Cloud Radio Access Network is a promising mobile network architecture. It is based on decoupling Base Band Units (BBUs) from Radio Remote Units (RRUs) and on centralizing the baseband processing of many Radio Remote Heads (RRHs) in a BBU pool. Such architecture paves the way for many improvements in mobile networks such as increased flexibility, increased energy efficiency, reduced operational costs, and better user experience. However, as computing resources are shared among the RRHs connected to the BBU pool, it becomes increasingly challenging to schedule the processing of users' data, especially on overloaded BBU pools, while respecting the time constraints imposed by the Hybrid Automatic Repeat Request (HARQ) mechanism. In fact, the amount of time required to process users' data is heavily dependent on radio parameters such as Modulation Coding Scheme index (MCS). In this paper, we propose to enable the coordination between radio and computing resources schedulers; such coordination allows the radio scheduler to adjust users' MCS indexes (i.e., which in turns adjusts the processing time), so that the computing resources scheduler can also schedule the processing of users' data on the BBU pool while respecting the HARQ-deadline. We propose three Integer Linear Programming (ILP)-based schemes and three low-complexity heuristics, and we evaluate the performance with respect to different performance metrics. The simulation results reveal the benefits of coordination solutions; especially, in terms of reducing the wasted transmission power. They also indicate for each metric the best coordination scheme that can be adopted.