Cognitive Radio Technologies:
Services and Software for Intelligent Wireless Networks
Technology
Non-Collaborative Distributed Network Optimization
Leveraging our ground-breaking research into
game theoretic analysis and design of cognitive
radio net-works, CRT has developed a suite of
distributed non-collaborative algorithms which
converge to stable radio resource allocations (e.g.,
power, frequency, modulation, beam patterns)
which optimize network performance without
requiring a centralized controller or coordination
between distributed controllers.
Highly Scalable
Because our algorithms work with instead of
against network interactions, there is no need to
  • coordinate adaptations between controllers
  • distribute observations between controllers
  • message a centralized controller
  • distribute clocks
All this adds up to networks whose complexity is
in-dependent of scale (our basic ad-hoc suite) or
scales linearly with network density (our traffic
re-active and beamforming suites).
For our algorithms, selfishness is
socially optimal

Widely Applicable
Because our algorithms encompass all traditional PHY resources, e.g., channel,
power, modulation, transmit/receive beam patterns, and have been designed to
accommodate a wide variety of scenarios, e.g., MIMO systems, subcarrier allocation,
our algorithms can optimize networks running a wide variety of waveforms
including:802.11a/b/g/n, Mobile/Fixed WiMAX, 802.22, LTE, UMB, TD-SCDMA, and
Zigbee. This is enhanced by our commitment to
portable software design.

Dramatic Improvements in Network Performance
Achieve pre-planned like performance, but optimized in real-time to changing network
conditions.
The following are some of the background publications on which this software
package is based.

Chapters 5, 6 and 7 in J. Neel, "Analysis and Design of Cognitive Radio Networks and Distributed
Radio Resource Management Algorithms," PhD Dissertation Virginia Tech 2006.

(pdf) J. Neel, J. Reed, "Performance of Distributed Dynamic Frequency Selection Schemes for
Interference Reducing Networks," Milcom 06.

(pdf) James Neel, "Synthetic Symmetry in Cognitive Radio Networks," SDR Forum Technical
Conference 2007.

(
paper) (presentation) James O. Neel (CRT),  Rekha Menon (Tyco Electronics), Allen B.
MacKenzie (VT), Jeffrey H. Reed, (CRT,VT), "Interference Reducing Networks" CrownCom07