nality between users is calculated offline and users are grouped together according to this calculation. In semistatic environments where channels are relatively constant (low mobility such as Wi-Fi applications), this technique can save greatly on computational cost that no longer needs to be accounted for in real time. Quasi- real-time solutions where "spare" compute resources are used opportunistically to maintain near-optimal grouped user sets are also possible. System-level optimization Most air interface schedule implementations focus on base station level optimization, where the base station implies colocation of MAC(/RLC/Packet Data Convergence Protocol) com- ponents with (high and low) physical layer processing in a single unit that is colocated with the antenna. Or in Open Radio Access Network language: a colocated central unit (CU)/dis- tributed unit (DU)/ radio unit (RU) or integrated small-cell system. In this case, the sched- uler (MAC layer) is colocated with the antenna for a single-cell site. However, centralization of processing gives another degree of freedom. Let's look at the system from a very high level in Fig. 7-11. Note the F1 interface in this picture that is defined by 3GPP in 38.475. This standard defines the low-level messages required for the controlled transfer of user data between CU and DU, allowing DU buffer space to remain limited and the bulk of the user buffers to be contained in the CU. This mechanism allows a single user (the middle one in the figure above) to be connected to multiple DUs at the same time, where the CU controls which DU owns the data flow to this UE. This introduces the concept of the CU scheduler Chapter 7 Wireless scheduling and Quality of Service optimization techniques 255 algorithm that can have limited/no visibility into air interface conditions between the DU and the RU but instead has capability to route packets through different air interfaces. This CU scheduling algorithm becomes a system-level scheduler. See Fig. 7-12 in which the RU is depicted i