5G Cloud-RAN and FronthaulAricent FH-TSS Aricent FH-TSS 1914.3 RoE Aricent FH-TSS Aricent FH-TSS...

Copyright © 2018 Aricent. All rights reserved.

5G Cloud-RAN and Fronthaul5G-KS 2018 (IITM Research Park)

RaviKanth Pasumarthy, AVP Technology

Vinesh Varghese, Director Technology

2Copyright © 2018 Aricent. All rights reserved.

5G Use-cases & Requirements

UHD Broadcast

Self Driving Car

Remote

Manufacturing

Remote

Healthcare

3D Video,

4K,8K UHDGigabytes in a

Second

Traffic Safety &

Control

Media Everywhere

Smart

Home/Building

Smart Meter

Fleet Management

Tracking

Smart City

Massive MTC (mMTC)Ultra Reliable Low Latency Communication

(uRLLC)

Enhanced Mobile BroadBand

(eMBB)

Features

• Very High Bandwidth

• Widespread Coverage

Industrial

Application &

Control

IMT-2020 Requirements

• Downlink / Uplink Peak Data Rate 20 Gbps / 10 Gbps

• User plane latency: 4ms

• Downlink Peak Spectral Efficiency 30 bits/s/Hz

• Uplink Peak Spectral Efficiency 15 bits/s/Hz

Features

• Massive numbers

• Small Data Volumes

• Low Cost

• High Battery Life


• Connection Density 1 million devices per sq.km

• Battery life > 10 Years

Features

• Ultra Reliable

• Very Low Latency

• Very High Availability


• User plane Latency < 1 ms

• Control plane Latency < 20 ms

• Reliability 99.9999%

High Speed Train

AR/VR

Autonomous Vehicle

Online Predictive Maintenance

Infotainment

Platnooning

Automotive Transport Society Healthcare Factory Utilities

Remote surgery

Wearables

Remote consultations / Telemedicine

Task automation

Predictive Maintenance

Mission-critical control

Smart metering

Smart Utility Mgmt(Water, Gas Metering, power, pollution …)

Smart Traffic Mgmt(traffic routing, parking, monitoring..)

Smart Education

Smart Agriculture

Smart Grid

Intelligent Transport Systems

UAV-based surveillance

Smart airport

Fleet Management

Railway Signalling

Public Safety

Mission-critical PTT

Mission-critical video (high upload)

Mission-critical sensors (drones, smoke detector, security camera)

Multimedia

Augmented Reality / Virtual Reality

Gaming

Transforming and linking multiple industries with Telecom


Key Principles of 5G Network

• New Air-interface• mmWave• Massive MIMO and

beamforming

New Radio (NR)

• Next Gen Core• Multi RAT Support• MEC Support• Network Slicing

Network Elements

• Virtualized / Cloud-RAN

• SDN/NFV based Networks

• Distributed deployment

Programmable Networks

• Fronthaul (ideal or non-ideal)

• Mid-haul / Backhaul• Resource differentiation• Synchronization

Transport

• Artificial Intelligence• Big-data and Analytics• Network Automation• Security

Management

• Flexible numerology – allows multiplexing of services with qualify and latency requirements and also large SCS for mmWave

• Spectrum - Allocation of higher frequency bands – ensures additional spectrum and wide bandwidth availability, ensuring support for very high data-rates

• Adaptable air-interface - scalable sub-carrier spacing, variable slot-lengths, scalable TTI, minimize control overhead, short PUCCH (for latency) and long PUCCH (for coverage), advanced channel coding techniques, flexible HARQ

• Self-contained slot structure (TDD) to reduce latency – adaptable UL/DL switching, data/ACK in same slot, SRS in every slot etc

• Ultra-lean design to enhance network energy performance – minimizing always-on signals, reduce periodicity of PSS/SSS/PBCH

• Shortened TTI and processing– reduces latency

• Support of carrier aggregation of upto 16 carriers,

• Beam-centric design enabling usage of beamforming and massive number of antennas to improve performance

• Service Based Architecture (SBA) – stateless, open, flexible and realization using VNFs, enabling movement and scaling of AFs dynamically

