Self-Organizing Networks in LTE and Quantification of Economic Benefits Amit Mukhopadhyay, Ph. D. Director, Network Modeling & Optimization -

Transcription

1 Self-Organizing Networks in LTE and Quantification of Economic Benefits Amit Mukhopadhyay, Ph. D. Director, Network Modeling & Optimization - Wireless Bell Labs 1

2 Agenda Self Organizing Networks (SON) fundamentals Economic model 2

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4 3GPP SON helping Operators solve their challenges OPEX reduction Fast adaptation to network conditions Increase network quality Avoid time-consuming and repetitive tasks Avoid drive tests Process simplification Avoid error-prone and slow manual operations world of data is dynamic so networks must adapt real time Provide Higher End User Quality of Experience Ensure service continuity Embed system and product expertise in the network Self Organizing Network (SON) is a 3GPPstandardized initiative which drives the building of intelligence and automation into the network itself to help operators solve those challenges SON provides Operators with a path to maximize their network performance with lower effort (and thus lower cost). 4

5 EPS Architecture: eutran and EPC Network Topology PCRF S7 PDN GW PDN GW S5/S8 S7c EPC Standards described the EPC elements as logical functions that can be integrated or distributed - Physical topology & implementation varies based on numerous considerations S1-MME MME MME S1-MME S1-U X2 S11 enb X2 SGW SGW S1-U S1-MME X2 S1-U Standards specified that enbs are interconnected via the X2 reference point to improve handover performance - X2 connectivity is logical, not necessarily physical - Many options of creating logical connectivity, with different cost implications enb typically connects to multiple MME s and S-GW to leverage load sharing / balancing capability and increases reliability enb eutran enb 5

6 SON Overview Self Configuration : Automatic installation procedures to get the necessary basic configuration for system operation. Works when the enb is powered up and has backbone connectivity but the RF transmitter is not yet switched on. Functions: Basic Set up + Initial Radio Configuration Self Optimization UE & enb measurements and performance measurements are used to auto-tune the network. Works when the pre-operational state is complete and the RF interface is additionally switched on. Function: Optimization/Adaptation Fig : 3GPP TS

7 Example Prelaunch and Post-launch Optimizations Pre-Launch Repeat until desired configurations achieved Design Configure Drive Test Analyze DT Results Resolve/Reconfigure Post-Launch Continuous operations PM Collect Data (Remotely) Top 10 PM Analyze Drive Test Other Backhaul RF Analyze DT Results Remote ly Resolvable Field Visits Don t know/dt required Resolve/Reconfigure 7 7

8 Key SON features Self Configuration - Network connection, database update, software download, - Physical Cell ID configuration - Neighbor Recognition Self Optimization - Load balancing - Hand-off optimizatyion - Interference co-ordination - Capacity and coverage optimization - Energy optimization Self Healing - Outage detection and compensation - Multi-homing 8

9 Physical Cell ID configuration Cell PCI needs to be: - Collision free - Confusion free Only 504 unique PCIs available, which need to be recycled among cells Determined during planning via planning tool and then configured into enodeb via EMS or manually/config files PCI algo New cell Automate configuration efforts 9

10 Automatic Neighbor Recognition (ANR) As a part of the normal call procedure, the enb instructs each UE to perform measurements on neighbor cells. 1.The UE sends a measurement report regarding cell B. This report contains Cell B s PCI. 2.The enb instructs the UE, using the newly discovered PCI as parameter, to read the ECGI 3.When the UE has found out the new cell s ECGI, the UE reports the detected ECGI to the serving cell enb. 4.The enb decides to add this neighbor relation A B Reduce pre-launch and post-launch configuration efforts 10

11 Load Balancing Objective: Distribute UEs camping on or connected to a cell to balance the traffic load. Delay or advance the handing over of UEs between cells. enb monitors load in the cell and exchanges related information over X2 or S1 with neighbouring node(s) LTE Load Balancing Distribute load across neighbouring cells 11

12 LTE SON Vision: Inter-RAT Load Balancing for Layered Heterogeneous Networks G Macro Ubiquitous 3G deployment LTE Macro Partial LTE deployment (midterm transition stage) LTE Pico + Femto Femto Pico Femto Geographic Layout 1. 3G-only UE: stays on 3G as it moves through network 2. 3G+LTE UE: moves between 3G macro, LTE macro, & LTE macro/pico 3. 3G+LTE UE: able to access 3G & LTE macros, plus LTE HeNB (femto) 12

13 Robustness Optimization Objective: detecting and enabling correction of following problems: - Connection failure due to intra-lte mobility - Unnecessary HO to another RAT HO failure categories - Failures due to too late HO triggering - Failures due to too early HO triggering Requirements: - Detection of too late/early HO or wrong cell HO - Reducing inefficient use of network resources due to unnecessary HOs Identify failed/unnecessary HOs and suggests changes in HO parameters 13 13

