Acknowledgement
This work was support by Dong Seoul University Research Support Center in 2023.
References
- Spectrum Policy Task Force Report, Federal Communications Commission, Washington, DC, USA, 2020, DOI: https://www.fcc.gov/document/spectrum-policy-task-force
- S. Haykin, "Cognitive Radio: Brain-Empowered Wireless Communication," IEEE Journal on Selected Areas in Communications, vol. 23, No. 2, pp. 201-220, Feb. 2005, DOI: 10.1109/JSAC.2004.839380
- J. Andrews et al., "Femtocells: Past, Present, and Future," IEEE Journal on Selected Areas in Communication, vol.30, No.3, Apr. 2012, pp.497-508, Mar. 2012, DOI: 10.1109/JSAC.2012.120401
- H. Elsawy et al., "HetNets with cognitive small cells: User offloading and distributed channel access techniques," IEEE Communications Magazine, vol.51, No.6, pp.28-36, June 2013, DOI: 10.1109/MCOM.2013.6525592
- Salman, Ayesha, et al. "Novel sensing and joint beam and null steering based resource allocation for cross-tier interference mitigation in cognitive femtocell networks," Wireless Networks, No.24, pp.2205-2219, Aug.2018, DOI: https://doi.org/10.1007/s11276-017-1465-6
- B. Liu et al., "Optimal Spectrum Sensing Interval in MISO Cognitive Small Cell Networks," IEEE Access, Vol. 6, pp. 3479-3490, Jan. 2018, DOI: 10.1109/ACCESS.2018.2789914
- H. Zhang et al, "Resource Allocation for Cognitive Small Cell Networks: A Cooperative Bargaining Game Theoretic Approach," IEEE Transactions on Wireless Communications, vol. 14, No. 6, pp. 3481-3493, June. 2015, DOI: 10.1109/TWC.2015.2407355
- G. Wu et al., "Spectrum Sharing with Dynamic Cournot Game in Vehicle-Enabled Cognitive Small-Cell Networks," Journal of Computer Networks and Communications, vol. 2019, pp.1-9, Dec. 2019 https://doi.org/10.1155/2019/4835923
- G. Owen, "Game theory," Emerald Group Publishing, 2013.
- T. N. Tran et al., "A Game Theory Based Clustering Protocol to Support Multicast Routing in Cognitive Radio Mobile Ad Hoc Networks," IEEE Access, vol. 8, pp. 141310-141330, Aug. 2020, DOI: 10.1109/ACCESS.2020.3013644
- A. Kumar et al., "A Game Theory Based Hybrid NOMA for Efficient Resource Optimization in Cognitive Radio Networks," IEEE Transactions on Network Science and Engineering, vol. 8, No. 4, pp. 3501-3514, Sept. 2021, DOI: 10.1109/TNSE.2021.3116669
- K. Danesh et al., "Game theory based spectrum sensing and transmission in energy harvesting hybrid cognitive radio networks," International journal of communication systems, vol.35. No.10, Jun. 2022
- Lo. B.F., "Design and analysis of common control channels in cognitive radio ad hoc networks," PhD diss., Georgia Institute of Technology, 2013
- N. Nie et.al., "A Game Theoretic Approach to Interference Management in Cognitive Networks," Wireless Communications, pp.199-219, 2007
- N. Nie et.al., "A Game Theoretic Approach to Interference Management in Cognitive Networks," Wireless Communications, vol. 143, 2007, DOI: https://doi.org/10.1007/978-0-387-48945-2_9
- B. Wang et al., "Advances in cognitive radio networks: A survey," IEEE Journal of selected topics in signal processing, vol. 5, No.1, pp.5-23, Feb. 2011, DOI: 10.1109/JSTSP.2010.2093210
- T.Y. Wu et al., "CACH: Cycle-adjustable channel hopping for control channel establishment in cognitive radio networks," IEEE INFOCOM 2014-IEEE Conference on Computer Communication, Toronto, Canada, pp.2706-2714, Apr.2014