access icon free Optimal power control and spectrum sensing for throughput maximisation in cognitive radio systems under PUEA

© The Institution of Engineering and Technology
Received 11/03/2019, Accepted 04/07/2019, Revised 26/06/2019, Published 17/07/2019

The authors propose an optimal joint power control and multi-band spectrum sensing scheme for cognitive radio (CR) systems to increase the spectral efficiency and to overcome the spectrum-sensing errors, in the presence of primary user emulation attacker (PUEA). This optimisation problem is solved to maximise the opportunistic CR data rate under interference and power budget constraints. To solve the formulated optimisation problem, they convert it to a convex problem, and then derive an optimal strategy for joint power control and spectrum access in the considered CR system. They show that the optimal strategy follows a quasi-underlay signaling, which is equipped with spectrum sensing. They evaluate the performance of the optimised scheme for the CR system in the presence of PUEA, and compare it with the conventional underlay scheme. For more comparison, they compare the proposed approach to that of a similar system, which does not consider the PUEA in the formulation of the joint spectrum sensing and power allocation. They show that the proposed optimal joint power control and spectrum sensing can significantly improve the system performance in terms of average achievable CR data rates compared with the considered conventional methods.

Inspec keywords: power control; signal detection; cognitive radio; telecommunication security; radio spectrum management; optimisation

Other keywords: multiband spectrum sensing scheme; throughput maximisation; cognitive radio systems; optimal joint power control; formulated optimisation problem; optimised scheme; interference; system performance; primary user emulation attacker; optimal power control; optimal strategy; opportunistic CR data rate; equal power allocation; joint spectrum sensing; convex problem; considered CR system; spectrum access; power budget constraints; average achievable CR data rates; spectrum-sensing errors; conventional underlay scheme; PUEA

Subjects: Power and energy control; Signal detection; Radio links and equipment; Optimisation techniques

