Overview of Radio Access Network Edge: RAN EDGE

Hello folks, Welcome back to Learnizo Global. We discussed Edge computing in our previous article. Edge computing moves to computing closer to end-users to minimize the distance that data has to travel, while still retaining the centralized nature of cloud computing.

What is RAN Edge?

The Radio Access Network (RAN) edge is outside the network core and closer to the end-user. 5G RAN incorporates virtualization and edge computing into its infrastructure.

RAN nodes at the edge connect users to the core network, clouds, the internet, and to other users without user data traveling as far before reaching the nearest RAN node. Adding general-purpose servers to a RAN node gives the node more compute, networking, and storage resources to use.

Types of RAN nodes can be traditional cell towers, rooftop antennas, or small cell deployments more common with 5G RANs. An alternative to installing servers at a node is using a local data center to serve multiple nodes. Servicing multiple nodes in this way is commonly associated with cloud RAN (C-RAN), but is not the only defining characteristic of C-RAN architecture; nor is it only used in C-RAN.

RAN deployments at the edge have benefits including lower latencies, improved user experiences, optimized network efficiency, reduced network congestion, and local compute power for devices. These benefits open up or improve use cases including autonomous vehicles CV2X (Cellular Vehicle to Anything), mobile gaming, and support for the Internet of Things (IoT).

Virtualizing RAN Infrastructure at the Edge

Many RAN deployments are in the process of being virtualized through software-defined networking (SDN) and network functions virtualization (NFV). The edge becomes more accessible and reasonable when using a virtual RAN (vRAN) architecture. This is because the network operators can split the RAN functions between different aspects of the RAN. For example, vRAN is commonly split between the central unit (CU) and distributed unit (DU).

While the CU may be on-site at the edge with a DU, it can also be more centrally located at an aggregation site and interact with multiple DUs. A CU operates protocols including the Radio Resource Control (RRC) and Packet Data Convergence Protocol (PDCP).

The RRC ensures the quality of service, connects user equipment to the RAN, and broadcasts information. The PDCP compresses and decompresses IP data stream headers, transfers user data over the RAN, among other technical functions. These are examples of the control and user plane functions.

The DU controls protocols are designed for the lower network levels of the OSI model. The protocols include the radio link control (RLC), medium access control (MAC), and the PHY protocol. The last of the list is called PHY because it interacts with the physical layer of the network, typically the node’s radio unit.

A radio unit consists of the antenna and some software. The antennas of course transmit and receive the radio frequencies over the air. The associated software converts the data received as frequencies into a format the rest of the RAN functions can read.

In 5G RANs, antennas are being upgraded to multiple-input, multiple-output (MIMO) antennas, more specifically referred to as massive MIMO in 5G networks. Massive MIMO is multiple antennas in one unit with a physical size corresponding to the frequency it supports. Additionally, MIMO technology has much more transmission ports that increase the network capacity and data throughput. The catch here is it requires more processing resources to support all antenna signals. Having edge computing resources can help support massive MIMO.

Use Cases That Benefit From the RAN Edge

A number of use cases are possible with computing power closer to the user. Using edge computing in a RAN reduces latency, alleviates network congestion, aids autonomous vehicles, improves mobile gaming experiences, and supports dense Internet of Things (IoT) deployments, among other use cases.

Lower Latency and Reducing Network Congestion

Moving resources to the RAN edge reduces latency because instead of processing and analyzing data in the cloud, it can be done closer to the user. In short, data spends less time going through the network and returns to the user faster.

This helps to ease network congestion because everyone’s data is not going over the same paths to the network core or cloud, but instead is localized. Basically, not everyone is on one highway going to the same distant location. Instead, they are only on the highway for a short time before exiting and arriving at their destination. This leaves room for other drivers that are entering the highway further down.

Increasing computing power throughout the RAN gives individual nodes the power to intelligently route data over the network. Instead of relying on inefficient routing tables, the local computing power supports routing software that is aware of network health. Since the software is aware of how the different connections are performing, it can send traffic over an optimal route.

Self-Driving Cars

Autonomous vehicles and self-driving cars are a popular use case discussed with edge computing and 5G (CV2X Cellular Vehicle to anything). An important element to note is most of the functions an autonomous vehicle relies on to function safely and effectively can and are done within the vehicle. Relying on edge computing to analyze and process data used for when to break is dangerous. Instead, secondary functions can be offloaded. The “5G Edge Computing Whitepaper” published by the FCC’s 5G IoT Working Group, suggested offloading the storing and updating of detailed maps to the edge.

Mobile Gaming at the RAN Edge

Another popular set of use cases for edge computing are augmented reality (AR) and virtual reality (VR). Both of these require low latency and consume a large number of computing resources. However, they are a subset of a larger use case that will require edge computing for the same reasons; mobile gaming, as the graphics quality and technical complexity of mobile games are increasing.

Phones running advanced games on themselves suffer from short battery life. So, putting the compute resources separated from where the gameplay occurs makes sense. However, if the data processing is in a central cloud, the latency would make any game unplayable. This makes edge computing important to mobile gaming for the reasons stated above for low latency and reducing network congestion.

Dense IoT Deployments

Dense IoT deployments put a lot of strain on a network because of their combined demand for computing resources and a high degree of data creation. IoT devices are often small and are not designed with a lot of computing power within them. Edge computing is able to take over processing and analyzing a large amount of data an IoT device’s sensors created throughout a day. Edge computing on the RAN specifically is beneficial here because the IoT device is sending its data over the network to wherever the computing resources are. Therefore, having those resources at the nearest network node allows for the data to go over the infrastructure it would use anyways and get to the resources quickly, reducing network congestion.