Abstract
Cognitive radio (CR) technology is crucial for enabling dynamic spectrum management. CR allows opportunistic spectrum sharing with licensed primary radio (PR) users by allowing the so-called secondary users to dynamically access the under-utilized parts of the frequency bands that are allocated/licensed to the PR networks (PRNs). The CR system pays a utilization-dependent price to PRNs for utilizing the unused spectrum. An essential challenge in this domain is how to characterize the economic implications of spectrum sharing between the CR system and PRNs. Specifically, we consider a CR system with two competing CR service providers. This market model is known as the “duopoly model,” a market structure premise that consists of two companies providing the same type of service. For such a model, we investigate the problem of maximizing the overall achieved profit in the CR system. Specifically, we mathematically formulate the profit-maximization spectrum assignment problem for the two CR providers subject to spectrum sharing, power distribution, spectrum pricing, and quality of service constraints. We demonstrate that this optimization problem is an NP-hard binary nonlinear programming problem. Therefore, we adopt a meta-heuristic optimization method based on Antlion Optimization to solve the problem suboptimally. Simulation results revealed that our proposed profit-aware optimization significantly outperforms traditional CR-based spectrum access mechanisms.
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References
Suganthi, N., Meenakshi, S.: An efficient scheduling algorithm using queuing system to minimize starvation of non-real-time secondary users in cognitive radio network. Clust. Comput. (2022)
Sumathi, A.C., Vidhyapriya, R., Vivekanandan, C., Sangaiah, A.K.: Enhancing 4g co-existence with wi-fi/iot using cognitive radio. Clust. Comput. 22, 11295–11305 (2019)
Yang, Y., Park, L.T., Mandayam, N.B., Seskar, I., Glass, A.L., Sinha, N.: Prospect pricing in cognitive radio networks. IEEE Trans. Cognit. Commun. Netw. 1(1), 56–70 (2015)
Xie, R., Yu, F.R., Ji, H.: Spectrum sharing and resource allocation for energy-efficient heterogeneous cognitive radio networks with femtocells. IEEE Int. Conf. Commun. 2012, 1661–1665 (2012)
Reshma, C. R.: Spectrum pricing in cognitive radio networks: an analysis. Int. J. Adv. Comput. Sci. Appl. 13(3) (2022). https://doi.org/10.14569/IJACSA.2022.0130307
Handouf, S., Sabir, E., Sadik, M.: A pricing-based spectrum leasing framework with adaptive distributed learning for cognitive radio networks. In: Advances in Ubiquitous Networking, pp. 39–51 (2016)
Nallarasan, V., Kottilingam, K.: Spectrum management analysis for cognitive radio IoT. In: International Conference on Computer Communication and Informatics (ICCCI), vol. 2021, pp. 1–5 (2021)
Mustafa, A., Islam, M.N.U., Ahmed, S.: Dynamic spectrum sensing under crash and byzantine failure environments for distributed convergence in cognitive radio networks. IEEE Access 9, 23153–23167 (2021)
Yang, P., Wee, H., Pai, S., Yang, H., Wee, P.: A hybrid of monopoly and perfect competition model for hi-tech products. Int. J. Syst. Sci. 41, 1293–1300 (2010)
Guo, P., Hassin, R.: Strategic behavior and social optimization in Markovian vacation queues. Oper. Res. 59(4), 986–997 (2011)
Ménard, C.: A. a. cournot, recherches sur les principes mathématiques de la théorie des richesses, édition et préface de h. guitton, coll.<< les fondateurs >>, paris, calmann- lévy, 1974, 248 pages. Ann. Hist. Sci. Soc. 30(5), 1141–1146 (1975)
Shitovitz, B.: Oligopoly in markets with a continuum of traders. Econometrica 41(3), 467–501 (1973)
Askar, S.: The rise of complex phenomena in Cournot duopoly games due to demand functions without inflection points. Commun. Nonlinear Sci. Numer. Simul. 19, 1918–1925 (2014)
Zhou, W., Wang, X.-X.: On the stability and multistability in a duopoly game with r &d spillover and price competition. Discret. Dyn. Nat. Soc. 2019, 1–20 (2019)
Gal-Or, E.: Quality and quantity competition. Bell J. Econ. 14(2), 590–600 (1983)
Baruffa, G., Femminella, M., Pergolesi, M., Reali, G.: Comparison of Mongodb and Cassandra databases for spectrum monitoring as-a-service. IEEE Trans. Netw. Serv. Manag. 17(1), 346–360 (2020)
Rajendran, S., Calvo-Palomino, R., Fuchs, M., Van den Bergh, B., Cordobes, H., Giustiniano, D., Pollin, S., Lenders, V.: Electrosense: open and big spectrum data. IEEE Commun. Mag. 56(1), 210–217 (2018)
Zhang, Y., Song, L., Pan, M., Dawy, Z., Han, Z.: Non-cash auction for spectrum trading in cognitive radio networks: contract theoretical model with joint adverse selection and moral hazard. IEEE J. Sel. Areas Commun. 35(3), 643–653 (2017)
Gadekallu, T., Khare, N.: Ffbat-optimized rule based fuzzy logic classifier for diabetes. Int. J. Eng. Res. Afr. 24, 137–152 (2016)
Gadekallu, T., Khare, N.: Cuckoo search optimized reduction and fuzzy logic classifier for heart disease and diabetes prediction. Int. J. Fuzzy Syst. Appl. 6, 25–42 (2017)
Gandomi, A., Yang, X.-S., Talatahari, S., Alavi, A.: Metaheuristic applications in structures and infrastructures. Newnes (2013)
Mirjalili, S., Mirjalili, S., Lewis, A.: Grey wolf optimizer. Adv. Eng. Softw. 69, 46–61 (2014)
Assiri, A.S., Hussien, A.G., Amin, M.: Ant lion optimization: variants, hybrids, and applications. IEEE Access 8, 77746–77764 (2020)
Gao, Q., Xu, X.: The analysis and research on computational complexity. In: The 26th Chinese Control and Decision Conference (2014 CCDC), pp. 3467–3472 (2014)
Halloush, R.D., Salaimeh, R., Al-Dalqamoni, R.: Availability-aware channel allocation for multi-cell cognitive radio 5g networks. IEEE Trans. Veh. Technol. 71(4), 3931–3947 (2022)
Zhang, Y., Wang, J., Li, W.: Optimal pricing strategies in cognitive radio networks with heterogeneous secondary users and retrials. IEEE Access 7, 30937–30950 (2019)
Zhu, S., Wang, J., Li, W.W.: Optimal pricing strategies in cognitive radio networks with multiple spectrums. IEEE Syst. J. 1–11 (2020)
Liu, W., Yang, S., Sun, S., Wei, S.: A node deployment optimization method of WSN based on ant-lion optimization algorithm. In: 2018 IEEE 4th International Symposium on Wireless Systems Within the International Conferences on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS-SWS), pp. 88–92 (2018)
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Conceptualization: [HBS, GAER], Methodology: [HBS, MS, AA, GAER]; Formal analysis and investigation: [HBS, MQS]; Writing-original draft preparation: [HBS, MQS]; Writing-review and editing: [HBS, GAER, AA].
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Bany Salameh, H., Samara, M.Q., Elrefae, G.A. et al. Profit-maximization spectrum sharing in opportunistic duopoly market under dynamic spectrum pricing and QoS constraints. Cluster Comput 27, 1491–1502 (2024). https://doi.org/10.1007/s10586-023-04026-6
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DOI: https://doi.org/10.1007/s10586-023-04026-6