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A flexible transmit power selection concept for underlay cognitive users is proposed in this paper. We have employed an opportunistic, sensing based spectrum sharing method. Besides the power constraint to avoid interference at PU, the transmit power constraints of secondary user is also considered. Received Signal Strength Indicator based carrier selection method has been adopted. To resolve hidden terminal problem, twin scan concept is used at both ends (secondary transmitter and receiver) with same carrier frequency. Secondary transmitter selects suitable carrier frequency to initiate communication with the minimum power level as defined by the proposed algorithm. If received signal strength at the corresponding secondary receiver is below the predefined required receiver threshold, then power level is stepped up automatically. To maximize secondary user channel capacity, we have considered flexible power selection strategy as per channel state information. If the cognitive receiver is unable to recover the received information, even with the peak transmit power, it will again perform the frequency scanning operation. This is repeated till the best result is achieved. A power control circuit is designed to check the power selection concept.
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Mitola, J. (2000). Cognitive radio— an integrated agent architecture for software defined radio. PhD Dissertation, KTH, Stockholm, Sweden.
Zhao, Q., & Sadler, B. M. (2007). A survey of dynamic spectrum access. IEEE Signal Processing Magazine,24(3), 79–89. CrossRef
Le, L. B., & Hossain, E. (2008). Resource allocation for spectrum underlay in cognitive radio networks. IEEE Transactions on Wireless Communications,7(12), 5306–5315. CrossRef
Kang, X., Liang, Y. C., Garg, H. K., & Zhang, L. (2009). Sensing-based spectrum sharing in cognitive radio networks. IEEE Transactions on Vehicular Technology,58(8), 4649–4654. CrossRef
Badawy, A., & Khattab, T. (2013, October). A hybrid spectrum sensing technique with multiple antenna based on GLRT. In Wireless and Mobile Computing, Networking and Communications (WiMob), 2013 IEEE 9th International Conference on (pp. 736–742). Lyon, France: IEEE. doi: 10.1109/WiMOB.2013.6673438.
Yongjun, X., & Xiaohui, Z. (2013). Optimal power allocation for multiuser underlay cognitive radio networks under QoS and interference temperature constraints. China Communications,10(10), 91–100. CrossRef
Liu, Z., Wang, P., Xia, Y., Yang, H., & Guan, X. (2016). Chance-constraint optimization of power control in cognitive radio networks. Peer-to-Peer Networking and Applications,9(1), 245–253. CrossRef
Yao, H., Zhou, Z., Liu, H., & Zhang, L. (2009, June). Optimal power allocation in joint spectrum underlay and overlay cognitive radio networks. In Cognitive Radio Oriented Wireless Networks and Communications, 2009 (CROWNCOM’09) 4th International Conference on (pp. 1–5) Germany: IEEE, Courtyard Hannover Maschsee. doi: 10.1109/CROWNCOM.2009.5189342.
Wang, Y., Ren, P., Du, Q., & Sun, L. (2015). Optimal power allocation for underlay-based cognitive radio networks with primary user’s statistical delay QoS provisioning. IEEE Transactions on Wireless Communications,14(12), 6896–6910. CrossRef
Gu, J., & Jeon, W. S. (2013). Optimal power allocation in an “off” spectrum sensing interval for cognitive radio. IEEE Communications Letters,17(10), 1908–1911. CrossRef
Benaya, A. M., Shokair, M., El-Rabaie, E. S., & Elkordy, M. F. (2015). Optimal power allocation for sensing-based spectrum sharing in MIMO cognitive relay networks. Wireless Personal Communications,82(4), 2695–2707. CrossRef
Chen, Y., Lei, Q., & Yuan, X. (2014). Resource allocation based on dynamic hybrid overlay/underlay for heterogeneous services of cognitive radio networks. Wireless Personal Communications,79(3), 1647–1664. CrossRef
Oh, J., & Choi, W. (2010, September). A hybrid cognitive radio system: A combination of underlay and overlay approaches. In Vehicular Technology Conference Fall (VTC 2010- Fall), 2010 IEEE 72nd (pp. 1–5). Ottawa, Ontario, Canada: IEEE. doi: 10.1109/VETECF.2010.5594302.
Qiu, T., Xu, W., Song, T., He, Z., & Tian, B. (2011, May). Energy-efficient transmission for hybrid spectrum sharing in cognitive radio networks. In Vehicular Technology Conference (VTC Spring), 2011 IEEE 73rd (pp. 1–5). Budapest, Hungary: IEEE. doi: 10.1109/VETECS.2011.5956224.
