Cognitive Radio: State-of-the-art

With the rise of a wide range of technologies and services, two contradictory findings regarding the radio frequency behavior have been reported. The explosive growth of wireless and multimedia services has triggered a surging need for high quality of service (QoS) and bandwidth. The radio spectrum becomes more precious today [1]. Nevertheless, real experiments
for spectrum occupancy statistics performed on some frequency bands, such as the band B = [3 GHz; 6 GHz] in down-town Berkeley [2], has indicated the under-utilization of the frequency spectrum over time and geographical locations [3] [4]. This seemingly paradoxical behavior highlights a serious problem in the fixed spectrum assignment policies and underlines an apparent spectrum scarcity. A range of research studies in this area are conducted, and the new proposed solution was the Cognitive Radio (CR) [5]. This concept, through its four fundamental operations [6] (Fig. 1), generates a big interest as a key cost-effective solution to find strategies for sustaining the enormous proliferation of new technologies with limited spectrum resources.

Figure 1: Cognitive radio cycle.

The CR concept was first proposed by Joseph Mitola in his publications during 1999 [5] [7] and in his PhD thesis [8]. He proposed the following description "The term cognitive radio identifies 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: (a) detect user communications needs as a function of use context, and (b) to provide radio resources and wireless services most appropriate to those needs.". The federal communications commission (FCC) in the United States was among the first worldwide spectrum regulatory bodies allowing the cognitive radios to operate in licensed bands [9]. The FCC defines the cognitive radio as "A radio or system that senses its operational electromagnetic environment and can dynamically and autonomously adjust its radio operating parameters to modify system operation, such as maximize throughput, mitigate interference, facilitate interoperability, access secondary markets.".

Figure 2: Evolution of the number of cognitive radio-related publications.

During the last decade, the cognitive radio paradigm has aroused huge interest among the community of researchers. Using the Scopus Search page [10], we have typed the keyword "Cognitive radio" as a search string to retrieve some useful data and statistics related to this research topic. Scopus is is one of the largest bibliographic databases and it is only available through academic subscription. Fig. 2 tracks the evolution of the number of publications related to the concept of cognitive radio, the number of published documents in this research area has been steadily increasing since its invention by J. Mitola in 1999. It is widely expected that the concept of cognitive radio will revolutionize the classical spectrum allocation strategies toward more efficient and optimal sharing of the frequency resource, many countries around the world have began to update their thinking and research directions to consider the emerging theme of cognitive radio (Fig. 3).

Figure 3: Cognitive radio-related publications around the world.

As suggested by the aforementioned definitions, the cognitive radio should be able to sense the spectral environment and access it in an opportunistic way. Cognitive devices can be reconfigured independently to choose the best network and the best frequency bands to ensure optimal service to the user. As opposed to current systems where the allocation of spectrum is static, the cognitive radio devices will look to dynamically access the radio spectrum by automatically detecting free frequency bands.

BIBLIOGRAPHY

[1] "FCC web site," http://www.fcc.gov/oet/info/database/spectrum/.

[2] R. W. Broderson, A. Wolisz, D. Cabric, S. M. Mishra, and D. Willkomm, "Corvus: A cognitive radio approach for usage of virtual unlicensed spectrum," UC Berkeley White Paper, Technical Report, July 2004.

[3] "Shared spectrum compagny, spectrum occupancy measurement," http://www.sharedspectrum.com/measurements/.

[4] "U.S. frequency allocations," http://www.ntia.doc.gov/osmhome/allochrt.pdf.

[5] J. Mitola III and G.Q Maguire, "Cognitive radio: making software radios more personal," IEEE Personal Communications, vol. 6, pp. 13-18, August 1999.

[6] L. Khalid and A. Anpalagan, "Emerging cognitive radio technology: Principles, challenges and opportunities," Computers and Electrical Engineering, vol. 36, no. 2, pp. 358-366, 2010.
[7] J. Mitola III, "Technical challenges in the globalization of software radio," IEEE Communications Magazine, vol. 37, pp. 84{89, February 1999.
[8] J. Mitola III, "Cognitive radio: an integrated agent architecture for software defined radio," Ph.D. Thesis, KTH Royal Institute of Technology, 2000.
[9] Federal Communications Commission, "Report of spectrum policy task force," ET Docket 02-135, November  2002.
[10] "SCOPUS database," http://www.scopus.com/.