LAUSR

Non-orthogonal multiple access (NOMA) technique is capable of improving the efficiency of delivering and pushing contents in wireless caching networks. However, due to the differences of the data volume and the channel condition, the static power control schemes cannot fully explore the potential of NOMA. To solve this problem, dynamic power control for NOMA transmissions in wireless caching networks is studied in this letter, which can be adjusted based on the status of content transmissions. In particular, we focus on minimizing the transmission delay with the considerations of each user’s transmission deadline and the total power constraint. An iterative algorithm is first proposed to approach the optimal solution of dynamic power control. Then a deep neural network (DNN)-based method is designed to keep a balance between the performance and the computational complexity. Finally, Monte-Carlo simulations are provided for verifications.