjölä (Nokia)

The first implementation of large-scale multi-tiered dynamic spectrum
sharing is getting under way in the U.S. The FCC has authorized access to
the 3550-3700 MHz band under the Citizens Broadband Radio Service (CBRS),
where incumbents will share spectrum with underlay services whose spectrum
authorizations will be managed by a Spectrum Access System (SAS). This is
the first example of SAS-managed spectrum sharing, and expanding the SAS
concept to other bands has already been proposed.

The purpose of this session is to cover:

   - The policy origin of multi-tiered SAS-managed spectrum sharing;
   - An overview of the SAS rules and implementation details in the CBRS
   band
   - The regulator’s view of SAS certification and evolution
   - SAS-managed sharing opportunities outside the U.S.
   - Challenges of shared spectrum access under SAS control

The tutorial will be comprised of individual talks, and a panel discussion.
More information here
http://dyspan2017.ieee-dyspan.org/program/tutorials/ieee-dyspan-2017-tutorial-spectrum-access-systems



*Impact of RF Front End Nonlinearity on Dynamic Spectrum Access Networks*
March 6, 2017, 1:30am-5:30pm
*Organizers: *Jeffrey H. Reed, Aditya V. Padaki and Vuk Marojevic, Virginia
Tech, USA

Radio frequency (RF) front ends are nonlinear systems that have nonlinear
frequency response that can impair receiver performance by harmful adjacent
channel interference in non-intuitive ways. In dynamic spectrum access
scenarios, where heterogeneous transceivers access portions of shared
spectrum, communications performance can be compromised because of poor RF
selectivity. This tutorial addresses the technological challenges in
receiver-centric wireless network design and develops an analytical
framework for quantifying the implications of RF front end nonlinearity on
network performance, utilization, and fairness. This tutorial will further
provide deep technical insights into nonlinear adjacent channel
interference management avoidance, and cancellation for next generation
dynamic spectrum access networks.

The tutorial is organized in three parts. The first part introduces the
fundamental analytical framework for characterizing and quantifying the
impact of RF front end nonlinearity on dynamic spectrum access system
performance. We present model specific spectral characterization to
describe the phenomena of third order intermodulation, cross-modulation and
desensitization of the receiver front-end nonlinear distortion, necessary
for adjacent channel co-existence analysis. The second part presents a
comprehensive wireless network management framework and strategies that
account for the RF imperfections and diversity of heterogeneous wireless
devices. The third part establishes the fundamentals of nonlinear
interference between symbols of adjacent channels and addresses the
scalability and network level mechanisms for nonlinear adjacent channel
interference avoidance.

Example practical applications of the topics covered in this tutorial are
in the design of spectrum access schemes for the 3.5 GHz band and the
recent efforts to open AWS-3 band for sharing in the US, but the same
principles apply to any spectrum sharing band. Overall, this tutorial
introduces the fundamentals of receiver-centric analysis, frameworks and
algorithms critical to the design, development, testing and successful
deployment of next generation dynamic spectrum access networks.

*Open Source Signal Processing in the GNU Radio Ecosystem*
March 6, 2017, 1:30am-5:30pm
*Organizers: *Nathan West (Oklahoma State University, Naval Research
Laboratory) and Tim O’Shea (Virginia Tech, DEEPSIG Inc)

This tutorial will provide a brief introduction to GNU Radio and the
ecosystem surrounding it, demonstrate basic spectrum sensing and packet
communications with gnuradio, and introduce a number of the key tools and
resources from the open source software radio community. We will advance
through the tutorial from basics of getting up and running in GNU Radio for
performing spectrum sensing and packet communications, through how to build
and implement custom blocks and out-of-tree modules, to how to accelerate
them, survey a number of modems and tools available from the community, and
then explore some of the emerging trends in heterogeneous processing with
dataflow graph compilers such as Tensorflow and explore their use in signal
processing as well as machine learning tasks in conjunction with GNU Radio.


*Wireless Prototyping and Implementation with USRP and Other
Software-defined Radios using MATLAB and Simulink*March 6, 2017,
1:30am-5:30pm

Engineers working on wireless systems face many technical challenges,
including capturing wireless signals, making custom measurements, and
performing filtering, correlation and demodulation on captured data. MATLAB
provides a flexible programming environment for digital signal processing
and analysis, and engineers can now connect MATLAB directly to radio
hardware like the USRP radios from Ettus Research. This capability allows
wireless engineers to locate signals and quickly test design ideas in
MATLAB with live RF sources.

This tutorial will demonstrate several core functions of the MATLAB suite
which support prototyping and implementation including: MATLAB functions
and Simulink blocks to connect to RTL-SDR, USRP and Zynq radios;
transmitting and receiving live RF signals; fixed-point receiver design;
hardware/software co-design for Zynq based radios; generating HDL code for
receiver algorithms and deploying them onto FPGA and Zynq based radios; and
examples of ADS-B and LTE.

-- 
Mariya Zheleva
Assistant Professor
Department of Computer Science
University at Albany, SUNY
http://www.cs.albany.edu/~mariya/ <http://cs.ucsb.edu/~mariya/>

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