A cognitive radio is a transceiver which automatically changes its transmission or reception parameters so wireless communicationsmay have spectrum agility to select available wireless channels opportunistically. This process is also known as dynamic spectrum management. A cognitive radio, as defined by the researchers at Virginia Polytechnic Institute and State University, is “a software defined radio with a cognitive engine brain”.
In response to the operator’s commands, the cognitive engine is capable of configuring radio-system parameters. These parameters include “waveform, protocol, operating frequency, and networking”. It functions as an autonomous unit in the communications environment, exchanging information about the environment with the networks it accesses and other CRs. A CR “monitors its own performance continuously”, in addition to “reading the radio’s outputs”; it then uses this information to “determine the RF environment, channel conditions, link performance, etc.”, and adjusts the “radio’s settings to deliver the required quality of service subject to an appropriate combination of user requirements, operational limitations, and regulatory constraints”. These processes have been described as “reading the radio’s meters and turning the radio’s knobs”.
The concept of cognitive radio was first proposed by Joseph Mitola III in a seminar at KTH (the Royal Institute of Technology in Stockholm) in 1998 and published in an article by Mitola and Gerald Q. Maguire, Jr. in 1999. It was a novel approach in wireless communications, which Mitola later described as:
The point in which wireless personal digital assistants (PDAs) and the related networks are sufficiently computationally intelligent about radio resources and related computer-to-computer communications to detect user communications needs as a function of use context, and to provide radio resources and wireless services most appropriate to those needs.
Cognitive radio is considered as a goal towards which a software-defined radio platform should evolve: a fully reconfigurable wireless transceiver which automatically adapts its communication parameters to network and user demands.
Regulatory bodies in the world (including the Federal Communications Commission in the United States and Ofcom in the United Kingdom) found that most radio frequency spectrum was inefficiently utilized. Cellular network bands are overloaded in most parts of the world, but other frequency bands (such as military, amateur radio and paging frequencies) are insufficiently utilized. Independent studies performed in some countries confirmed that observation, and concluded that spectrum utilization depends on time and place. Moreover, fixed spectrum allocation prevents rarely used frequencies (those assigned to specific services) from being used, even when any unlicensed users would not cause noticeable interference to the assigned service. Therefore, regulatory bodies in the world have been considering to allow unlicensed users in licensed bands if they would not cause any interference to licensed users. These initiatives have focused cognitive-radio research on dynamic spectrum access.
The first phone call over a cognitive-radio network was made on Monday, 11 January 2010 in the Centre for Wireless Communications at the University of Oulu using CWC’s cognitive-radio network, CRAMNET (Cognitive Radio Assisted Mobile Ad Hoc Network), which was developed by CWC researchers.
Depending on transmission and reception parameters, there are two main types of cognitive radio:
- Full Cognitive Radio (Mitola radio), in which every possible parameter observable by a wireless node (or network) is considered.
- Spectrum-Sensing Cognitive Radio, in which only the radio-frequency spectrum is considered.
Other types are dependent on parts of the spectrum available for cognitive radio:
- Licensed-Band Cognitive Radio, capable of using bands assigned to licensed users (except for unlicensed bands, such as the U-NIIband or the ISM band. The IEEE 802.22 working group is developing a standard for wireless regional area network (WRAN), which will operate on unused television channels.
- Unlicensed-Band Cognitive Radio, which can only utilize unlicensed parts of the radio frequency (RF) spectrum. One such system is described in the IEEE 802.15 Task Group 2 specifications, which focus on the coexistence of IEEE 802.11 andBluetooth.
- Spectrum mobility: Process by which a cognitive-radio user changes its frequency of operation. Cognitive-radio networks aim to use the spectrum in a dynamic manner by allowing radio terminals to operate in the best available frequency band, maintaining seamless communication requirements during transitions to better spectrum.
- Spectrum sharing: Provides a fair spectrum-scheduling method; a major challenge to open-spectrum usage. It may be regarded as similar to generic media access control (MAC) problems in existing systems.
Although cognitive radio was initially thought of as a software-defined radio extension (full cognitive radio), most research work focuses on spectrum-sensing cognitive radio (particularly in the TV bands). The chief problem in spectrum-sensing cognitive radio is designing high-quality spectrum-sensing devices and algorithms for exchanging spectrum-sensing data between nodes. It has been shown that a simple energy detector cannot guarantee the accurate detection of signal presence, calling for more sophisticated spectrum sensing techniques and requiring information about spectrum sensing to be regularly exchanged between nodes. Increasing the number of cooperating sensing nodes decreases the probability of false detection.
Filling free RF bands adaptively, using OFDMA, is a possible approach. Timo A. Weiss and Friedrich K. Jondral of the University of Karlsruhe proposed a spectrum pooling system, in which free bands (sensed by nodes) were immediately filled by OFDMA subbands. Applications of spectrum-sensing cognitive radio include emergency-network and WLAN higher throughput and transmission-distance extensions. The evolution of cognitive radio toward cognitive networks is underway; the concept of cognitive networks is to intelligently organize a network of cognitive radios.
