5G Small Cell Backhaul Networks using mmwave bands

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1 5G Small Cell Backhaul Networks using mmwave bands Andreas Kassler Karlstad University, Sweden 1

2 5G for Smart Cities 2

Software Defined and Cloud Network Flexibility

Networks 10 Tbpsper Km2 Mission Critical

Density Low Cost <1 millisecond Deep Coverage

Security High Availability High Reliability <1

3 The 5G Vision Unified Connectivity Multi-Gigabits per second Extreme Datarates Software Defined and Cloud Network Flexibility Massive amount of Small cells Enhanced Mobile Networks 10 Tbpsper Km2 Mission Critical Services Massive Internet of Things Ultra High Density Low Cost <1 millisecond Deep Coverage Ultra low Energy Ultra Low Latency Strong Security High Availability High Reliability <1 out of 100 million packets lost challenging locations 10+ years of battery life 3

air interface (mmwave Spectrum NR) Challenging interference

4 Extreme Mobile Broadband PICTURES COURTESY QUALCOMM Extreme Capacity to each user and extremely dense deployments Multi Gbps air interface (mmwave Spectrum NR) Challenging interference management and backhaul design Flexible architecture: NFV, SDN and CloudRAN 4

5 Extreme Mobile Broadband PICTURES COURTESY QUALCOMM Extreme Low Latency Tactile Internet < 1 ms Challenging air interface and system architecture design 5

6 Extreme Mobile Broadband PICTURES COURTESY QUALCOMM Immersive Experience 4K plus life streaming VR (Pokemon Go is just the beginning) 6

Negligible E2E loss rate Low latency: Avoid Retransmissions

7 5G as enabler for New Applications PICTURES COURTESY QUALCOMM AUTONOMOUS DRIVING INDUSTRIAL AUTOMATION Extreme Reliability Negligible E2E loss rate Low latency: Avoid Retransmissions Link and Path diversity for fault tolerance and seamless mobility 7

8 5G as enabler for New Applications AUTONOMOUS MANUFACTURING PICTURES COURTESY QUALCOMM INDUSTRIAL AUTONOMOUS AUTOMATION DRONES SMART GRID REMOTE SURGERY 8

Ap p Ap p Operating System Specialized Packet Forwarding Hardware Ap p Ap p Ap p Operating System Ap p Specialized Packet Forwarding Hardware P4 P4: programmable Ap p Ap p Operating System

9 Software Defined Networking - Principle 3. Well-defined open API Northbound Interface App App App Network Operating System SDN Controller 2. At least one good operating system Extensible, possibly open-source 1. Open interface to switch hardware Southbound Interface, e.g. OpenFlow Ap p Ap p Operating System Specialized Packet Forwarding Hardware Ap p Ap p Ap p Operating System Ap p This is precisely how you must process packets! Ap p Ap p Operating System Specialized Packet Forwarding Hardware Ap p Ap p Ap p Operating System Ap p Specialized Packet Forwarding Hardware P4 P4: programmable Ap p Ap p Operating System Specialized Packet Forwarding Hardware Ap p Specialized Packet Forwarding Hardware McKeown et.al.: OpenFlow: Enabling Innovation in Campus Networks, CCR 2008 P4: Programming Protocol-Independent Packet Processors, ACM Sigcomm CCR, July

interconnect Andromeda: NFV stack for containers Espresso

10 Its happening Example: Google applies several SDN principles Jupiter: Datacenter interconnect B4: WAN interconnect Andromeda: NFV stack for containers Espresso Google Brings SDN to the Public Internet Amin Vahdat, ONS, April 4,

Network Function Virtualization (NFV) - Principle Old Telco Model - HARDWARE NEW Telco Model

Router Automation Reduce TTM Orchestration Elasticity Apply Cloud principles to

Additional complexity more components, interfaces, more things that can go wrong Key

Telco Cloud: advanced networking needs to be automated COTS compute, mem, disc SDN helps NFV

11 Network Function Virtualization (NFV) - Principle Old Telco Model - HARDWARE NEW Telco Model - VIRTUALIZED vrouter vrouter VNF-A vdpi vdpi vhlr vqoemon DPI, Firewall, NAT, QoE Mon HLR Router Automation Reduce TTM Orchestration Elasticity Apply Cloud principles to Telco&Networking But: Flexibility decoupling software from hardware Agility Scale-In and-out Additional complexity more components, interfaces, more things that can go wrong Key difference IT Cloud vs. Telco Cloud: advanced networking needs to be automated COTS compute, mem, disc SDN helps NFV in network automation and virtualization less errors Network Functions Virtualisation - An Introduction, Benefits, Enablers, Challenges & Call for Action (White Paper Oct/2012) 11

12 Its happening 12

13 5G RAN and Core Research challenges High Capacity and reliable Baseband Pool Interconnection from the Cloud Cooperative Radio and low latency Fronthaul/Backhaul joint optimization Base Station Platform on commodity servers NFV realtime performance aspects due to virtualization NFV Management, Orchestration and Security NFV Performance Benchmarking NFV Placement Optimization Control&Data plane split Programmable Control and Dataplanes Signalling traffic explosion (scaling VMs) 13

