An Adaptive Grey Wolf Optimization Algorithm for Secrecy Rate Optimization in Interference Limited Wireless Networks

Throughout the revolving generations of cellular technologies, data security has been one of the biggest concerns. In an interference-limited wireless network, this security concern becomes quite vital due to the intervention of eavesdroppers in the network. As a result, the max-min secrecy throughput problem becomes one of the most significant optimization problems in the fields of wireless communication and network security. Nature-inspired optimization algorithms are quite vital tools for this kind of optimization problem. In this paper, a problem-specific adaptive version of the Grey Wolf Optimization Algorithm has been used to solve this max-min throughput problem, and the performance of the proposed algorithm has been compared with the existing methods and with a few existing meta-heuristic algorithms. The balance between the exploration and the exploitation phase has been controlled to enhance the convergence speed to yield the optimal solution in the lowest possible time.