Communication devices today are becoming ever more sophisticated and diverse, delivering a plethora of new services and applications. The last hop to the end user, a person or device, is increasingly being delivered wirelessly. This sophistication brings with it complexity, making conventional approaches to organisation, implementation and regulation increasingly inadequate. This is especially seen in the case of usage of the radio spectrum, which has manifested itself as a perceived a shortage of spectrum, but this shortage is mainly due to inadequate command and control regulation, and conventional technical understanding – studies have shown up to 90% of the radio spectrum remains idle in any one geographical location.
Spectrum is a very precious resource and thus underutilization of a large part of allocated spectrum is not affordable. The misconception of spectrum shortage might have grown because of existing regulatory policies of spectrum licensing. Hence, growing demands of spectra cannot be met if alternate regulatory schemes are not found. What is required is an approach where unlicensed users may operate in licensed spectra while accommodating the licensed/existing users at high priority. Thus the need was felt for new types of devices operating in unlicensed bands without causing interference to licensed users called primary users (PU).
The idea for cognitive radio has come out of the need to utilize the radio spectrum more efficiently, and to be able to maintain the most efficient form of communication for the prevailing conditions. By using the levels of processing that are available today, it is possible to develop a radio that is able to look at the spectrum, detect which frequencies are clear, and then implement the best form of communication for the required conditions. In this way cognitive radio technology is able to select the frequency band, the type of modulation, and power levels most suited to the requirements, prevailing conditions and the geographic regulatory requirements.
A Cognitive Radio may be defined as an intelligent wireless communication system that is aware of its surrounding environment, learns from the environment and adapts its internal states to statistical variations in the incoming RF stimuli by making corresponding changes in certain operating parameters in real time.
In general the cognitive radio may be expected to look at parameters such as channel occupancy, free channels, the type of data to be transmitted and the modulation types that may be used. It must also look at the regulatory requirements. In some instances it may be necessary to use a software defined radio, so that it can reconfigure itself to meet and achieve the optimal transmission technology for a given set of parameters. Accordingly Cognitive radio technology and software defined radio are often tightly linked.
The states in the above CR cycle defining the spectrum management process consists of following major steps:
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Spectrum Sensing: A CR user can only allocate an unused portion of the spectrum. Therefore, the CR user should continuously monitor the Radio Environment for the availability of free spectrum bands, capture their information, and then detect the spectrum holes.
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Spectrum Decision: Once the available spectra are identified, it is essential that CR users select the best available band according to their QoS requirements. Especially in CRAHNs, spectrum decision involves jointly undertaking spectrum selection and route formation.
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Spectrum Sharing: The transmissions of CR users should be coordinated by spectrum sharing functionality to prevent multiple users colliding in overlapping portions of the spectrum.
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Spectrum Mobility: If the specific portion of the spectrum in use is required by a PU, the communication must be switched to another vacant portion of the spectrum.
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Radio Environment: The idea of Radio Environment Maps (REMs) design is to decide what type information must be stored and how this would be available to the various radios (CR or otherwise). REM covers multi-domain environmental information such as geographical features, available services, spectral regulations, location of various entities of interest (radios, reflectors, obstacles) plus radio-equipment capability profiles, relevant policies and past experiences. The REM information can be updated with observations from CR nodes and disseminated throughout CR networks
Authors: Tarun, Shubham and Pankaj