14 New Airinterface and Deployment <1GHZ: LONG RANGE, LOW POWER IOT GHZ: ADVANCED LTE TYPE FOR MISSION CRITICAL GHZ: ADVANCED LTE TYPE FOR MISSION CRITICAL > 6 GHZ: MMWAVE, EXTREME BANDWIDTH, SHORT RANGE, DIRECTIONAL ANTENNAS, FRONTHAUL AND BACKHAUL > 6 GHZ: MMWAVE, EXTREME BANDWIDTH, SHORT RANGE, DIRECTIONAL ANTENNAS, FRONTHAUL AND BACKHAUL WIDE AREA DEPLOYMENT AND LOCAL HOTSPOT DIVERSE DENSE DEPLOYMENT (MESH, PEER-TO-PEER) 14

Beamforming, Highly Directional Beams Challenge for Access and Transport Radio

15 Propagation Effects LOS/NLOS/Outage due to high pathloss, intermittend links Atmospheric effects, rain Antenna MMWave Challenges Directional Antennas Beamforming, Highly Directional Beams Challenge for Access and Transport Radio Challenges for Power Amplifier due to linearity and high bandwidth Low Tx Power and Rx Sensitivity 15

16 Propagation Effects LOS/NLOS/Outage due to high pathloss, intermittend links Atmospheric effects, rain Antenna MMWave Challenges Directional Antennas Beamforming, Highly Directional Beams Challenge for Access and Transport Radio Challenges for Power Amplifier due to linearity and high bandwidth Low Tx Power and Rx Sensitivity 16

17 Transport Layer issues for 5G NR NLOS High Latency Problems for Transport Layer Intermittent Link at mmwave Frequencies Low Latency queuing schemes (e.g. CoDel) lead to low effectiveness Marcus Pieska, Andreas Kassler, TCP Performance over 5G mmwave Links - Tradeoff between Capacity and Latency, submitted to IEEE Wimob

18 Dense Small Cell Networks Dense Deployment of Small Cells Core Network Reuse enb Umrella cell HETNET Wireless mesh backhaul to save cabling costs Small inter-cell distance low energy for AN Cost Efficient solutions with high capacity enb Minimize Energy Consumption by switching Off SC SC Guarantee backhaul is connected SC SC enb SC Mesh backhaul provides resiliency against link failures and loadbalancing Fast SDN based local reconfiguration 18

19 Energy Efficient Small Cell Backhaul Operation INTERNET MeNB One sector of a Macro enb with fixed access to the Internet Several Small Cells (s) are deployed to increase capacity Enrica Zola, Andreas Kassler, and Wooseong Kim: Joint User Association and Energy Aware Routing for Green Small Cell mmwave Backhaul Networks, in IEEE WCNC 2017, San Francisco, March

20 Energy Efficient Small Cell Backhaul Operation INTERNET MeNB mmwave backhaul (BH) links to connect the s and the MeNB Mesh BH

21 Energy Efficient Small Cell Backhaul Operation INTERNET 1 UE1 MeNB 2 UE2 UE UE3 6 mmwave BH links Some users (UEs) in the area downloading data We consider downlink only - MeNB is the sender - UE is the receiver 21

22 Energy Efficient Small Cell Backhaul Operation INTERNET 1 UE1 MeNB 2 UE2 5 UE4 3 4 UE3 6 mmwave BH links Some users (UEs) in the area downloading data Multiple possibilities to connect Microwave access (LTE) on access links (AL) - Macro AL - Small Cell AL 22

23 Energy Efficient Small Cell Backhaul Operation INTERNET 1 MeNB 2 Route 1: associate with Macro UE3 Route 2: associate with Small cell 5 power on 3 and 5 6 mmwave BH links Some users (UEs) in the area downloading data Multiple possibilities to connect Microwave access (LTE) on access links (AL) - Macro AL - Small Cell AL Route 3: associate with Small cell 6 power on 3, 4 and 6 23

24 Modelled as Mixed Integer Linear Program 1) save power and 2) satisfy users demand 24

25 MILP: Goal Configured through SDN based on Model User association to enb i Routing on meshed BH links (i,j) 1) save power and 2) satisfy users demand enb i activation 25

26 MILP: Goal Configured through SDN based on Model User association to enb i Routing on meshed BH links (i,j) enb must be powered ON 1) save power and 2) satisfy users demand enb i activation 26

27 MILP: Goal Configured through SDN based on Model User association to enb i Routing on meshed BH links (i,j) enb must be powered ON 1) save power and 2) satisfy users demand enb i activation enb must be powered ON only if used 27

demand Routing on meshed BH links (i,j) Use only links where users

28 MILP: Goal Configured through SDN based on Model User association to enb i enb must be powered ON 1) save power and 2) satisfy users demand Routing on meshed BH links (i,j) Use only links where users data flows enb i activation enb must be powered ON only if used 28

