Cognitive radio

A cognitive radio is a kind of two-way radio that automatically changes its transmission or reception parameters, in a way where the entire wireless communication network -- of which it is a node -- communicates efficiently, while avoiding interference with licensed or licensed exempt users. This alteration of parameters is based on the active monitoring of several factors in the external and internal radio environment, such as radio frequency spectrum, user behaviour and network state. 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".^[1]

History

The idea of cognitive radio was first presented officially by Joseph Mitola III in a seminar at KTH, The Royal Institute of Technology in Stockholm, in 1998, published later in an article by Mitola and Gerald Q. Maguire, Jr in 1999.^[2] It was a novel approach in wireless communications that 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.^[3]

It was thought of as an ideal goal towards which a software-defined radio platform should evolve: a fully reconfigurable wireless black-box that automatically changes its communication variables in response to network and user demands.

Regulatory bodies in various countries (including the Federal Communications Commission in the United States, and Ofcom in the United Kingdom) found that most of the radio frequency spectrum was inefficiently utilized.^[4] For example, cellular network bands are overloaded in most parts of the world, but many other frequency bands, such as military, amateur radio and paging frequencies are not. Independent studies performed in some countries confirmed that observation,^[5][6][7] and concluded that spectrum utilization depends strongly on time and place. Moreover, fixed spectrum allocation prevents rarely used frequencies (those assigned to specific services) from being used by unlicensed users, even when their transmissions would not interfere at all with the assigned service. This was the reason for allowing unlicensed users to utilize licensed bands whenever it would not cause any interference (by avoiding them whenever legitimate user presence is sensed). This paradigm for wireless communication is known as cognitive radio.

The first phone call over a cognitive radio network was made on Monday 11 January 2010 in Centre for Wireless Communications at University of Oulu using CWC's cognitive radio network CRAMNET (Cognitive Radio Assisted Mobile Ad Hoc Network), that has been developed solely by CWC researchers.^[8],^[9]

Terminology

Depending on the set of parameters taken into account in deciding on transmission and reception changes, and for historical reasons, we can distinguish certain types of cognitive radio. The main two are:

• Full Cognitive Radio ("Mitola radio"): in which every possible parameter observable by a wireless node or network is taken into account.^[10]
• Spectrum Sensing Cognitive Radio: in which only the radio frequency spectrum is considered.^[11]

Also, depending on the parts of the spectrum available for cognitive radio, we can distinguish:

• Licensed Band Cognitive Radio: in which cognitive radio is capable of using bands assigned to licensed users, apart from unlicensed bands, such as U-NII band or ISM band. The IEEE 802.22 working group is developing a standard for wireless regional area network (WRAN) which will operate in unused television channels.^[12][13]
• Unlicensed Band Cognitive Radio: which can only utilize unlicensed parts of radio frequency spectrum.^{[citation needed]} One such system is described in the IEEE 802.15 Task group 2 specification.^[14] which focuses on the coexistence of IEEE 802.11 and Bluetooth.^{[citation needed]}

Technology

Although cognitive radio was initially thought of as a software-defined radio extension (Full Cognitive Radio), most of the research work is currently focusing on Spectrum Sensing Cognitive Radio, particularly in the TV bands. The essential problem of Spectrum Sensing Cognitive Radio is in designing high quality spectrum sensing devices and algorithms for exchanging spectrum sensing data between nodes. It has been shown^[15] 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 exchanged between nodes regularly. Increasing the number of cooperating sensing nodes decreases the probability of false detection.^[16]

Filling free radio frequency 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^[7] in which free bands sensed by nodes were immediately filled by OFDMA subbands.

Applications of Spectrum Sensing Cognitive Radio include emergency networks and WLAN higher throughput and transmission distance extensions.

Evolution of Cognitive Radio toward Cognitive Networks is under process, in which Cognitive wireless mesh network (e.g. CogMesh) is considered as one of the enabling candidates aiming at realizing this paradigm change.

Main functions

The main functions of Cognitive Radios are:^[17][18]

• Spectrum Sensing: detecting the unused spectrum and sharing it without harmful interference with other users. It is an important requirement of the Cognitive Radio network to sense spectrum holes. Detecting primary users is the most efficient way to detect spectrum holes. Spectrum sensing techniques can be classified 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 approaches proposed:
    • matched filter detection
    • energy detection
    • cyclostationary feature detection
  • Cooperative detection: refers to spectrum sensing methods where information from multiple Cognitive radio users are incorporated for primary user detection.
  • Interference based detection.

• 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 to meet the Quality of service requirements over all available spectrum bands, therefore spectrum management functions are required for Cognitive radios. These management functions can be classified as:
  • spectrum analysis
  • spectrum decision

The practical implementation of spectrum management functions is a very complex and multifaceted issue in itself, given that it has to address a mixture of technical and legal requirements. An example of the former is chosing 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, etc.) legislation^[19][20].

