5G-PICTURE. 5G Programmable Infrastructure Converging disaggregated network and compute Resources

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1 5G-PICTURE 5G Programmable Infrastructure Converging disaggregated network and compute s Anna Tzanakaki (University of Bristol, UK, NKUA, Greece)

2 Consortium IHP GmbH (Coordinator) University of Bristol ADVA Optical Networking Airrays GmbH Blu Wireless Technology CNIT COSMOTE EURECOM Fundació Privada i2cat, Internet I Innovació Digital a Catalunya Telecom Italia S.p.A Mellanox Huawei Technologies Dusseldorf GmbH Technische Universität Dresden Transpacket Paderborn University COMSA INSTALACIONES Y SISTEMAS INDUSTRIALES SL Ferrocarrils de la Generalitat de Catalunya Zeetta Networks University of Thessaly Universities (4x), Research Institutes (4x), SMEs (3x), Operators (3x), Industry partners (5x) 30 months duration Start: 01/06/ million euro EU funding 2

3 5G-PICTURE Main Objectives 5G-PICTURE will design and develop an integrated, scalable and open 5G infrastructure with the aim to support a variety of operational and end-user services for both ICT and vertical" industries. This infrastructure will rely on a converged fronthaul and backhaul solution, integrating advanced wireless access and novel optical network domains. 5G-PICTURE will rely on network softwarisation to enable an open reference platform instantiating a variety of network functions over a unified operating platform slicing and service chaining to facilitate optimised multi-tenant operational models

4 Concept 5G-PICTURE proposes to integrate network and compute/storage resources in a common infrastructure. To address the limitations of current solutions 5G-PICTURE will adopt the novel concept of Disaggregated-Radio Access Networks (DA-RANs) allows any service to flexibly mix-and-match and use compute, storage and network resources through HW programmability relies on network softwarisation to enable an open reference platform instantiating a variety of network functions adopts slicing and service chaining to facilitate optimised multi-tenancy operation Hierarchical compute & storage structure supported by a network hierarchy Integrated programmable wireless technologies at the edge and a hybrid passive/active optical transport network

5 Technical Approach Τo address the limitations of D-RAN and C- RAN will develop flexible functional splits Adoption of the notion of DA-RAN relying on resource disaggregation mixing-and-matching of resources Development of novel technology solutions and control & management platforms enhanced network and compute HW and SW modularity and flexibility Creation and deployment of programmable network functions and intelligent orchestration schemes service chaining slicing & multi-tenancy 5G-PICTURE OS (Synchronization) (beam tracking) MPI MPI OPP MPI NFV Orhestrator (Signal Processing/ massive MIMO) BVT/ R BVT/ R Tx mmwave (FFT, ifft) Monitoring and Profiling SDN Controller (vepc) b) c) module λ1 module λ2 module λν PON a) (vmme, vbbu) Slicing Manager RAM module λ1 module λ2 module λν Operations and Support System (OSS) vcdn Storage controller controller BVT/ R BVT/ R Tx MPI Processing (specific) e) OPP d) MPI MPI Processing (general)

6 high network bandwidth Increased BBU sharing Multi-protocol Interface SYNC low network bandwidth Limited BBU sharing Overall Infrastructure : General Purpose Processor : Specific Purpose Processor : Remote Unit BVT: Bandwidth variable transponder : Bandwidth variable wavelength selection switch Processing at the Server Processing at the Optical Link Fronthaul Flow MAC b) a) Elastic Optical Network Data Centre processing Cycle Prefix & FFT RF to Baseband 2 (1) (1) λ1 λ2 BVT λν λ1 λ2 BVT Tx λν module λ1 module λ2 module λν c) module λ1 module λ2 module λν λ1 λ2 λν BVT Multi-protocol Interface SYNC CPU CPU CPU d Key Challenge: Converged Fronthaul and Backhaul Services Converged Network and Compute Services Disaggregation of s 5

