TY - JOUR
AU - 
AB - Chapter 9 Chapter 0 Data Mining Applied to Cognitive Radio Systems Lilian Freitas, Yomara Pires, Jefferson Morais, João Costa and Aldebaro Klautau Additional information is available at the end of the chapter http://dx.doi.org/10.5772/51824 1. Introduction Cognitive radio (CR) is a novel technology that allows to improve spectrum utilization by enabling opportunistic access to the licensed spectrum band by unlicensed users [2]. This is accomplished through heterogeneous architectures and techniques of dynamic spectrum access. The CR is defined as an intelligent wireless communication system that is aware of its environment and is capable to learn from the environment and adapt its transmission parameters, such as frequency, modulation, transmission power and communication protocols [14]. An important aspect of a cognitive radio is spectrum sensing [10], which involves two main tasks: signal detection and modulation classification. Signal detection refers to detection of unused spectrum (spectrum holes). It is a simpler task and can be done, for example, by comparing the energy in the frequency band of interest with a predetermined threshold. This task is important so that the unlicensed users do not cause interference to licensed users. Modulation classification consists in automatically identifying the modulation scheme (PSK, FM, QAM, etc) of a 
TI - Data Mining Applied to Cognitive Radio Systems
JO - Advances in Data Mining Knowledge Discovery and Applications
DO - 10.5772/51824
DA - 2012-09-12
UR - https://www.deepdyve.com/lp/unpaywall/data-mining-applied-to-cognitive-radio-systems-fn0M3MBpjk
DP - DeepDyve
ER -