• CUPS: Separation of control and user-plane

• SDN: Improved QOS model for packet flow and policies. Helps defining service chaining for SDN based data flow

• NFV: Orchestration and Virtualization (NFV) – de-couple logical function from hardware

• Slicing – logical end-2-end networks tailed to customer needs

• MEC Support for low-latency services and offloading of data at EDGE. It provides Computing resources, Caching, Low latency and less traffic through core to meet the requirements for use-cases

• Exposure Functions, APIs, Common API Framework – to enable external interworking with 3GPP

• New 3GPP accesses: wire line-wireless convergence, satellite access. Also allows subscribe to events and have analysing and optimizing network performance and behaviour wrt services being offered

Unification of multiple technologies and network evolution to connect multiple verticals


5G Transport Architecture Terminology

✓ Fronthaul – Network between RRU/RU (Remote Unit) and DU (Distributed Unit) – can be CPRI or eCPRI or IEEE 1914.3

✓ Midhaul – Network between DU and CU (Centralized Unit) – “F interface”

✓ Backhaul – Network between CU and 5G NGC (and EPC)

eCPRI

4G - CPRI

1914.3 RoE

1914.3 RoE

eCPRI

Aricent FH-TSS Aricent FH-TSS

1914.3 RoE

Aricent FH-TSS

Aricent FH-TSS

SDN/NFV & MANAGEMENT CONTROL & ORCHESTRATION

Ref: T-TUT-HOME-2018-MSW-E

UP latency

eMBB – 4ms, URLLC – 0.5ms

CoverageFH 1-20km, typically p2p MH 20-40km, p2p or p2mp BH upto ~200km, p2mp or mp2mp

Latency~100us 1.5 to 10ms

BackhaulBackhaulMidhaul

Fronthaul

CU/MECDU

CN

UNI

UNI

UNI UNI

RRUeCPRI F1 NG

Time Server

~100-500us


5G Cloud-RAN


(Typical) RAN Architecture Evolution

For typical Macro network deployment, RAN evolution has evolved as

• Distributed RAN – with separate BBU HW per sector connected to RRH via optical interface

• Cloud-RAN – where the BBU is pooled on common (COTS) HW at centralized site and connects to multiple distributed units (RRH) via optical interface

• (e) Cloud-RAN – where CU, DU split is done with standardized interface between CU/DU, and Ethernet as option to connect to RRU

• With Cloud-RAN based architecture, NFV techniques and data center processing capabilities can be exploited and also enables coordination and centralization in mobile networks

RRH

fiber

fiber

TRANSPORT UNIT

CONTROL UNIT

BASE BAND

Distributed RAN

vBBU

TRANSPORT UNIT

CONTROL UNIT

BASE BAND

Cloud RAN

BASE BAND BASE BAND

Representative figure

CU

TRANSPORT UNIT

CONTROL UNIT

(e) Cloud RAN

DU

BASE BAND BASE BAND BASE BAND

F1

Ethernet


RAN Split Options

• RAN -split options helps to reduce the fronthaul requirements and also allow flexible and scalable HW implementations

LatencyData-rate

RRC PDCPHigh

RLC

Low

RLC

High

MAC

Low

MAC

High

PHY

Low

PHYRF

Data

RRC PDCPHigh

RLC

Low

RLC

High

MAC

Low

MAC

High

PHY

Low

PHYRF

Option 1 Option 2 Option 3 Option 4 Option 5 Option 6 Option 7 Option 8

Data

4Gbps 4016Mbps 4000Mbps 4000Mbps 4133Mbps

7a: 10.1-22.2Gbps7b: 37.8-86.1Gbps7c: 10.1-22.2Gbps

157.3Gbps

3Gbps 3024Mbps 3000Mbps 3000Mbps 5640Mbps 7a: 16.6-21.6Gbps7b: 53.8-86.1Gbps7c: 53.8-86.1Gbps

157.3Gbps

10ms 1-10ms ~100us ~100ms 250us

UL data

Latency

DL data

c

Scenario - 100MHz and 256QAM UL/DL, MIMO layers – 8 UL/DL, Number of antenna ports – 32,IQ – (2*7-16)) UL/DL

