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Automated HetNet Design

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Presented by Iris Barcia, COO, Keima at CW TEC 2018 - The inevitable automation of Next Generation Networks - 27 Sep, 2018

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Automated HetNet Design

  1. 1. Automated HetNet Design CW TEC 2018 Iris Barcia COO
  2. 2. We use intelligence to design the optimal network • Provider Perspective • Maximize ROI (optimal location) • Service / User Perspective • Context • Requirements and expectations 5G - Public Safety Design Portland
  3. 3. ROI: Multiple Independent Variables Technology Framework Locations Regulation Time G Efficiency Access Power Backhaul Spectrum Strategy
  4. 4. HetNet AutoDesign Workflow – Complexity
  5. 5. 2012: Challenges – Coverage Planning to Capacity Design • Link Adaption • Non-uniform Demand • Network Densification • Interference Continuum
  6. 6. 2018: Design Challenges – Capacity Planning • Link Adaption • Non-uniform Demand • Network Densification • Interference Continuum • mMIMO • 5G Numerology • Slicing, Edge Computing • New frequencies • Densification (more)
  7. 7. Training and modelling
  8. 8. Digitization of the Environment – Classification Multiple data sources – geographical differences Quantization Error < R/100 2012 – Environment Model, Lower Manhattan (Vector Clutter) 2018 – Environment Model, Lower Manhattan (DHM Clutter)
  9. 9. Manhattan
  10. 10. Manhattan
  11. 11. Manhattan
  12. 12. Manhattan
  13. 13. Boston
  14. 14. Boston
  15. 15. Boston
  16. 16. Boston
  17. 17. Dallas
  18. 18. Dallas
  19. 19. Dallas
  20. 20. Dallas
  21. 21. Dallas
  22. 22. Dallas
  23. 23. Learning propagation models • The model understands the environment and Autotunes its properties
  24. 24. Network Measurements
  25. 25. Network Measurements
  26. 26. Classification
  27. 27. Geocorrection
  28. 28. Signal Propagation
  29. 29. Network Measurements
  30. 30. Classification
  31. 31. Signal Propagation
  32. 32. AutoCorrect Azimuth Error - Detection and Correction
  33. 33. Understanding user behaviour - Demand • Network Agnostic Crowdsourced Information • Continuous update • Statistical Relevance • Seamless Integration • Context-aware sources • Crime • Rescue Centres • Events • Network Data Calibration Composite Demand heatmap - user clustering and density
  34. 34. Social Networks London
  35. 35. Social Networks London
  36. 36. Social Networks London
  37. 37. Social Networks London
  38. 38. Social Networks London
  39. 39. Manhattan
  40. 40. Manhattan
  41. 41. Manhattan
  42. 42. Manhattan
  43. 43. Dallas
  44. 44. Dallas
  45. 45. Dallas
  46. 46. Dallas
  47. 47. Design AutoDesign AutoConnect AutoX-Workflows
  48. 48. Slide presented by Andy Sutton
  49. 49. 32553 sites 41949 radios 39 macro – Core Hubs 13 km x 13 km 1 Day ~ 90K households Fixed Connection Type Connected Housholds Hub Edge 441 Tier 1 14133 Tier 2 8919 Tier 3 4481 Tier 4 2604 Tier 5 1803
  50. 50. AutoConnect – 5G Fixed Wireless • 5G Integrated Access and Backhauling • Fully deterministic* Increased latency -120 -100 -80 -60 -40 -20 0 540 550 560 570 580 590 600 610 620 Edge Hub Tier 1 Tier 2 Tier 3 Tier 4 Tier 5 RSSI(dBm) Bitrate(Mbps) FAIRFAX COUNTY - 5G FIXED WIRELESS Average of Uplink RSSI (dBm) Average of Downlink RSSI (dBm) Average of Uplink Bitrate (Mbps) Average of Downlink Bitrate (Mbps)
  51. 51. Edge Computing Hubs
  52. 52. Inter-Hub Connections
  53. 53. Tier 1
  54. 54. Tier 2
  55. 55. Tier 3
  56. 56. Tier 4
  57. 57. Tier 5
  58. 58. Core Hubs
  59. 59. Inter-Hub Connections
  60. 60. Tier 1
  61. 61. Tier 2 + Wired
  62. 62. Tier 3 + Wired
  63. 63. Tier 4 + Wired
  64. 64. Tier 5 + Wired
  65. 65. Future • Drones • Context – aware, self-deploying solutions • Ad-hoc structures Madrid
  66. 66. Thank you To design modern mobile networks we need precision To get the best of the network we need a holistic analysis To maximise ROI we need intelligence Gelli, Wales Keima www.keima.com info@keima.com

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