Lan, P., Sun, F., Chen, L., Xue, P., & Hou, J. (2013). Power allocation and relay selection for cognitive relay networks with primary QoS constraint. IEEE Wireless Communications Letters,2(6), 583–586. CrossRef
Lee, C. H., & Haenggi, M. (2012). Interference and outage in Poisson cognitive networks. IEEE Transactions on Wireless Communications,11(4), 1392–1401. CrossRef
Xing, Y., Mathur, C. N., Haleem, M. A., Chandramouli, R., & Subbalakshmi, K. P. (2007). Dynamic spectrum access with QoS and interference temperature constraints. IEEE Transactions on Mobile Computing,6(4), 423–433. CrossRef
Kang, X., Zhang, R., Liang, Y. C., & Garg, H. K. (2011). Optimal power allocation strategies for fading cognitive radio channels with primary user outage constraint. IEEE Journal on Selected Areas in Communications,29(2), 374–383. CrossRef
Bepari, D., & Mitra, D. (2014, February). GA based optimal power allocation for underlay cognitive radio networks. In Electronics and Communication Systems (ICECS), 2014 International Conference on (pp. 1–6). Coimbatore, India: IEEE. doi: 10.1109/ECS.2014.6892554.
Rosas, A. A., Shokair, M., & El_dolil, S. A. (2015). Proposed optimization technique for maximization of throughput under using different multicarrier systems in cognitive radio networks. In The Proceedings of Second International Conference on Electronics Engineering, Clean Energy and Green Computing (EEECEGC) (pp. 25–33). Konya, Turkey: Mevlana University, ISBN: 978-1-941968-12-3©2015 SDIWC.
Hou, L., Yeung, K. H., & Wong, K. Y. (2015). SEER: Spectrum-and energy-efficient routing protocol for cognitive radio ad hoc networks. Wireless Networks,21(7), 2357–2368. CrossRef
Lan, P., Chen, L., Zhang, G., & Sun, F. (2015). Optimal resource allocation for cognitive radio networks with primary user outage constraint. EURASIP Journal on Wireless Communications and Networking,2015(1), 239. CrossRef
Kang, X., Liang, Y. C., Nallanathan, A., Garg, H. K., & Zhang, R. (2009). Optimal power allocation for fading channels in cognitive radio networks: Ergodic capacity and outage capacity. IEEE Transactions on Wireless Communications,8(2), 940–950. CrossRef
Bala, I., Bhamrah, M. S., & Singh, G. (2015). Capacity in fading environment based on soft sensing information under spectrum sharing constraints. Wireless Networks,23(2), 1–13.
Ozcan, G., & Gursoy, M. C. (2015). Optimal power control for underlay cognitive radio systems with arbitrary input distributions. IEEE Transactions on Wireless Communications,14(8), 4219–4233. CrossRef
Quan, Z., Cui, S., & Sayed, A. H. (2008). Optimal linear cooperation for spectrum sensing in cognitive radio networks. IEEE Journal of Selected Topics in Signal Processing,2(1), 28–40. CrossRef
Liu, X., Jia, M., & Tan, X. (2013). Threshold optimization of cooperative spectrum sensing in cognitive radio networks. Radio Science,48(1), 23–32. CrossRef
Zhao, Y., Li, S., Zhao, N., & Wu, Z. (2010). A novel energy detection algorithm for spectrum sensing in cognitive radio. Information Technology Journal,9(8), 1659–1664. CrossRef
Atapattu, S., Tellambura, C., & Jiang, H. (2011, June). Spectrum sensing via energy detector in low SNR. In Communications (ICC), 2011 IEEE International Conference on (pp. 1–5). Japan: IEEE, Kyoto International Conference Centre. doi: 10.1109/icc.2011.5963316.
Zhang, W., Mallik, R. K., & Letaief, K. B. (2009). Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks. IEEE Transactions on Wireless Communications,8(12), 5761–5766. CrossRef
Lee, W. C. (2010). Mobile communications design fundamentals (Vol. 25). Hoboken: Wiley.
Semiconductor Components Industries, LLC. (2003). 3.3V/5V Programmable PLL Synthesized Clock Generator, NBC12429 (2003–Rev. 2) NBC12429/D, 1–2.
Philips Semiconductors, SA636. (1997). Low voltage high performance mixer FM IF system with high speed RSSI, IC17 Data Handbook, Nov 07.
- Optimized Flexible Power Selection for Opportunistic Underlay Cognitive Radio Networks
- Springer US