Latency requirement becomes stringent and data-rates also increase as we move to option-7/option-8


(Common) RAN Split Options

• Most commonly used RAN-Split options are Option-2, Option-6, Option-7.x and Option-8

• Option-8 is equivalent to Small-cell type of realization

• Centralized scheduler possible for options-6 onwards leading to better realization of high-gain coordinated algorithms (like joint scheduling, joint reception, and joint transmission options as part of 5G CoMP)

• Provides scalable and virtualized architecture options based on CU/DU and RU architecture

• Allows for cloud-RAN realization with CU running in cloud, and connected to multiple DU

• DU will also be virtualized and can be scaled-up/down based on the load/traffic/capacity requirements

• Fronthaul can be based on CPRI or eCPRI

Option -2

RRC

PDCP

RRM

CU

RLC

PHY SW

DU

MAC

RF

RU

Option -8

RRC

PDCP

RRM

CU

RLC

PHY SW

DU+RU

MAC

RF

Option -7.x

RRC

PDCP

RRM

CU

RLC

PHY-high SW

DU

MAC

RF

RU

PHY-low SW

CPRI

• CPRI is pre-dominantly used in 4G fronthaul. Max data rate supported in CPRI v7.0 is 24.33 Gbps (rate 10)

• For typical LTE scenario of 20MHz, 2x2 DL MIMO, the fronthaul data rate is ~1.96Gbps

• The IQ data of different AxCs are multiplexed by TDM scheme onto an electrical or optical transmission line, and link is always “ON” with Constant bit-rate data

• Specified for point-to-point topology and is more antenna dependent (rather than traffic dependent)

eCPRI

• eCPRI is used as fronthaul between CU/DU and RU for 5G network, using packet based fronthaul transport network

• Enables flexible functional decomposition while limiting the complexity of the eRE - Supports for Ethernet interface types – 10G, 25G, 40G and 100G

• More traffic dependent rather than antenna dependent, and and Ethernet can handle this with support of statistical multiplexing

• Enables realization of SDN/NFV based fronthaul


5G Fronthaul Transport Requirements

Handling of very high data-rate requirements

Handling of traffic and for different service types (or slices) with varied priorities (include packet prioritization) and quality of service over a unified network

Flexibility to scale the bandwidth based on user plane traffic

Statistical multiplexing for aggregating traffic from multiple sites

Should be traffic dependent and NOT be antenna dependent

Support for multiple network architectures

Meet stringent Synchronization and Timing requirements for 5G

Cost / Performance Trade-off by selecting proper FH/BH suitable for the network deployment

p(D) = offered traffic can be transported without queueing with a probability Ref: 5G transport network requirements for the next generation fronthaul interface

• Mix of transport technologies – optical, packet, microwave

• Ethernet based solutions provide - Reuse of existing infrastructure, flexibility, statistical multiplexing, flexible routing

• SDN is a key enabler for converged FH/BH networks in 5G to virtualize the transport network to support slicing and allow a flexible deployment of virtual functions in different places of the network

• GNSS, 1588, PTP are some of the synchronization options


5G RAN Realization


Towards Software Defined “Open” Network

Monolithic, Custom build Solutions

Closed and Proprietary interfaces

Built around available network

Flexible, COTS based Solutions

Open and modular interfaces and flows

Network defined by Services

• CU/DU Hardware

• 5G is accelerating the adoption of commodity HW, disaggregated solution within Telco’s.