- Spectrum sensing: Detecting unused spectrum and sharing it, without harmful interference to other users; an important requirement of the cognitive-radio network to sense empty spectrum. Detecting primary users is the most efficient way to detect empty spectrum. Spectrum-sensing techniques may be grouped into three categories:
- Transmitter detection: Cognitive radios must have the capability to determine if a signal from a primary transmitter is locally present in a certain spectrum. There are several proposed approaches to transmitter detection:
- Cooperative detection: Refers to spectrum-sensing methods where information from multiple cognitive-radio users is incorporated for primary-user detection
- Interference-based detection
- Power Control: Power control is used for both opportunistic spectrum access and spectrum sharing CR systems for finding the cut-off level in SNR supporting the channel allocation and imposing interference power constraints for the primary user’s protection respectively. In  a joint power control and spectrum sensing is proposed for capacity maximization.
- Spectrum management: Capturing the best available spectrum to meet user communication requirements, while not creating undue interference to other (primary) users. Cognitive radios should decide on the best spectrum band (of all bands available) to meetquality of service requirements; therefore, spectrum-management functions are required for cognitive radios. Spectrum-management functions are classified as:
- Spectrum analysis
- Spectrum decision
The practical implementation of spectrum-management functions is a complex and multifaceted issue, since it must address a variety of technical and legal requirements. An example of the former is choosing an appropriate sensing threshold to detect other users, while the latter is exemplified by the need to meet the rules and regulations set out for radio spectrum access in international (ITU radio regulations) and national (telecommunications law) legislation.
Cognitive radio (CR) versus intelligent antenna (IA)
An intelligent antenna (or smart antenna) is an antenna technology that uses spatial beam-formation and spatial coding to cancel interference; however, it requires an intelligent multiple- or cooperative-antenna array. On the other hand, cognitive radio allows user terminals to sense whether a portion of the spectrum is being used to share spectrum with neighbor users. The following table compares the two:
|Point||Cognitive radio (CR)||Intelligent antenna (IA)|
|Principal goal||Open spectrum sharing||Ambient spatial reuse|
|Interference processing||Avoidance by spectrum sensing||Cancellation by spatial pre/post-coding|
|Key cost||Spectrum sensing and multi-band RF||Multiple- or cooperative-antenna arrays|
|Challenging algorithm||Spectrum management tech||Intelligent spatial beamforming/coding tech|
|Applied techniques||Cognitive software radio||Generalized dirty-paper and Wyner-Ziv coding|
|Basement approach||Orthogonal modulation||Cellular based smaller cell|
|Competitive technology||Ultra-wideband for greater band utilization||Multi-sectoring (3, 6, 9, so on) for higher spatial reuse|
|Summary||Cognitive spectrum-sharing technology||Intelligent spectrum reuse technology|
CR can sense its environment and, without the intervention of the user, can adapt to the user’s communications needs while conforming to FCC rules in the United States. In theory, the amount of spectrum is infinite; practically, for propagation and other reasons it is finite because of the desirability of certain spectrum portions. Assigned spectrum is far from being fully utilized, and efficient spectrum use is a growing concern; CR offers a solution to this problem. A CR can intelligently detect whether any portion of the spectrum is in use, and can temporarily use it without interfering with the transmissions of other users. According to Bruce Fette, “Some of the radio’s other cognitive abilities include determining its location, sensing spectrum use by neighboring devices, changing frequency, adjusting output power or even altering transmission parameters and characteristics. All of these capabilities, and others yet to be realized, will provide wireless spectrum users with the ability to adapt to real-time spectrum conditions, offering regulators, licenses and the general public flexible, efficient and comprehensive use of the spectrum”.
The success of the unlicensed band in accommodating a range of wireless devices and services has led the FCC to consider opening further bands for unlicensed use. In contrast, the licensed bands are underutilized due to static frequency allocation. Realizing that CR technology has the potential to exploit the inefficiently utilized licensed bands without causing interference to incumbent users, the FCC released a Notice of Proposed Rule Making which would allow unlicensed radios to operate in the TV-broadcast bands. The IEEE 802.22 working group, formed in November 2004, is tasked with defining the air-interface standard for wireless regional area networks (based on CR sensing) for the operation of unlicensed devices in the spectrum allocated to TV service.
- Channel allocation schemes
- Channel-dependent scheduling
- Cognitive network
- Cooperative wireless communications
- Dirty paper coding (DPC)—Pre-cancels the known interference signal at the transmitter without additional transmitter power (regardless of interference type), which can be used to optimize cognitive wireless network channels.
- Intelligent antenna (IA)—Antenna technology which exploits electronic intelligence to enhance the performance of radio communication systems, as well as being used to enhance the performance of freeband systems. IA-based multiple antenna terminals enable multiple radio links to communicate simultaneously (up to the number of embedded multiple antennas).
- Link adaptation
- LTE Advanced
- Radio resource management (RRM)
- Software-defined radio
- Ultra Wideband
- Wipro Technologies
- ^ a b home [CWT Cognitive Radios]
- ^ a b “Software-Defined Radio. White Paper. A Technology Overview.(2002, August). pp 1–10.”. Wipro Technologies.
