Deep deterministic policy gradient-based energy efficiency optimization algorithm for CR-NOMA - ZHANG Yun (Dianxin kexue)
Cognitive radio non-orthogonal multiple access (CR-NOMA) technology was used to alleviate the shortage of spectrum resource, and improve the throughput of sensor devices. But the energy efficiency problem had been restricting the application of sensor devices. Therefore, for CR-NOMA, deep deterministic policy gradient-based energy efficiency optimization (DPEE) algorithm was proposed. By jointly optimizing the transmission power and time slot splitting coefficient, the energy efficiency of sensor devices was improved. The energy efficiency optimization problem was modeled as a Markov decision process, and it was solved by the deep deterministic policy gradient (DDPG) method. Finally, the influence of circuit power consumption, time slot durations and number of main devices on energy efficiency were analyzed. The simulation results show that the energy efficiency decreases as the circuit power consumption of sensor device increases. In addition, compared with other algorithms, the proposed algorithm improves energy efficiency.