Beyond Cognitive Radio:Lower Layer Protocols

Venu Veeravalli

Yingbin Liang

What’s Special about Cognitive Radio Network

Network Structures:

- Ad hoc vs Cellular

- Network with infrastructures- Research are applicable to cellular networks

How is it different from existing WiFi

- Cognition

- WiFi is not aware of environment

Broader View

Broader View of Cognitive Radio- not just sensing and interference avoidance

- Not necessarily primary and secondary, can be certain networks with open resources with some rules setting up for it

- Cognition: learn environment and act

Learning

What should we learn online

- traffic models of coexisiting networks

- learning transmission environment/channel;

- extrinsic interference environment

- power levels; modulations

What a priori knowledge should/could be available

- database

- power level

- codebook and modulation scheme

Learning

Metrics for Learning:

- bits/sec/Hz/sqm

- packet success rate

- connection failure

- to what extend that other users is not affected

- how to translate higher level metrics to lower level

Future Topics

How to incorporate and exploit information (phy/mac)

- depends on network structure

- adaptive transmission based on environment and constraints

- adaption of power, bandwidth, modulation

Questions to Be Addressed

How to improve sensing robustness, and how to trade off between robustness and overhead in cooperative sensing?

How to take into account geographical locations of radios to improve channel selection and access efficiency?

How to estimate and exploit time-varying fading channel state for better channel selection and access?

How to apply information theoretic insights to improve interference control and mitigation?

How to apply PHY insights for small networks to the design of large cognitive networks?

What are reasonable models for node mobility in cognitive networks, and how to design networks with node mobility?

How to optimally exploit feedback from networks