Energy Efficiency Optimization of NOMA IoT Communication for 5G

With the rapid increase in the number of mobile users and the continuous emergence of new wireless multimedia services, 5G mobile communication technology that can achieve spectral efficiency and data rate improvements has become a current research hotspot. This paper analyzes and summarizes the existing Internet of Things user grouping and power allocation algorithms under multi-carrier, and introduces the possible CSI (Channel State Information) error classification and modeling in the channel estimation process. For the dual-user cooperative 5G SWIPT-NOMA (Simultaneous Wireless Information and Power Transfer-Non-Orthogonal Multiple Access) transmission system with FD (Full-Duplex) antennas that exist in the presence of eavesdroppers, the physical layer security energy efficiency is used as the system performance measurement index. In view of the non-convex optimization problem and the high degree of coupling between variables, the joint solution of beamforming and power split ratio usually adopts the concave-convex procedure algorithm. This study proposes an improved particle swarm optimization algorithm, which is simpler than traditional solution methods. Aiming at the shortcomings of higher complexity of optimization algorithm, an improved particle swarm optimization algorithm with higher algorithm efficiency is proposed. The simulation results show that the optimal adaptive time slot optimization algorithm can obtain the optimal solution of the optimization problem, but the algorithm complexity is high. The improved particle swarm optimization algorithm is close to the optimal solution, the error is within the acceptable range, and the algorithm time is complicated.