Energy-efficient resource allocation optimization algorithm in industrial IoTs scenarios based on energy harvesting

摘要

Due to the rapid development of the mobile Internet and the Internet of Things (IoTs), the requirements of users and enterprises for data transmission have increased exponentially. Non-orthogonal multiple access technology can improve the spectrum efficiency of the system, but it also brings huge energy consumption. This paper studies the resource allocation of non-orthogonal multiple access systems from the perspective of energy efficiency. For the multi-carrier downlink NOMA communication scenario, the circuit energy consumption model related to the transmission rate is considered. Based on the GPE energy efficiency criterion that helps reduce the complexity of channel estimation, the joint optimization algorithm of channel resources and power resources is studied. By establishing a bilateral matching model between users and sub-channels, a low-complexity channel resource allocation algorithm based on centralized scheduling is proposed. In order to avoid the phenomenon that the data transmission quality is seriously degraded due to the energy saving of the system, the limitation of user service quality requirements is also added to the established optimization problem. The algorithm performance simulation experiment shows that the algorithm in this paper has higher average energy efficiency of the system compared with the non-cooperative centralized scheduling and the distributed RB allocation algorithm.