- ^ IEEE Xplore – Login
- ^ IEEE Spectrum: The End of Spectrum Scarcity
- ^ Václav Valenta et al., Survey on Spectrum Utilization in Europe: Measurements, Analyses and Observations
- ^ IEEE Xplore – Login
- ^ a b IEEE Xplore – Login
- ^ http://www.cwc.oulu.fi/home/files/news/CRAMNET_1.pdf
- ^ http://www.cwc.oulu.fi/home/files/news/CRAMNET_3.pdf
- ^ J. Mitola III and G. Q. Maguire, Jr., “Cognitive radio: making software radios more personal,” IEEE Personal Communications Magazine, vol. 6, nr. 4, pp. 13–18, Aug. 1999
- ^ S. Haykin, “Cognitive Radio: Brain-empowered Wireless Communications”, IEEE Journal on Selected Areas of Communications, vol. 23, nr. 2, pp. 201–220, Feb. 2005
- ^ IEEE 802.22
- ^ Carl, Stevenson; G. Chouinard, Zhongding Lei, Wendong Hu, S. Shellhammer & W. Caldwell (2009-01). “IEEE 802.22: The First Cognitive Radio Wireless Regional Area Networks (WRANs) Standard = IEEE Communications Magazine“. IEEE Communications Magazine (US: IEEE) 47 (1): 130–138.DOI:10.1109/MCOM.2009.4752688.
- ^ IEEE 802.15.2
- ^ http://ieeexplore.ieee.org/iel5/4234/30631/01413630.pdf?tp=&arnumber=1413630&isnumber=30631
- ^ Ian F. Akyildiz, W.-Y. Lee, M. C. Vuran, and S. Mohanty, “NeXt Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A Survey,” Computer Networks (Elsevier) Journal, September 2006. 
- ^ Cognitive Functionality in Next Generation Wireless Networks
- ^ Z. Li, F.R. Yu, and M. Huang, “A Distributed Consensus-Based Cooperative Spectrum Sensing in Cognitive Radios,” IEEE Trans. Vehicular Technology, vol. 59, no. 1, pp. 383–393, Jan. 2010.
- ^ F. Foukalas et. al Joint optimal power allocation and sensing threshold selection for SU’s capacity maximisation in SS CRNS
- ^ CEPT Report 159 on technical and operational requirements for Cognitive Radio operation in TV White Spaces
- ^ European Research project on spectrum access policies for Cognitive Radio
- ^ Dr.Bruce.Fette. (2004, October). Cognitive Radio Shows Great Promise.COTS Journal, [online].pp.1–5. Available:http://www.cotsjournalonline.com/home/article.php?id=100206
- ^ Carlos Cordeiro, Kiran Challapali, and Dagnachew Birru. Sai Shankar N. IEEE 802.22: An Introduction to the First Wireless Standard based on Cognitive Radios JOURNAL OF COMMUNICATIONS, VOL. 1, NO. 1, APRIL 2006
- ^ Natasha Devroye, Patrick Mitran and V. Tarokh, Limits on Communication in a Cognitive Radio Channel,” IEEE Communications Magazine, pp. 44–49, June 2006.
- IEEE DYSPAN Standards Committee (Dynamic Spectrum Access Networks), formerly IEEE Standards Coordinating Committee 41 (SCC41)
- Cognitive Functionality in Next Generation Wireless Networks
- A very rich collection of Cognitive Radio and Software-Defined Radio references – WCSP Group – University of South Florida (USF)
- A collaborative website about SDR and cognitive radio
- Adaptive Ad-hoc Freeband Communications – Dutch research project aiming to realize ambient, intelligent radio communications.
- Berkeley Wireless Research Center Cognitive Radio Workshop – first workshop on cognitive radio; its focus was mainly on research issues in topic
- Wimax and Cognitive Radio Research Group
- Center for Wireless Telecommunications (CWT), Virginia Tech
- Cognitive Radio Blog
- Cognitive Radio Information Center – SCC41 Reference Page
- Joseph Mitola III, Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio, Royal Institute of Technology (KTH) Stockholm, Sweden, 8 May 2000, ISSN 1403 – 5286. – PhD dissertation in which cognitive radio architecture was first defined in detail
- Cognitive Radio Technologies Proceeding of Federal Communications Commission – Federal Communications Commission rules on cognitive radio
- Scientific American Magazine (March 2006 Issue) Cognitive Radio
- Stefan Mangold on Cognitive Radio
- WWRF WG6 – Cognitive Wireless Networks and Systems
- CrownCom – International Conference on Cognitive Radio Oriented Wireless Networks and Communications
- IEEE COMSOC TCCN – The Technical Committee on Cognitive Networks of IEEE Communications Society
- IEEE DySPAN Conference
- Alcatel Lucent Chair on Flexible Radio
- European COST Action IC0905 TERRA on Techno-Economic Regulatory Framework for Cognitive Radio/Software Defined Radio (COST-TERRA)