Before understanding the architecture of ORAN, First we need to understand the LTE architecture which consist of EPC,eNB and the RF Antenna Unit.
The functions in LTE RAN are split so that the Baseband Unit (BBU) and the Remote Radio Head (RRH) can be separated physically. This allows the RRH to be located closer to the antenna, while the BBU can be located in center shown in fig.1a
Now Coming to 5G RAN Architecture as show in fig 1b
5G Architecture consist of :
a) 5G CORE
b) 5G RAN divided in to two parts – BBU and RU.
c) RF antenna Unit
BBU is split into CU and DU. Now the question comes What is CU and DU?
CU: CU is the centralized unit that runs the RRC,SDAP and PDCP layers.CU further divided into CU CP & CU UP
CU-CP: Central Unit – Control Plane: a logical node hosting the RRC and the control plane part of the PDCP protocol
CU-UP: Central Unit – User Plane: a logical node hosting the user plane part of the PDCP protocol and the SDAP protocol
DU: Distributed Unit: a logical node hosting RLC/MAC/High-PHY layers based on a lower layer functional split.
RU: Radio Unit: a logical node hosting Low-PHY layer and RF processing based on a lower layer functional split. More specific in including the Low-PHY layer (FFT/iFFT, PRACH extraction).
Now Question comes in mind what is ORAN? What is the need of ORAN?
The objective of the O-RAN Alliance is to clearly define requirements for an open, virtualized and interoperable RAN. It has defined two core principles to guide this mission, namely openness and intelligence.
In the case of intelligence, the O-RAN architecture has introduced a new type of Software Defined Network (SDN) controller called the RAN Intelligent Controller (RIC), which is responsible for automating the deployment of RAN functions in response to service needs. This includes a near real-time (near-RT) RIC and a non-near-real-time (non-RT) RIC. Both RICs make decisions based on analysis of data collected in the network using deep learning and artificial intelligence.
In the case of openness, the O-RAN architecture is based on well defined, open interfaces to enable interoperability between implementations from multiple vendors. This includes the fronthaul interface between the O-DU and O-RU based on split option 7.2x.
Near-RT RIC: O-RAN near-real-time RAN Intelligent Controller: a logical function that enables near-real-time control and optimization of RAN elements and resources via fine-grained data collection and actions over E2 interface. It may include AI/ML workflow including model training, inference and updates.
Non-RT RIC: O-RAN non-real-time RAN Intelligent Controller: a logical function within SMO that enables non-real time control and optimization of RAN elements and resources, AI/ML workflow including model training, inference and updates, and policy-based guidance of applications/features in Near-RT RIC.
Overall Architecture of O-RAN
Figure below provides a high-level view of the O-RAN architecture. It shows that the four key interfaces – namely, A1, O1, Open Fronthaul M-plane and O2 – connect SMO (Service Management and Orchestration) framework to O RAN network functions and O-Cloud. Figure below also illustrates that the O-RAN network functions can be VNFs (Virtualized Network Function), i.e., VMs or Containers, sitting above the O-Cloud and/or PNFs (Physical Network Function) utilizing customized hardware. All O-RAN network functions are expected to support the O1 interface when interfacing the SMO framework.
The Open Fronthaul M-plane interface, between SMO and O-RU, is to support the O-RU management in hybrid model.It is an optional interface to the SMO that is included for backward compatibility purposes.It is intended for management of the O-RU in hybrid mode only.
O1: Interface between management entity and O-RAN managed elements.
SMO a Service Management and Orchestration system.
A1-Interface between Non RT RIC & Near RT RIC.
O2- Interface between SMO & O cloud.