Cloud RAN challenges and solutions

In this paper, we take an overall look at key technical challenges in the evolution of the radio access network ( RAN) architecture towards Cloud RAN and solutions to overcome them. To address fronthaul limitations, we examine the implications and tradeoffs enabled by functional splits on fronthaul needs, system performance, and centralization scale. We examine the architecture of algorithms for multi-cell coordination and implications in a Cloud RAN environment. To maximize the use of general-purpose processors (GPP) and operating systems such as Linux for Cloud RAN, we propose methods of achieving real-time performance suitable for RAN functions. To enable right-sizing the amount of compute used for various RAN functions based on the workload, we propose methods of pooling and elastic scaling for RAN functions that exploit the fact that certain RAN functions perform per-user operations while others perform per-cell operations. Cloud RAN also aims to use cloud management technologies such as virtualized infrastructure management (VIM) and orchestration for automating the instantiation and scaling of RAN functions. We identify special needs for RAN arising from real-time constraints and a mix of GPP and non-GPP hardware. In the evolution towards 5G, we propose the use of Cloud-RAN-based multi-connectivity anchoring to address processing bottlenecks in a scalable manner. We identify opportunities for optimization across RAN and other network layers enabled by the distributed edge cloud architecture.