29 MILP: Goal Model formulated as a Mixed Integer Linear Problem CPLEX branch-and-cut search strategy GOAL: Minimize the total energy consumption (of all the enbs) while guaranteeing the rate demanded by each user Users demanded rate provided as an input to the problem Energy consumption at each enb and users rate: output 29

30 MILP: Solutions INTERNET MeNB If the total demanded rate can be satisfied by the MeNB 1 UE1 2 UE2 5 UE4 3 4 UE3 6 Switch off all the s and all the BH links Solution with the lowest power consumption 30

31 MILP: Solutions INTERNET 1 MeNB UE1 2 UE2 UE UE3 6 As the demand from the UEs increases, we need to switch on the s E.g.: 2 s are switched on Solution with higher power consumption Some users may demand more rate than available Pre-process: assign 0 Mbps to such users and count as blocked users 31

32 Total Network Power Consumption 32

33 Results #Active SC 33

34 Results #Active SC Almost half of the total SCs are ON x2 x3 34

35 Results #Active SC Almost all the SCs are ON x3 x10 35

36 UE Blocking Probability Due to the random nature of users drops and not to any limited capacity in the backhaul network and/or in the routing scheme 37

37 Avg rate obtained by each user vs demanded rate 38

38 Avg extra power consumption relative to the Always ON case 39

39 Avg extra power consumption relative to the Always ON case Flattens because almost all mmwave BH transceivers are ON 40

40 Avg rate that flows on all the BH links that are active 41

41 Target: Balance between Energy and Spectrum Efficiency High spectrum (SE) and energy efficiency (EE) Problem: UE association & BH traffic routing No switching off this time SE: AN > Minimum PRBs to satisfy QoS of UE i (deviating up to a threshold from the fewest) EE: AN+BH Minimum power needed to serve the UE traffic (among all BSs and alternative BH paths) Agapi Mesodiakaki, Enrica Zola, and Andreas Kassler: User Association in 5G Heterogeneous Networks with Mesh Millimeter Wave Backhaul Links, in: IEEE WoWMoM 2017, Macau, June

42 Example Rate demand 100 Mbps δ thres =1 no deviation from min PRBs maximum SE min (P AN +P BH ) maximum EE P AN Type of BS (number of Tx chains, scaling factor, power per PRB) Number of PRBs enb: P AN =59.87 W SC 7: P AN =1.28 W 43

Example P BH BH route Link bandwidth, channel conditions BH traffic Solutions w/o LB SC 7, route 2 LB SC 7, route 1 enb no BH link SC 7, route 1 L1(750 MHz, -57.25dBm, 100Mbps) L2 (100 MHz, -62.

43 Example P BH BH route Link bandwidth, channel conditions BH traffic Solutions w/o LB SC 7, route 2 LB SC 7, route 1 enb no BH link SC 7, route 1 L1(750 MHz, dBm, 100Mbps) L2 (100 MHz, dBm, 100 Mbps) SC 7, route 2 L3(500 MHz, dBm, 300Mbps) L4 (200 MHz, dBm, 100 Mbps) enb: P BH =0 W SC 7, route 1: w/o LB: P BH =0.752 nw LB: P BH =2.09 nw SC 7, route 2: w/o LB: P BH =0.671 nw LB: P BH =2.89 nw Algorithms w/o LB BH power calculation as if BH links were exclusively used by UE i LB by jointly considering the traffic of the already associated Ues, starting with the UEs with the fewest candidates 44

Simulation Scenario 100, 150, 300 Mbps GBR demands Hotspot traffic Orthogonal channels SCs-eNB SCs in different clusters interfere BH: 73 GHz, variable BW (0.

44 Simulation Scenario 100, 150, 300 Mbps GBR demands Hotspot traffic Orthogonal channels SCs-eNB SCs in different clusters interfere BH: 73 GHz, variable BW ( GHz) Algorithms: Proposed ESE w/o LB, ESE with LB Highest SINR with random path in BH RangeExpansion (+13 db) with random path in BH MPL (minimum path loss) with random path in BH BH-hop with LB [9] BS with max. spectrum efficiency, among them select the one with the minimum number of BH hops, least loaded 45

45 Simulation Results Relative percentage difference compared to MPL-random Positive percentage increase in the studied metric compared to MPL-random, whereas negative decrease 46

46 5G will be based on Conclusions Applying Cloud Paradigms to the Telco World Using Software Defined Networking for flexible traffic steering New Radio providing large capacity New challenges Dense networks require energy efficient operation User association and offloading need to consider backhaul Transport Layer needs to be more efficient Optimization more complex 47

5G in the Automotive Industry A Telecoms Manufacture's view Preben Mogensen, Nokia Networks Fellow & Professor at Aalborg University

5G for people and things Key to the programmable world i 5G in the Automotive Industry A Telecoms Manufacture's view Preben Mogensen, Nokia Networks Fellow & Professor at Aalborg University 1 Nokia Solutions