Fundamentals of Cognitive Radio Networks

Michał Pawłowski

Contents

1. Motivation behind Cognitive Radio2. Spectrum Sharing3. Cooperative Spectrum Sensing4. Routing5. Artificial Intelligence Methods in CR

Motivation behind CR

With the growing number of wireless devices and increased spectrum occupancy, the unlicensed spectrum is getting scarce. In addition large

portion of licensed spectrum is underutilized. CR was created to solve this problem, by exploiting the existence of spectrum holes. Unlicensed users using CRs (Secondary Users), are aware of their spectrum environments

and change their transmission and reception parameters to avoid interference with licensed spectrum users (Primary Users).

Motivation behind CR (2)

In addition to maximizing the efficiency of spectrum usage, CR's adaptation engine is supposed to improve wireless communication as a whole. That includes minimizing BER, maximizing data throughput

and reducing power consumption.

To achieve these goals, cognitive radio optimizes

following parameters:

Motivation behind CR (3)

What differs CR from software-defined radio is ability to self-reconfigure. Moreover, using artificial intelligence methods, CR is able to learn

from environment observation and previously made decisions.

Spectrum Sharing in CRN

Spectrum Sensing – CR detects unused spectrum and determines the method of sharing it without interfering PUs.

Spectrum Analysis – Information collected by Spectrum Sensing are used to schedule spectrum access by unlicensed users (SUs).

Spectrum Access – Spectrum holes are accessed by SU. In order to avoid collisions with PU and other SUs, cognitive medium access control (MAC) protocol is used.

Spectrum Mobility – CR have to ensure that data transmission can continue in case of changing used frequency.

Cooperative Spectrum Sensing

Since spectrum sensing performed by single CR user may be unreliable, SUs are able to share sensing results with their neighbours or fusion centre to improve PU signal detection.

The cooperative spectrum sensing architecture may be either centralized or distributed. In centralized cooperative spectrum sensing SUs sense the target channels and report the sensing results to the central controller, whereas in distributed approach SUs exchange the sensing results among each other, and the decision on spectrum access by each unlicensed user is made locally.

Cooperative Spectrum Sensing

For example, in this picture SU1 may not be able to detect transmission from PU L1 due to channel fading. However, if SU2 senses the spectrum and reports the presence of PU L1 to the controller, SU2 can be notified by this controller and will defer its transmission to avoid any interference to the PUs .

Routing

Due to presence of PUs in the network, SU must use appropriate routing algorithm. For example, SU1 may require to use the route through users 2 and 4 to the destination SU5

(instead of route through SU3). This is because using the shorter route may interfere PU.

Artificial intelligence in CR

The cognitive adaptation engine is at the core of the cognitive radio. It is the intelligence that drives the decision-making process. That's why CR needs to have the ability to learn and adapt their wireless transmission according to the ambient radio environment.

There are three major categories of intelligent algorithm used in CR: Machine learning supervised learning unsupervised learning reinforcement learning Genetic algorithm Fuzzy logic

These algorithms are used to observe the state of the wireless environment and build knowledge about the environment. This knowledge is used by a CR to adapt its decision on spectrum access and to improve performance of connection.

References

[1] Cognitive Radio Communications and Networks, Principles and Practice, ELSEVIER, Alexander M. Wyglinski, Maziar Nekovee, Y. Thomas Hou.

[2] Dynamic spectrum access and management in cognitive radio networks, CAMBRIDGE UNIVERSITY PRESS, Ekram Hossain, Dusit Niyato, Zhu Han

[3] Cognitive Radio Network Architecture: Part I – General Structure, K. –C. Chen, Y. –J. Peng, N. Prasad, Y. –C. Liang, S. Sun

[4] Spectrum Sharing in Cognitive Radio Networks, H.Feizresan, M. J. Omidi

Thank you!