Dynamic Spectrum Access Technology, Cognitive Radio, and Spectrum Sensing Younes Abdi, PhD Faculty of Information Technology University of Jyväskylä Email: younes.abdi@jyu.fi
Outline Introduction What is Dynamic Spectrum Access (DSA)? Cognitive Radio (CR) Cognitive Radio Network Architecture IEEE Standards Supporting CR and DSA Applications Spectrum Sensing Cooperative Spectrum Sensing Tradeoffs in Cooperative Sensing Summary References
Introduction The Radio Spectrum
Introduction Different spectrum bands for different services
Introduction The radio spectrum is crowded
Introduction The spectrum is underutilized Spectrum utilization [1]
Dynamic Spectrum Access (DSA) The White Space concept Primary Users (PU) and Secondary Users (SU) The concepts of white space and dynamic spectrum access [1]
Dynamic Spectrum Access (DSA) Implemented by Cognitive Radios (CR) Self-awareness, context-awareness, and adaptability Definition of CR [2]: A cognitive radio is a radio whose control processes permit the radio to leverage situational knowledge and intelligent processing to autonomously adapt towards some goal. Intelligence is the capacity to acquire and apply knowledge, especially, toward a purposeful goal.
Cognitive Radio (CR) Architecture Components of a cognitive radio system [3]
Cognitive Radio Network Architecture: Primary and Secondary Users CR Network Architecture [1]
IEEE Standards Supporting CR and DSA functionalities The evolution of IEEE standardization activities relating to CR and DSA © 2008 IEEE.
The IEEE 802.22 Standard Wireless RAN TV-Band Devices Geolocation/Database Spectrum Sensing 802.22 wireless RAN classification as compared to other popular wireless standards © 2006 IEEE.
Applications of Cognitive Radio
Applications of Cognitive Radio Wireless Cellular Networks Public Safety Networks Smart Grid Wireless Medical Networks …
CR Applications: Smart Grid An IEEE 802.22-based smart grid architecture © 2011 IEEE.
Spectrum Sensing in Cognitive Radios CRs listen to their radio environment Various signal processing techniques Sensing quality is vulnerable to wireless impairments The sensing quality is enhanced with cooperative communication techniques
Cooperative Spectrum Sensing The hidden node problem and need for cooperative spectrum sensing The hidden node problem in a CRN [3]
Cooperative Sensing Three step: Local sensing, reporting, decision/data fusion Basic configuration of centralized cooperative spectrum sensing
Proposed Sensing Structures The sensing-throughput tradeoff Joint reporting-fusion optimization Random Interruptions in Cooperation
The Sensing-Throughput Tradeoff Energy consumed by a sensing CR vs. the maximum throughput achieved.
Joint Reporting-Fusion Optimization Linear fusion of quantized reports in cooperative sensing.
Performance of the Joint Optimization Performance of the proposed joint reporting-fusion optimization scheme compared with the optimal linear combining.
Random Interruptions in Cooperation Linear fusion of quantized reports in cooperative sensing.
Performance of the Random Interruptions Performance of the proposed method and linear cooperative sensing
Summary Radio spectrum DSA technology Cognitive radio Spectrum sensing in cognitive radios Cooperative spectrum sensing
Selected References [1] I. F. Akyildiz, W.-Y. Lee, M. C. Vuran, and S. Mohanty, “A survey on spectrum management in cognitive radio networks,” IEEE Communications Magazine, vol. 46, no. 4, pp. 40–48, 2008. [2] J. O. Neel, “Analysis and design of cognitive radio networks and distributed radio resource management algorithms,” Ph.D. dissertation, Virginia Polytechnic Institute and State University, 2006. [3] M. Sherman, A. N. Mody, R. Martinez, C. Rodriguez, and R. Reddy, “IEEE standards supporting cognitive radio and networks, dynamic spectrum access, and coexistence,” IEEE Communications Magazine, vol. 46, no. 7, pp. 72–79, 2008. [4] I. F. Akyildiz, B. F. Lo, and R. Balakrishnan, “Cooperative spectrum sensing in cognitive radio networks: A survey,” Elsevier Physical Communications, vol. 4, no. 1, pp. 40–62, March 2011. [5] J. Mitola, Cognitive Radio—An Integrated Agent Architecture for Software Defined Radio. Royal Institute of Technology (KTH), 2000. [6] Y. Abdi and T. Ristaniemi, “Joint Local Quantization and Linear Cooperation in Spectrum Sensing for Cognitive Radio Networks,” IEEE Transactions on Signal Processing, vol. 62, no. 17, pp. 4349-4362, Sept. 1, 2014. [7] Y. Abdi and T. Ristaniemi, “Random Interruptions in Cooperation for Spectrum Sensing in Cognitive Radio Networks,” IEEE Transactions on Communications (accepted for publication), 2016.
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