7 high network bandwidth Increased BBU sharing Multi-protocol Interface SYNC low network bandwidth Limited BBU sharing Physical Network Infrastructure : General Purpose Processor : Specific Purpose Processor : Remote Unit BVT: Bandwidth variable transponder : Bandwidth variable wavelength selection switch Processing at the Server Processing at the Optical Link Fronthaul Flow MAC processing Cycle Prefix & FFT b) (1) RF to Baseband 2 (1) a) BVT BVT Tx λ1 λ2 λν λ1 λ2 λν Elastic Optical Network module λ1 module λ2 module λν c) module λ1 module λ2 module λν Data Centre λ1 λ2 λν BVT CPU Multi-protocol Interface SYNC d CPU CPU WiFi Small Cells WLAN GW HeNB Femto Cells 5G-Xhaul Wireless Backhaul/Fronthaul HeNB HeNB vbbu 2 vbbu VM Data Centers Integrated optical and wireless network infrastructure for transport and access capitalising the 5G-Xhaul physical infrastructure Wireless domain: Dense layer of small cells complemented by macro cells to ensure ubiquitous coverage Small cells can be backhauled to the macro-cell site either wirelessly using a combination of mm-wave and sub-6 wireless technologies or using a hybrid optical network platform Optical Domain Adoption of a dynamic and flexible/elastic frame based optical network solution combined with enhanced capacity WDM PONs BB Processing: s are connected to remote BB processing pools through high bandwidth transport links enb Macro Cell enb WDM-PON HeNB GW Wireless Access Backhaul vbbu 1 vbbu 2 TSON vbbu vbbu vbbu VM Fronthaul S GW/GSN PDN-GW 60GHz /Sub-6 links for FH/BH FH BH vbbu 1 EPC Internet 6

8 n on RF to Baseband Cycle Prefix & FFT RF to Baseband Cycle Prefix & FFT processing processing MAC MAC Convergence of Networking and Computation Fronthaul adopting flexible functional splits Mega DCs Internet Transport Network and Compute s Metro s Controller MetroNFVI Mid-DCs Processing parallelisation Full with commodity hardware and hybrid solutions Disaggregation of Network and Compute resources Mixing and matching of resources to efficiently support services HWA Local DCs s Controller NFVI RAM SSD s Controller NFVI Local DCs Macro-cells Frontlhaul Remote/regional DC Wireless Access RAM SSD Regional DCs Remote/regional DC s Controller NFVI Micro- DCs ent & ent & End-user services End-user services 8 End point End point

9 Processing Parallelization 2 a) b) c) d) RF to Baseband (1) Cycle Prefix & FFT Optical inter DC network Transport requirements: Split 2 processing DC MAC RF to Baseband (1) Cycle Prefix & FFT / processing Intra DC network Transport requirements: Split 3 / MAC RF to Baseband (1) Cycle Prefix & FFT / processing Intra DC network Transport requirements: Split 4 / MAC BBU sub-frame processing time < 1ms To reduce processing delay, BB processing is handled in parallel over disaggregated compute resources Model 1: parallel (or sequential) processing mode each function is distributed across multiple processing units (1:N) Model 2: Pipelining each processing unit handles a specific function adopting 1:1 mapping 9

10 Validation - Demo Activities Large DCs Internet RAM SSD RAM SSD Metro Metro Mid-DCs RAM SSD Macro-cells Wireless Access Mini DCs Micro- DCs Extensive demonstration activities to showcase ICT and vertical industry use cases Converged fronthaul and backhaul services in a smart city test-bed (city of Bristol, UK) Seamless service provisioning and mobility management in high speed railway environments - 5G railway experimental testbed (FGC, Barcelona, Spain) Media services supporting large venues with increased density and static-to-low mobility - stadium testbed supporting large venues (Bristol, UK) 19/07/

11 UK 5G Trials Programme 5G & University of Bristol & Bristol is Open SDNx & Cloud 5G & Big King s College London Fibre (Janet) 5G Consumer Use- Cases 5G Industry Use-Cases 5GIC, University of Surrey 11

12 Thanks for your attention! 5G-PICTURE Project Project Coordinator: Technical Manager: Eckhard Grass Anna Tzanakaki Project Website: Twitter: