Abstract
This paper studies the case of an overlay cognitive radio network where the primary user leases spectral resources to the secondary user in exchange for cooperation, considering that both type of users have specific quality of service requirements. We investigate the problem of joint power and time allocation for the secondary access during the cooperative phase, with a view to optimizing the effective capacity of the primary user given an average energy constraint for the secondary user. Afterwards, the optimal power allocation of the secondary user for its own transmission phase is investigated in order to maximize the effective capacity of the secondary link. The proposed joint power and time allocation mechanism is compared with an optimal time/constant power allocation scheme and a less sophisticated baseline allocation scheme, i.e. power allocation under constant time and its superiority is proven for various network parameters. The reference model of one primary–one secondary user is extended to a general multi user cognitive radio network through the proposed pairing mechanism based on matching theory. Particularly, considering the remarks of the reference scenario, we propose two different matching schemes (with/without consideration of primary users’ quality of service requirements) and we confirm their superiority compared to other matching mechanisms.
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Buddhikot, M. (2007). Understanding dynamic spectrum access: Models, taxonomy and challenges. In 2nd IEEE international symposium on new frontiers in dynamic spectrum access networks (DySPAN) (pp. 649–663).
Mitola, J., & Maguire, J. G. Q. (1999). Cognitive radio: Making software radios more personal. IEEE Personal Communications, 6(4), 13–18.
Haykin, S., & Setoodeh, P. (2015). Cognitive radio networks: The spectrum supply chain paradigm. IEEE Transactions on Cognitive Communications and Networking, 1(1), 3–28.
Akyildiz, I., Lee, W.-Y., Vuran, M. C., & Mohanty, S. (2008). A survey on spectrum management in cognitive radio networks. IEEE Communications Magazine, 46(4), 40–48.
Singh, J. S. P., Rai, M. K., Singh, J., & Kang, A. S. (2014). Trade-off between and and or detection method for cooperative sensing in cognitive radio. In IEEE international advance computing conference (IACC) (pp. 395–399).
Simeone, O., Stanojev, I., Savazzi, S., Bar-Ness, Y., Spagnolini, U., & Pickholtz, R. (2008). Spectrum leasing to cooperating secondary ad hoc networks. IEEE Journal on Selected Areas in Communications, 26(1), 203–213.
Laneman, J., Tse, D., & Wornell, G. W. (2004). Cooperative diversity in wireless networks: Efficient protocols and outage behavior. IEEE Transactions on Information Theory, 50(12), 3062–3080.
Cui, C., Man, H., Wang, Y., & Liu, S. (2016). Optimal cooperative spectrum aware opportunistic routing in cognitive radio ad hoc networks. Wireless Personal Communications, 91(1), 101–118.
Goldsmith, A., Jafar, S., Maric, I., & Srinivasa, S. (2009). Breaking spectrum gridlock with cognitive radios: An information theoretic perspective. Proceedings of the IEEE, 97(5), 894–914.
Wu, D., & Negi, R. (2003). Effective capacity: A wireless link model for support of quality of service. IEEE Transactions on Wireless Communications, 2(4), 630–643.
Tang, J., & Zhang, X. (2007). Quality-of-service driven power and rate adaptation over wireless links. IEEE Transactions on Wireless Communications, 6(8), 3058–3068.
Roth, A. E., & Sotomayor, M. A. O. (1992). Two-sided matching: A study in game-theoretic modeling and analysis. Cambridge: Cambridge University Press.
Gale, D., & Shapley, L. S. (1962). College admissions and the stability of marriage. American Mathematical Monthly, 69(1), 9–15.
Musavian, L., & Aissa, S. (2010). Effective capacity of delay-constrained cognitive radio in Nakagami fading channels. IEEE Transactions on Wireless Communications, 9(3), 1054–1062.
Vassaki, S., Poulakis, M. I., Panagopoulos, A. D., & Constantinou, P. (2011). Optimal power allocation under qos constraints in cognitive radio systems. In 8th International symposium on wireless communication systems (ISWCS) (pp. 552–556).
Vassaki, S., Poulakis, M. I., Panagopoulos, A. D., & Constantinou, P. (2014). Qos-driven power allocation under peak and average interference constraints in cognitive radio networks. Wireless Personal Communications, 78(1), 449–474.
Xu, D., & Li, Q. (2015). Effective capacity region and power allocation for two-way spectrum sharing cognitive radio networks. Science China Information Sciences, 58(6), 1–10.
Xu, D., & Li, Q. (2015). On the effective capacity region for cognitive radio multiple access channels. AEU-International Journal of Electronics and Communications, 69(6), 958–961.
Hammouda, M., Akin, S., & Peissig, J. (2014). Effective capacity in cognitive radio broadcast channels. In IEEE global communications conference (GLOBECOM) (pp. 1071–1077).
Wang, Y., & Liu, K. (2015). Statistical delay qos protection for primary users in cooperative cognitive radio networks. IEEE Communications Letters, 19(5), 835–838.
Roumeliotis, A. J., Vassaki, S., & Panagopoulos, A. D. (2016). Time allocation mechanism with qos constraints in a spectrum leasing environment. In IEEE International conference on telecommunications (ICT) (pp. 43–47).
Elalem, M. (2016). Effective capacity analysis for cognitive networks under qos satisfaction. Journal of Information Sciences and Computing Technologies, 5(3), 498–518.
Gu, Y., Saad, W., Bennis, M., Debbah, M., & Han, Z. (2015). Matching theory for future wireless networks: Fundamentals and applications. IEEE Communications Magazine, 53(5), 52–59.
Bayat, S., Louie, R. H., Vucetic, B., & Li, Y. (2013). Dynamic decentralised algorithms for cognitive radio relay networks with multiple primary and secondary users utilising matching theory. Transactions on Emerging Telecommunications Technologies, 24(5), 486–502.
Roumeliotis, A. J., Vassaki, S., & Panagopoulos, A. D. (2015). Overlay cognitive radio networks: A distributed matching scheme for user pairing. In IEEE international wireless communications and mobile computing conference (IWCMC) (pp. 172–177).
Jovicic, A., & Viswanath, P. (2009). Cognitive radio: An information-theoretic perspective. IEEE Transactions on Information Theory, 55(9), 3945–3958.
Chen, Y., Yu, G., Zhang, Z., Chen, H. H., & Qiu, P. (2008). On cognitive radio networks with opportunistic power control strategies in fading channels. IEEE Transactions on Wireless Communications, 7(7), 2752–2761.
Hong, Y. W. P., Huang, W. J., & Kuo, C. C. J. (2010). Cooperative communications and networking: Technologies and system design. Berlin: Springer.
Zeidler, E. (2004). Oxford users’ guide to mathematics. Oxford: Oxford University Press.
Boyd, S., & Vandenberghe, L. (2004). Convex optimization. Cambridge: Cambridge University Press.
Iwama, K., & Miyazaki, S. (2008). A survey of the stable marriage problem and its variants. In IEEE international conference on informatics education and research for knowledge-circulating society (ICKS) (pp. 131–136).
Hong, X., Wang, J., Wang, C.-X., & Shi, J. (2014). Cognitive radio in 5g: A perspective on energy-spectral efficiency trade-off. IEEE Communications Magazine, 52(7), 46–53.
Wang, C.-X., Haider, F., Gao, X., You, X.-H., Yang, Y., Yuan, D., et al. (2014). Cellular architecture and key technologies for 5g wireless communication networks. IEEE Communications Magazine, 52(2), 122–130.
Tseng, F. H., Chou, L. D., Chao, H. C., & Wang, J. (2015). Ultra-dense small cell planning using cognitive radio network toward 5g. IEEE Wireless Communications, 22(6), 76–83.
Tehrani, M. N., Uysal, M., & Yanikomeroglu, H. (2014). Device-to-device communication in 5g cellular networks: Challenges, solutions, and future directions. IEEE Communications Magazine, 52(5), 86–92.
ElSawy, H., Dahrouj, H., Al-Naffouri, T. Y., & Alouini, M. S. (2015). Virtualized cognitive network architecture for 5g cellular networks. IEEE Communications Magazine, 53(7), 78–85.
Mumtaz, S., Huq, K. M. S., Ashraf, M. I., Rodriguez, J., Monteiro, V., & Politis, C. (2015). Cognitive vehicular communication for 5g. IEEE Communications Magazine, 53(7), 109–117.
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Appendix: Matching Algorithm for Multi-user CRNs
Appendix: Matching Algorithm for Multi-user CRNs
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Roumeliotis, A.J., Vassaki, S. & Panagopoulos, A.D. Joint Power and Time Allocation Scheme with QoS Constraints in Overlay Multi-user Cognitive Radio Networks. Wireless Pers Commun 98, 337–362 (2018). https://doi.org/10.1007/s11277-017-4872-1
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DOI: https://doi.org/10.1007/s11277-017-4872-1