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NSF Workshop on Bridging Gap Between Wireless Networking Technologies and Advances in Physical Layer

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NSF Workshop on Bridging Gap Between Wireless Networking Technologies and Advances in Physical Layer Breakout Session 3 – PowerPoint PPT presentation

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Title: NSF Workshop on Bridging Gap Between Wireless Networking Technologies and Advances in Physical Layer


1
NSF Workshop on Bridging Gap Between Wireless
Networking Technologies and Advances in Physical
Layer
  • Breakout Session 3

2
Participants
  • Mario Gerla, Michael Honig, Tom Hou, Vijay Kumar,
    Tom Luo, Narayan Mandayam, Madhav Marathe, Anna
    Scaglione, Kang Shin, R Srikant, Aravind
    Srinivasan, Tan Wong, Lizhong Zheng

3
Summary
  • A number of advances are being made at creating
    new and more realistic models at PHY layer
  • E.g. DMT models that quantify reliability rate
    trade-off
  • New technologies in form of Cognitive Radios,
    MIMO radios and Cooperative communication will
    likely result in new PHY layer abstractions
  • Current algorithmic/optimization methods often do
    not use the new models
  • Tradeoff between realistic models and tractable
    models
  • New techniques in algorithm theory and
    combinatorial optimization need to be developed
  • Higher layers can benefit from an understanding
    of the PHY layer

4
PHY layer models 1
  • Holistic view of control and data needs to be
    taken
  • New and more realistic models at PHY layer are
    now available
  • E.g. what is the networking viewpoint on the
    Diversity-Multiplexing Gain Tradeoff, for
    wireless multihop networks ?
  • Layered approach should be maintained to the
    extent possible interfaces need to be created to
    expose information between layers for cross layer
    optimization
  • Distinguish between models versus metrics

5
PHY Layer Models 2
  • New technologies such as cognitive radios are
    currently being developed. PHY level abstractions
    for these new technologies would provide the
    first step to more realistic protocol design and
    algorithmic analysis

6
Issues in Optimization and Algorithms 1
  • Many problems are cast as mixed (continuous as
    well as discrete variables) non-convex programs
  • Very little work has been done in distributed
    optimization
  • Good working definitions of distributed
    algorithms
  • Robust Optimization algorithms should work when
    instances vary slightly, proof techniques should
    work when models are varied slightly
  • Fault Tolerant algorithms

7
Issues in Algorithms and Optimization 2
  • Algorithms and analysis based on simple
    interference models such as disk graphs should
    not be discarded off hand
  • Even though theorems might not extend, the proof
    techniques might still be extensible
  • Simple models are amenable to analysis and one
    needs to quantify the additional gains that can
    be made by using more complicated models
  • Generic algorithms algorithms work for all
    successively complicated models, analysis depends
    on the model at hand

8
Issues in Networking
  • Better systems and high level protocols can be
    built by understanding the PHY level abstractions
  • E.g. Cognitive radio helps reduce the
    interference and enrich topology options (such as
    TCP fairness)
  • New application areas such as Vehicular networks,
    Underwater networks, etc. require modifying PHY
    models
  • Spatial and temporal variation in usage of
    spectrum can be used for better spectrum
    utilization

9
Summary
  • A number of advances are being made at creating
    new and more realistic models at PHY layer
  • E.g. DMT models that quantify reliability rate
    trade-off
  • New technologies in form of Cognitive Radios,
    MIMO radios and Cooperative communication will
    likely result in new PHY layer abstractions
  • Current algorithmic/optimization methods often do
    not use the new models
  • Tradeoff between realistic models and tractable
    models
  • New techniques in algorithm theory and
    combinatorial optimization need to be developed
  • Identifying classes of integer programs and
    non-convex programs that can be solved
    efficiently exploiting the structure of the
    underlying problems

10
What are we asked to Cover 1
  • Comments on talks so far
  • Specific Comments on Talks
  • Important issues that are overlooked
  • For physical layer folks
  • what are other recent advances at physical layer,
    what are their impact on wireless networking,
    future
  • expected advances/breakthroughs at physical layer
    and how they will impact wireless networking
    research, where are the research gaps

11
What are we asked to Cover 2
  • Wireless networking folks
  • Current status (where we are now), future
    expectations on wireless networking and research
  • Challenges, desired technology advances/
    breakthrough from the physical layer, new
    advances needed from theoretical perspective
  • Algorithm design and optimization
  • Status and Open Problems
  • Advances/breakthrough at the physical layer, new
    challenging problems arising from future wireless
    networking, identify research gaps

12
Models
  • Realistic yet computationally tractable
  • Get provable bounds using realistic models
  • Recent techniques in optimization have not been
    exploited
  • Over head of managing additional parameters
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