Intelligent Power Allocation Algorithm for Energy-Efficient Mobile Internet of Things (IoT) Networks

With mobile communication technology development, the mobile Internet of Things (IoT) is booming, and the IoT applications are springing up all the time. However, the wireless channels are complex, and the security of mobile IoT networks is facing many challenges. Energy efficiency is critical for secure communications in mobile IoT networks. To reduce energy consumption, we propose a transmit antenna selection (TAS)-based secrecy scheme employing amplify-and-forward (AF) relaying. Firstly, we derive the exact expressions, and analyze the physical layer security performance. Then, to further improve energy efficiency, we formulate the power allocation problem, which is a non-convex complicated problem. To solve this problem, we propose a novel power allocation intelligent optimization algorithm. Based on the designed power allocation function, an improved grey wolf optimization (IGWO) algorithm is employed to obtain the allocation parameter. For convergence speed and convergence precision, the proposed IGWO algorithm obtains better optimization performance than other swarm intelligence algorithms. Compared with other algorithms, the running time of IGWO is reduced by 24%, while maintaining the same optimization accuracy. This greatly improves the energy efficiency of mobile IoT networks.