• Limited SOC options available for 5G RAN realization, CPU based (x86 or ARM) solution with FPGA used

• ASIC based solutions for baseband will come into picture once the solutions are verified

• RU Hardware

• 5G RU designs will be “inherently intelligent”. Part of PHY runs in RU and also handling for digital beam-forming functionality

• This will also have challenge wrt some of the key considerations of RU design like size, weight, and power

• Realization of Virtualized cloud native network and moving towards “open” interfaces

• Reduction in overall deployment timelines with disaggregation

• Built around usage of open-source and open interfaces in overall solutioning along with 3GPP standards

Migration towards Software-defined “Open” Network philosophy

Hardware &Software

Software

Telecom/DatacomProtocols & Application

White Box HW

INTEGRATED DISAGGREGATED

Network Function Abstractions

HW/ Platform Abstractions

White Box HW

OPEN & MODULAR SW

Pre-tested & Feature Rich

HW Platform Independent & Cost Effective


CU/DU Solution Trends

• Moving towards Open-Hardware, Open-Software and “Open-Interfaces” paradigm

• Existing Central offices being transitioned to Datacentres, with additional that will be spawned to cater to the unique use cases.

• Reducing the overall TCO is still a priority, Solution around GP processor architectures, still drives the innovation.

• Solutioning compute , storage , network node elements around the xhaul will be a key driver for innovation.

Factors influencing CU/DU Solution

Intel Server

ARM based SOC

DSP based SOC

FPGA

ASIC

Smart-NIC

Power Consumption

Scalability

Virtualization

Deployment / Use-cases

xHaul Interfacing

• Reference HW solution being proposed in open-source computing hardware can be used for 5G Network solution till DU

• Open19, OCP and also Intel Rack Sack Architecture are some of the options that can be explored

Synchronization


SmartNIC/FPGA based acceleration in RAN

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORENETWORK DATA PLANE

NETWORK CONTROL PLANE

SECURITY STORAGE

XEON

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

XEON

FPGA/ASIC

NETWORK DATA PLANE

SECURITY Acc & STORAGE Tranport

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORE

CORESNIC SW NETWORK CTRL PLANE

SECURITY SERVICES

STORAGE SERVICES

SMARTNIC

PCIE

TRADITIONAL NIC

INS

TA

NC

E

INS

TA

NC

E

INS

TA

NC

E

INS

TA

NC

E

HYPERVISOR

vSWITCH StorageCrypto

CompressSecurity

SMART NIC

INS

TA

NC

E

INS

TA

NC

E

INS

TA

NC

E

INS

TA

NC

E

HYPERVISOR

vSWITCH StorageCrypto

CompressSecurity

• Fully programmable, FPGA based and enables disaggregated “cloud” based architecture

• Optimization at Platform Level and replaces standard NICs

• Workload specific Acceleration for better TCO

• Reducing the load of CPU by offloading to SmartNIC leading to leading to better CPU core utilization

• In-line processing of data-plane

• Can be programmed and scaled on-demand resulting in a real “elastic” cloud


Programmable data-plane with SmartNIC

• As VNFs are scale to meet high processing requirements, performance goals for data-plane acceleration can be realized with SmartNICs

• Distribute and optimize workloads between x86 server and software-reconfigurable, FPGA-based SmartNICs in virtualized environments

• Performance at lowest power but lacks major flexibility

• Cores & Optimized SW

• Match-Action Pipeline

• Connection tracking

• Packet Parsing

• High Performance programmable data planes

• FPGA Flexibility but at increased cost & power

• ASIC highest

• Flexible Architecture Partition to enable high performance, throughput workloads.

FPGA ALGORITHMS

ASICCORES

SOFTWAREDATAPLANE

PROGRAMMING

Programmable SmartNICs help in accelerating critical BB and security workloads and migrating acceleration services


RU Solution - Solution trends

Enabling Post Moore Era, Domain Specific Architecture

Highly Integrated Heterogenous SoC, solution

• Processing Core (Reduced process Node) for Radio Apps

• FPGA’s for unique digital/acceleration logic

• SW Programmable Engines , Enabling custom Functions

• Integrated Data Converters

• Scalable & high Performance IO

Platform SW/Acceleration SW : Common Framework

Enabling Scalable RU Product,

• Reduced Power Envelope (Target within PoE Specs)

• Better Performance & Smaller Form factor Designs

• High Through put, low latency

• Higher Adoption and flexibility leads to lower TCO.

5G Radio Unit

Domain Specific Architecture

Adaptable Radio

Architecture

Common SWframework


Thank You

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Santa Clara, CA 95054

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