14 Coverage and Capacity Optimization Objective: Users ability to establish and maintain connections with acceptable or default service quality Implies: - Coverage is continuous - Users are unaware of cell borders Coverage includes both idle and active modes for both UL and DL Coverage optimization has higher priority than capacity optimization Optimization of parameters through analysis of call trace data Also used for drive test minimization - Requires UEs with GPS and data logging - Privacy concerns not applicable Trade-off between capacity and coverage 14

15 Inter Cell Interference Coordination (ICIC) - Implemented to improve interferencelimitations found in Cellular systems deployed with universal reuse - Inter Cell Interference Coordination - Uplink Soft Fractional Frequency Reuse, Fractional Frequency Reuse - Downlink - Power limitation on frequency blocks - Improvements in later releases - Antenna parameter optimisation e.g. tilt, azimuth Improve user throughput and customer experience 15

16 Energy Consumption Optimisation Drivers towards a Greener network Reduce Carbon Footprint Full enode B switch-off is not possible: idle mode instead Responsiveness Component level (CPU, FPGA) Board level (modem) Cell level (Carrier) Site level (Node B) Reduce Power consumption; additional benefit - Interference Reduction 16

17 Automatic Cell Outage Detection and Compensation Two tasks: Detect Cell Outage In enb with mis-operating cell In surrounding cells of neighbour enbs Compensate for Cell Outage Fault report to OA&M From affected enb From neighbour enbs Reconfig of antenna parameters Azimuth and tilt adjustment via RET Reconfig of neighbour power Coordination between affected enbs Minimize system capacity loss following outage 17

18 Interactions between various SON use cases Capacity Optimization Coverage Optimization LEGEND Coverage impact RACH optimization Cell Outage detection/comp Energy Savings Capacity impact OPEX impact ICIC Load Balancing optimization Self configuration Hand Over optimization Automatic Neighbor Relation Physical Cell ID configuration Terrain 2G/3G/4G Use case Interactions must be modeled and quantified to realize full SON potential 18

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20 Lifecycle Cost Impacts of SON Network Planning Site Acquisition & Preparation Indicates SON impact Physical Installation Commissioning Pre-Launch Activities: Onetime CapEx Integration Pre Launch RF Optimization OA & M Post-Launch Activities: Recurring OpEx Several Pre- and Post-launch Activities Leverage SON Efficiencies 20

21 CapEx Elements Impacted by SON Core Equipment Services not impacted by SON features RAN Deployment Services Services impacted Study Transport Site Construction by SON features focus Network CapEx RAN CapEx Deployment Services CapEx A Relatively Small Portion of Network CapEx is Impacted by SON 21

22 OpEx Elements Impacted by SON CCPU CPGA CPGA Study focus CCPU A Relatively Small Portion of Network OpEx is Impacted by SON 22

23 Mapping of Key SON Features to Business Impacts Note: Time to Market (TTM) and Churn Reduction impacts have been left out 23

24 Computation of Key Cost Elements Note: Only CapEx and OpEx included in this analysis, not Marketing Costs 24

25 Key Modeling Assumptions Effort estimate parameters: Scheduled over a 5 year period implementing > 10,000 sites 2.5 million subscribers at the end of 5 years ~ 90% of current 2G/3G cell sites reused Unit labor cost estimate parameters: Typical wireless operator requires 900 and 1200 employees to manage RAN capacity and service assurance, Average annual loaded salaries of ~ $100,000 Energy cost estimate parameters: - Cell sites in business centers and dense urban areas are often lightly loaded - 10% of sites in these areas could be powered down overnight 25 25

26 CapEx and OpEx Savings Components Relative % reduction of CapEx Activities due to SON 60.0% 50.0% 40.0% 30.0% 20.0% % CapEx Without SON %CapEx With SON 10.0% 0.0% Network Planning Commissioning Integration Pre-launch RF Optimization Relative % reduction of OpEx Activities due to SON 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Pow er OA&M % OpEx Without SON %OpEx With SON 26

27 Concluding Remarks A relatively small part of Network CapEx and OpEx benefit directly from SON; but cost areas where SON is impactful, the benefits can be significant SON benefits for an operator scales linearly with the size of the network; future mini/pico cells may bring benefits of SON in a more significant way Impacts of SON are also reflected in faster deployment and better QoE which translate to Time To Market as well as churn reduction benefits Future SON and xson features may open the doors for unforeseen benefits % % 80.00% 60.00% 40.00% 20.00% 0.00% 39.63% 25.99% 60.37% 47.59% Without SON With SON Capex % Opex % 27

28 A Final Thought: Outage Detection and Self Healing High Traffic Serving Density Cell/Sector Area Load is shared Normal by Traffic Map The Neighboring cells BS I, II & III Serving Cell/Sector Minimize impact of cell outage Has Outage BS II shared load High Traffic Density Area Dynamically minimize service interruption caused by cell outage based on real time traffic loading. Adjust antenna configuration in nearby cells. BS I I β γ α β γ α BS II β γ α β γ α β γ α BS BS III III β γ γ α β γ γ α 28

29 Acknowledgments Craig Connick, Kamakshi Sridhar, Susan Sanders, Louise Gabriel, Ashoke Sharma and many other colleagues at Alcatel-Lucent 29