References

    1. 1)
      • 15. Abedi, M.R., Mokari, N., Javan, M.R., et al: ‘Secure communication in OFDMA-based cognitive radio networks: an incentivized secondary network coexistence approach’, IEEE Trans. Veh. Commun., 2017, 66, (2), pp. 1171–1185.
    2. 2)
      • 29. Abedi, M.R., Mokari, N., Javan, M.R., et al: ‘Limited rate feedback scheme for resource allocation in secure relay-assisted OFDMA networks’, IEEE Trans. Wirel. Commun., 2016, 15, (4), pp. 2604–2618.
    3. 3)
      • 30. Chen, C., Cheng, H., Yao, Y.-D.: ‘Cooperative spectrum sensing in cognitive radio networks in the presence of the primary user emulation attack’, IEEE Trans. Wirel. Commun., 2011, 10, (7), pp. 2135–2141.
    4. 4)
      • 12. Karimi, M., Sadough, S.M.S.: ‘Improved spectrum sensing and achieved throughput of multiband cognitive radio systems under probabilistic spectrum access’, AEU – Int. J. Electron. Commun., 2018, 86, pp. 8–16.
    5. 5)
      • 9. Haghighat, M., Sadough, S.M.S.: ‘Cooperative spectrum sensing for cognitive radio networks in the presence of smart malicious users’, AEU – Int. J. Electron. Commun., 2014, 68, (6), pp. 520–527.
    6. 6)
      • 23. Yu, R., Zhang, Y., Liu, Y., et al: ‘Securing cognitive radio networks against primary user emulation attacks’, IEEE Netw., 2016, 30, (6), pp. 62–69.
    7. 7)
      • 27. Janatian, N., Sun, S., Modarres-Hashemi, M.: ‘Joint optimal spectrum sensing and power allocation in CDMA-based cognitive radio networks’, IEEE Trans. Veh. Technol., 2015, 64, (9), pp. 3990–3998.
    8. 8)
      • 21. Abedi, M.R., Mokari, N., Saeedi, H., et al: ‘Robust resource allocation to enhance physical layer security in full-duplex receivers: active adversary’, IEEE Trans. Wirel. Commun., 2017, 16, (2), pp. 885–899.
    9. 9)
      • 8. Verma, P., Singh, B.: ‘Joint optimization of sensing duration and detection threshold for maximizing the spectrum utilization’, Digit. Signal Process., 2018, 74, pp. 94–101.
    10. 10)
      • 17. Xu, D., Li, Q.: ‘Improving physical-layer security for primary users in cognitive radio networks’, IET Commun., 2017, 11, (15), pp. 2303–2310.
    11. 11)
      • 31. Chen, R., Park, J.M., Bian, K.: ‘Robust distributed spectrum sensing in cognitive radio networks’. The 27th Conf. on Computer Communications (INFOCOM 2008), Phoenix, AZ, USA, April 2008.
    12. 12)
      • 3. Ostovar, A., Chang, Z.: ‘Optimisation of cooperative spectrum sensing via optimal power allocation in cognitive radio networks’, IET Commun., 2017, 11, (13), pp. 2116–2124.
    13. 13)
      • 14. Abedi, M.R., Mokari, N., Saeedi, H., et al: ‘Secure robust resource allocation in the presence of active eavesdroppers using full-duplex receivers’. 2015 IEEE 82nd Vehicular Technology Conf. (VTC 2015-Fall), Boston, MA, USA, September 2015, pp. 1–5.
    14. 14)
      • 1. Mitola, J., Maguire, G.Q.: ‘Cognitive radio: making software radios more personal’, IEEE Pers. Commun., 1999, 6, (4), pp. 13–18.
    15. 15)
      • 33. Boyd, S., Vandenberghe, L.: ‘Convex optimization’ (Cambridge University Press, Cambridge, UK, 2004).
    16. 16)
      • 13. Onumanyi, A., Onwuka, E., Aibinu, A., et al: ‘A modified OTSU's algorithm for improving the performance of the energy detector in cognitive radio’, AEU – Int. J. Electron. Commun., 2017, 79, pp. 53–63.
    17. 17)
      • 18. Karimi, M., Sadough, S.M.S., Torabi, M.: ‘Improved joint spectrum sensing and power allocation for cognitive radio networks using probabilistic spectrum access’, IEEE Syst. J., 2019, pp. 1–8.
    18. 18)
      • 2. Haykin, S.: ‘Cognitive radio: brain-empowered wireless communications’, IEEE J. Sel. Areas Commun., 2005, 23, (2), pp. 201–220.
    19. 19)
      • 25. Karimi, M., Sadough, S.M.S.: ‘Efficient transmission strategy for cognitive radio systems under primary user emulation attack’, IEEE Syst. J., 2017, 12, (4), pp. 3767–3774.
    20. 20)
      • 28. Awin, F.A., Abdel-Raheem, E., Ahmadi, M.: ‘Designing an optimal energy efficient cluster-based spectrum sensing for cognitive radio networks’, IEEE Commun. Lett., 2016, 20, (9), pp. 1884–1887.
    21. 21)
      • 7. Soleimanpour-Moghadam, M., Talebi, S.: ‘Jointly optimal rate control and total transmission power for cooperative cognitive radio system’, IET Commun., 2017, 11, (11), pp. 1679–1688.
    22. 22)
      • 16. Sharifi, A.A., Sharifi, M., Niya, M.J.M.: ‘Secure cooperative spectrum sensing under primary user emulation attack in cognitive radio networks: attack-aware threshold selection approach’, AEU – Int. J. Electron. Commun., 2016, 70, (1), pp. 95–104.
    23. 23)
      • 10. Zou, J., Huang, L.: ‘Joint pricing and service selection for service-differentiated duopoly in cognitive radio networks’, IET Commun., 2017, 11, (13), pp. 2074–2081.
    24. 24)
      • 19. Chin, W.-L.W., Le, T.N., Tseng, C.-L.: ‘Authentication scheme for mobile OFDM-based on security information of physical layer over time-variant and multipath fading channels’, Inf. Sci., 2015, 321, pp. 238–249.
    25. 25)
      • 11. Ali, M., Nam, H.: ‘Effect of spectrum sensing and transmission duration on spectrum hole utilisation in cognitive radio networks’, IET Commun., 2017, 11, (16), pp. 2539–2543.
    26. 26)
      • 20. Chin, W.-L., Le, T.N., Tseng, C.-L., et al: ‘Cooperative detection of primary user emulation attacks based on channel-tap power in mobile cognitive radio networks’, Int. J. Ad Hoc Ubiquit. Comput., 2014, 15, (4), pp. 263–274.
    27. 27)
      • 4. Torabi, M., Nerguizian, C.: ‘Adaptive transmission in spectrum sharing systems with Alamouti OSTBC under spatially correlated channels’, IEEE Trans. Veh. Technol., 2017, 66, (4), pp. 3131–3142.
    28. 28)
      • 5. Aghazadeh, B., Torabi, M.: ‘Performance evaluation of multi-user diversity in a SIMO spectrum sharing system with reduced CSI load’, Digit. Signal Process., 2018, 72, pp. 160–170.
    29. 29)
      • 6. Abedi, M.R., Mokari, N., Javan, M.R., et al: ‘Robust and secure content delivery in energy and spectrum efficient next-generation networks’. 2018 IEEE Globecom Workshops (GC Wkshps), Abu Dhabi, UAE, December 2018, pp. 1–6.
    30. 30)
      • 26. Lopez-Ramos, L.M., Marques, A.G., Ramos, J.: ‘Jointly optimal sensing and resource allocation for multiuser interweave cognitive radios’, IEEE Trans. Wirel. Commun., 2014, 13, (11), pp. 5954–5967.
    31. 31)
      • 24. Karimi, M., Sadough, S.M.S.: ‘A probabilistic spectrum access approach to joint sensing and power allocation in multiband cognitive radio’. 2017 Iranian Conf. on Electrical Engineering (ICEE), Tehran, Iran, May 2017, pp. 1933–1937.
    32. 32)
      • 22. Ahmadfard, A., Jamshidi, A., Keshavarz-Haddad, A.: ‘Game theoretic approach to optimize the throughput of cognitive radio networks in physical layer attacks’, J. Intell. Fuzzy Syst., 2015, 28, (3), pp. 1281–1290.
    33. 33)
      • 32. Jin, Z., Anand, S., Subbalakshmi, K.P.: ‘Detecting primary user emulation attacks in dynamic spectrum access networks’. 2009 IEEE Int. Conf. on Communications, Dresden, Germany, June 2009, pp. 1–5.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-com.2019.0224
Loading

Related content

content/journals/10.1049/iet-com.2019.0224
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading