Background Extended reality (XR) service is a promising application for future communications. In wireless communications, XR data are transmitted over radio between base stations and mobile terminals. A region is usually divided into multiple cells, each of which is equipped with a base station to serve users. One base station usually serves multiple users, and multiple base stations may serve one user at the same time. Task The task of this competition is to design a scheduling algorithm for XR service. By properly allocating radio resources, we want to maximize the number of XR data frames that are successfully transmitted. A diagram is provided below for illustration: The transmission of a data frame is failed when it cannot be completely transmitted during the permitted transmission time window. Therefore, the objective of this task can be modeled as: () \mathcal{P}: \max \sum_j f_j \tag{1} () () f_j=\left\{\begin{array}{c} 1, g_j \geq T B S_j \\ 0, g_j< T B S_j \end{array}\right. \tag{2} () Here, (f_j) represents the transmission result of the (j)-th frame: when the actual transmitted bits (g_j) (computed via (5)) is not less than the size of the frame, i.e., (TBS_j) (transport block size), the frame would be successfully transmitted so that (f_j=1). Otherwise, (f_j=0). To achieve better user experience, scheduling algorithm should be proposed to efficiently assign the limited radio resources: Time domain resource, which is divided into several transmission time intervals (TTIs), each TTI corresponds to a transmission time of (0.5)ms. Frequency domain resource, which is divided into several resource block groups (Resource Block Group, RBG), each RBG corresponds to a transmission bandwidth of (5760) kHz. Power domain resource: each cell has a fixed maximum transmission power to serve users. Summarily, two optimization variables are introduced to represent the scheduling result: () b_{r n t}^{(k)} \in