Multi-Stage Time-Space-Power Resource Allocation: From the Perspective of User Experience Rate

In last decades, joint design of user scheduling and precoding has been investigated for single transmission time interval (TTI). However, this family of single-stage design cannot optimize real-time metrics that are measured in temporal dimension. In this paper, we target on optimizing the experience rate, which is defined as the ratio of a user's data packet size to the total time for completely delivering the user's data. A novel multi-stage dynamic resource programming is formulated as a multi-stage mixed integer nonlinear programming (MINLP) problem. Then, a low-complexity iterative algorithm is proposed for a jointly optimizing user scheduling and precoding. In particular, a second cone programming problem is dedicatedly designed, for providing a high-quality initial point for the iterative algorithm. The simulation results demonstrate that the proposed design endorses enhanced experience rate performance, with fast convergence behavior.