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Two-stage decision making policy for opportunistic spectrum access and validation on USRP testbed


“Recently, various paradigms, for instance, device-to-device communications, LTE-unlicensed and cognitive radio based on an opportunistic spectrum access (OSA) are being envisioned to improve the average spectrum utilization. In OSA, secondary (unlicensed) users (SUs) need decision making policies (DMPs) to identify and transmit over optimum frequency bands without any interference to the primary (licensed) users as well as minimize the number of collisions among SUs. In this paper, we have proposed a two-stage DMP consisting of Bayesian Multi-armed Bandit algorithm to accurately characterize the frequency band statistics independently at each SU and frequency band selection scheme for orthogonalization of SUs. The analytical and simulation results show that the proposed DMP leads to 45% improvement in the average spectrum utilization compared to 36–39% in the existing DMPs. Furthermore, the number of collisions are 58.5% lower in the proposed DMP making SU terminals energy-efficient. The performance of the proposed DMP has been verified on the proposed USRP testbed in real radio environment and the experimental results closely match the simulated results .”

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The authors thank the Department of Science and Technology (DST), Government of India for the INSPIRE fellowship in support of this work.

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Correspondence to Rohit Kumar.

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Kumar, R., Darak, S.J., Sharma, A.K. et al. Two-stage decision making policy for opportunistic spectrum access and validation on USRP testbed. Wireless Netw 24, 1509–1523 (2018). https://doi.org/10.1007/s11276-016-1420-y

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  • Decentralized network
  • Dynamic spectrum learning and access
  • Opportunistic spectrum access
  • Multi-armed bandit
  • Decision making policy