Interference-Aware Resource Allocation in Cognitive Radio Networks Using Improved Grey Wolf Optimizer

The need for spectrum has become a critical consideration due to the increasing number of mobile wireless devices. In a network topology consisting of Device-to-Device (D2D) and cellular networks, throughput optimization with consideration for interference is essential. To achieve optimal results, Cognitive Radio Networks (CRN) are implemented. Using the Improved Grey Wolf Optimizer (I-GWO) meta-heuristic algorithm, this research focuses on obtaining the optimal value from the CRN-D2D network model. The optimal value being sought is the best system throughput, which can then be used as a method for channel allocation management. A comparison is made between the I-GWO algorithm and its predecessor, the Grey Wolf Optimizer (GWO). In the CDF network throughput, at $\mathbf{C D F}=\mathbf{0 . 5}, \mathbf{I}-\mathbf{G W O}$ achieves throughput up to $6.2 \times 10^{-7} \mathbf{b p s} / \mathbf{H z}$, compared to GWO which only reaches $5 \times 10^{-7} \mathbf{~ b p s} / \mathbf{H z}$, meaning that I-GWO achieves 24% better results than GWO. With this improvement, it is expected that user devices within the network area will experience less interference and better data transmission.