OSA: Opportunistic Spectrum Access in Cognitive Radio Networks

OSA Testbed 

When we take a look at spectrum allocation chart in US as shown in Fig 1, we can see that almost all spectrum has already been allocated and it requires license to operate. Small portion of unlicensed spectrum is already overcrowded because of the successful deployment of innovative wireless networking including Wireless LAN (WLAN), mesh networks, Blue tooth and so on. On one hand, there is no more spectrum left to be allocated for future wireless technologies, on the other hand recent surveys have shown that the most of the licensed spectrum is either underutilized or idle most of the time. Thus the motivation is to develop the adaptive algorithms through which the wireless devices change their transmission parameters such as transmit power, modulation schemes, frequency, networks, and so on, according to their operating wireless environment in which they operate. Wireless devices can access underutilized or idle licensed spectrum dynamically and opportunistically without creating harmful interference to the licensed users, and the technology is regarded as Cognitive Radio. One challenge in Cognitive Radio Network (CRN) is to detect the spectrum optimally or search the spectrum database/map efficiently and reliably so that the cognitive radio users (unlicensed users) would not create harmful interference to licensed users while they use idle spectrum opportunities dynamically. Major research challenges are: to sense and detect the idle or underutilized spectrum in wide-band regime, to allocate wireless resources such as power, channel, etc., to secure/protect primary users, to design robust routing protocols.

Fig. 1: Frequency allocation chart of the U.S.

Experimental setup consists of USRP and computer with LabVIEW as shown in Fig 2, which represent a user. 
Fig. 2: SDR (Computer with USRP)

For spectrum overlay, a typical test-bed is shown in Fig 3. where secondary users sense channels and identify the idle bands (a.k.a. white spaces) and utilize them opportunistically and dynamically without creating any harmful interference to primary/licensed users. For spectrum overlay, a typical test-bed is shown in Fig 3. where secondary users coexist with licensed/primary users to utilize the bands dynamically without exceeding pre-specified threshold so as not create harmful interference to primary/licensed users. 

Fig. 3: Spectrum Overlay 

Fig. 4: Spectrum Underlay 

Wi-Spy, which is shown in Fig 5, can be used to monitor channel usage and spectrum analysis for secondary users. Spectrum usage and analysis is shown in Fig 6.


Fig. 5 Wi-Spy to monitor channel occupancy and spectrum analysis 

Fig. 6: Snapshot of the Wi-Spy spectrum analyzer


  • Danda B. Rawat, Sachin Shetty, and Chunsheng Xin, "Game Theoretic Approach to Dynamic Spectrum Access in Heterogeneous Cognitive Radio Networks with Multi-radio and QoS Requirements," IEEE Systems Journal, 2014, in press
  • Danda B. Rawat and Sachin Shetty. “Game Theoretic Approach to Dynamic Spectrum Access with Multi-radio and QoS Requirements,” in Proceedings of 2013 IEEE Global Conference on Signal and Information Processing – (IEEE GlobalSIP 2013), December 2013.
  • S. Shetty and D. B. Rawat. Cloud Computing based Cognitive Radio Networking. Cognitive Radio Technology Applications for Wireless and Mobile Ad hoc Networks, Book Chapter, IGI, 2013.
  • Danda Rawat, Sachin Shetty, Khurram Raza, "Secure Radio Resource Management in Cloud Computing Based Cognitive Radio Networks",  In Proceedings of the 4th International Workshop on Security in Cloud Computing, Pittsburgh, PA, September 2012.
  • D. B. Rawat, B. B. Bista, S. Shetty, and G. Yan. Waiting Probability Analysis for Dynamic Spectrum Access in Cognitive Radio Networks. In Proceedings of the 7th International Conference on Complex, Intelligent, and Software Intensive System (CISIS 2013) July 3rd - July 5th, 2013, Taichung, Taiwan.

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