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Hybrid Optimization Algorithms for Resource Allocation in Heterogeneous Cognitive Radio Networks

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Abstract

In recent days, accessing the spectrum of Cognitive Radio spread has gained significance in the applications of sensor based wireless devices. In this promising environment the bottle neck existed in accessing the spectrum which makes complications in the setup on wireless networks. In each cognitive space the spread spectrum optimization to the entire user is much more needed for enjoying the fruits of cognitive Radio. To achieve this, an effective mechanism is needed for the effective utilization of spectrum in cognitive radio system. Even though there are many substantial innovations in the area of cognitive radio none of the prevailing articles have focused on providing solutions to the problems which are related to efficient allocation of spectrum for each subordinate user with less power utilization and interference. In this article, the framework has been analyzed in both presence and absence of prime users with maximizing the capacity and data rate of the network. Further, the proposed model is solved by integrating a hybrid optimization algorithm with effective decision-making mechanism. Moreover, the simulation results validate that best solution is achieved considering capacity, spectrum sharing, data rate and interference for each subordinate users in entire network.

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Correspondence to Yuvaraja Teekaraman.

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Teekaraman, Y., Manoharan, H., Basha, A.R. et al. Hybrid Optimization Algorithms for Resource Allocation in Heterogeneous Cognitive Radio Networks. Neural Process Lett 55, 3813–3826 (2023). https://doi.org/10.1007/s11063-020-10255-2

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