• Spectrum Mobility: is defined as the process when a cognitive radio user exchanges its frequency of operation. Cognitive radio networks target to use the spectrum in a dynamic manner by allowing the radio terminals to operate in the best available frequency band, maintaining seamless communication requirements during the transition to better spectrum.

• Spectrum Sharing: providing the fair spectrum scheduling method. One of the major challenges in open spectrum usage is the spectrum sharing. It can be regarded to be similar to generic media access control MAC problems in existing systems

Cognitive radio (CR) versus intelligent antenna (IA)

Intelligent antenna (or smart antenna) is antenna technology using spatial beamforming and spatial coding to cancel interference; however, it requires intelligent multiple or cooperative antenna array. On the other hand, cognitive radio (CR) allows user terminals to sense whether a portion of the spectrum is being used or not, in order to share the spectrum among neighbor users. The following table compares the different points between two advanced approaches for the future wireless systems: Cognitive radio (CR) vs. Intelligent antenna (IA).

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 the higher band utilization	Multi-sectoring (3, 6, 9, so on) for higher spatial reuse
Summary	Cognitive spectrum sharing technology	Intelligent spectrum reuse technology

Description

In response to the operator's commands, the cognitive engine is capable of configuring the radio system parameters. These parameters include "waveform, protocol, operating frequency, and networking".^[21] It functions as an autonomous unit in the communication environment and frequently exchanges information about the environment with the networks it is able to access as well as with other CRs (Wipro Technologies, 2002).^[21]. 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". ^[1]

Practical application

CR can sense its environment and without the intervention of the user can adapt to the users communication needs while conforming to FCC rules. Conceptually, the amount of spectrum is infinite, practically for propagation and other reasons it is finite because of the desirability of certain portions of the band. Even the spectrum which is assigned is far from being 100% utilized, hence efficient use of the spectrum 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 or not, and can temporarily latch into or out of it without interfering with the transmissions of other users thereby efficiently utilizing spectrum. According to Dr.Bruce Fette (2004), "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".^[22]

The future of CR

The phenomenal 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 the Notice of Proposed Rule Making to allow unlicensed radios to operate in the TV broadcast bands. The IEEE 802.22 working group formed in November/2004 is equipped with the task of 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.^[23]

See also

• 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 the additional transmit power regardless of knowing the interference at the receiver, which can be used to optimize cognitive wireless network channels.^[24]
• Intelligent antenna (IA) is 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. For instance, IA-based multiple antenna terminals enable to communicate multiple radio links simultaneously up to the number of embedded multiple antennas.
• Link adaptation
• LTE Advanced
• OFDMA
• Radio resource management (RRM)
• Software-defined radio
• Ultra Wideband

References

1. ^ ^{a b} home [CWT Cognitive Radios]
2. ^ IEEE Xplore - Login
3. ^ http://www.it.kth.se/~jmitola/Mitola_Dissertation8_Integrated.pdf
4. ^ IEEE Spectrum: The End of Spectrum Scarcity
5. ^ Václav Valenta et al., Survey on Spectrum Utilization in Europe: Measurements, Analyses and Observations
6. ^ IEEE Xplore - Login
7. ^ ^{a b} IEEE Xplore - Login
8. ^ http://www.cwc.oulu.fi/home/files/news/CRAMNET_1.pdf
9. ^ http://www.cwc.oulu.fi/home/files/news/CRAMNET_3.pdf
10. ^ 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
11. ^ S. Haykin, "Cognitive Radio: Brain-empowered Wireless Communications", IEEE Journal on Selected Areas of Communications, vol. 23, nr. 2, pp. 201-220, Feb. 2005
12. ^ IEEE 802.22
13. ^ 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. 
14. ^ IEEE 802.15.2
15. ^ http://www.eecs.berkeley.edu/wireless/posters/WFW05_cognitive.pdf
16. ^ IEEE Xplore - Login
17. ^ 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. [1]
18. ^ Cognitive Functionality in Next Generation Wireless Networks
19. ^ CEPT Report 159 on technical and operational requirements for Cognitive Radio operation in TV White Spaces
20. ^ European Research project on spectrum access policies for Cognitive Radio
21. ^ ^{a b} "Software-Defined Radio. White Paper. A Technology Overview.(2002, August). pp 1-10.". Wipro Technologies. http://www.broadcastpapers.com/whitepapers/WiproSDRadio.pdf?CFID=1289733&CFTOKEN=d39ad02d46e2f73c-652340C5-F32E-4237-83D81F2959FF7406. 
22. ^ 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
23. ^ 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
24. ^ Natasha Devroye, Patrick Mitran and V. Tarokh, Limits on Communication in a Cognitive Radio Channel," IEEE Communications Magazine, pp. 44-49, June 2006.

External links

• 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)