Abstract-Cloud radio access networking (C-RAN) constitutes a promising architecture for next-generation systems. Beneficial centralized signal processing techniques can be realized under the C-RAN architecture. Furthermore, given the recent rapid development of cloud computing, the C-RAN architecture is an ideal platform for supporting network function virtualization (NFV), software-defined networking (SDN) and artificial intelligence (AI). However, most of the existing contributions on C-RAN are mainly focused on the physical layer issues. The nextgeneration networks are expected to support compelling wireless applications satisfying diverse delay requirements, such as ultrareliable and low-latency communications (URLLC), etc. Hence, we invoke the effective capacity theory for statistical delaybounded QoS provision in C-RAN architectures, where the delay is taken into account. Based on the system model proposed, we conceive sophisticated power allocation schemes for maximizing the effective capacity of both single-user and multi-user scenarios. Our simulation results show that a low delay outage probability can be guaranteed by appropriately choosing the delay exponent. Furthermore, our simulation results demonstrate that the proposed algorithm significantly outperforms the existing algorithms in terms of the achievable effective capacity. Finally, some open research challenges are highlighted.