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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
IMT-2020 Requirements
• Connection Density 1 million devices per sq.km
• Battery life > 10 Years
Features
• Ultra Reliable
• Very Low Latency
• Very High Availability
IMT-2020 Requirements
• 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
3Copyright © 2018 Aricent. All rights reserved.
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
4Copyright © 2018 Aricent. All rights reserved.
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
Copyright © 2018 Aricent. All rights reserved.
5G Cloud-RAN
6Copyright © 2018 Aricent. All rights reserved.
(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
7Copyright © 2018 Aricent. All rights reserved.
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
8Copyright © 2018 Aricent. All rights reserved.
(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
9Copyright © 2018 Aricent. All rights reserved.
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
Copyright © 2018 Aricent. All rights reserved.
5G RAN Realization
11Copyright © 2018 Aricent. All rights reserved.
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
12Copyright © 2018 Aricent. All rights reserved.
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
13Copyright © 2018 Aricent. All rights reserved.
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
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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
15Copyright © 2018 Aricent. All rights reserved.
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
Copyright © 2018 Aricent. All rights reserved.
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