This was presented by Dr John Naylon, CTO of CBNL, at Mobile World Congress 2012. This made up part of the Energy Efficient Networks session where industry experts discussed the energy efficiency challenges facing operators when deploying their networks. This presentation analyses live customer data that clearly demonstrates the efficiencies intelligent data aggregation technologies can bring to mobile backhaul networks. The data reveals that aggregation can reduce bandwidth requirements by a minimum of 40% whilst delivering an identical service. The presentation also highlights how wireless point to multipoint network architecture dramatically improves spectral efficiency and power efficiency per link. The introduction includes a short video of John highlighting the key points of the presentation and how point to multipoint wireless backhaul can help operators become more efficient, save costs and bring environmental benefits to their backhaul networks.

1. www.cbnl.com
Next generation thinking
Efficient Mobile Backhaul
John Naylon
Mobile World Congress, Barcelona - 29 February 2012

2. The Problem Space: Mobile Backhaul
• Need to connect mobile base stations 100%
(node Bs) to core network
− Could use copper, fibre or microwave radio
− Microwave is the dominant choice 75%
− ~0.5M new microwave backhaul connections
per annum
50%
25%
0%
'08 '09 '10 '11 '12 '13 '14 '15
Microwave Fibre Copper
Worldwide Mobile
Backhaul Connections
Source: Infonetics Research
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3. The Problem Space: Mobile Backhaul Traffic Properties
Sample backhaul demands for 3 tri-cell node Bs in a live, busy HSPA+ network:
Mbps
Can we exploit statistical properties of this data to
make our backhaul more efficient?
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4. First Property: Data is Bursty
• Data is bursty, i.e. has sharp transient peaks and a much lower mean
− This characteristic is driven by user and application behaviour
− Burstiness still present when traffic is aggregated within a node B/eNode B
Mbps
Handset traffic (one iPhone 4)
Peak: 11.44 Mbps
Mean: 0.14 Mbps
Ratio: 79.20 Mbps
Handset traffic (10 Devices)
Peak: 12.07 Mbps
Mean: 1.44 Mbps
Ratio: 8.37 Mbps
Node B backhaul traffic
Peak: 23.31 Mbps
Mean: 5.54 Mbps
Ratio: 4.20 Mbps
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5. First Property: Data is Bursty (2)
• Network-wide average of peak-to-mean ratio is approximately 4:1 in this
HSPA+ example network
− Major implication for efficiency since it is
mandatory to provision backhaul that can
accommodate the offered peak load
− However if we have a dedicated link the
mean utilisation de facto cannot be greater
than the mean offered load
− Therefore the mean utilisation will be
approximately in the ratio of 1:4 to the
peak, i.e. approximately 25%
− So the data’s properties mean that:
Dedicated backhaul
links are 75% idle!
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6. Second Property: Peak Demand is not Synchronised
• Peak bandwidth demand does not occur simultaneously at adjacent node Bs
− Peaks are of short duration (seconds, not
hours like the daily ‘swells’)
− Peaks arise from random, independent
actions of network end users
Mbps
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7. Second Property: Peak Demand is not Synchronised (2)
• Peak bandwidth demand does not occur simultaneously at adjacent node Bs
− Peaks are of short duration (seconds, not
hours like the daily ‘swells’)
− Peaks arise from random, independent
actions of network end users
− In the studied HSPA+ network, average
cross-correlation factor of pairs of node Bs
in geographical proximity is 0.16 indicating
very weak correlation (network-wide
correlation is even lower, at 0.06)
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8. Using These Properties to Improve Backhaul Efficiency
• Non-uniform data rate and absence of correlation lets us share, or
multiplex, resources instead of using dedicated resources (just as we do in the
RAN)
Point-to-Point Point-to-Multipoint
Dedicated radio + Shared radio +
Dedicated RF antenna per link Shared RF channel antenna for all links
channel per link for all links
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9. Savings from Point-to-Multipoint Architecture: Spectrum
• We examine measured backhaul profiles from a group of eight node Bs
− Live network, large middle-eastern operator, heavy data usage
− HSPA+ tri-cellular node Bs
− Theoretical maximum throughput 64.8Mbps per site
• Consider the amount of spectrum needed for each of the two topologies
− Use the bare minimum of spectrum to carry exact data profile (no ‘headroom’)
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10. Savings from Point-to-Multipoint Architecture: Spectrum
Peak: 11.29 Mbps
Mean: 2.47 Mbps
Point-to-Point Microwave Radio, Star Topology Point-to-Multipoint Microwave Radio
Cumulative Peak: 11.3 Mbps Cumulative Peak: 11.3 Mbps
Cumulative Mean: 2.5 Mbps Cumulative Mean: 2.5 Mbps
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11. Savings from Point-to-Multipoint Architecture: Spectrum
Peak: 15.12 Mbps
Mean: 4.18 Mbps
Point-to-Point Microwave Radio, Star Topology Point-to-Multipoint Microwave Radio
Cumulative Peak: 26.4 Mbps Cumulative Peak: 19.5 Mbps
Cumulative Mean: 6.6 Mbps Cumulative Mean: 6.6 Mbps
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12. Savings from Point-to-Multipoint Architecture: Spectrum
Peak: 17.45 Mbps
Mean: 7.61 Mbps
Point-to-Point Microwave Radio, Star Topology Point-to-Multipoint Microwave Radio
Cumulative Peak: 43.9 Mbps Cumulative Peak: 30.9 Mbps
Cumulative Mean: 14.2 Mbps Cumulative Mean: 14.2 Mbps
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13. Savings from Point-to-Multipoint Architecture: Spectrum
Peak: 14.51 Mbps
Mean: 4.64 Mbps
Point-to-Point Microwave Radio, Star Topology Point-to-Multipoint Microwave Radio
Cumulative Peak: 58.4 Mbps Cumulative Peak: 42.9 Mbps
Cumulative Mean: 18.9 Mbps Cumulative Mean: 18.9 Mbps
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14. Savings from Point-to-Multipoint Architecture: Spectrum
Peak: 15.83 Mbps
Mean: 5.69 Mbps
Point-to-Point Microwave Radio, Star Topology Point-to-Multipoint Microwave Radio
Cumulative Peak: 74.2 Mbps Cumulative Peak: 51.7 Mbps
Cumulative Mean: 24.6 Mbps Cumulative Mean: 24.6 Mbps
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15. Savings from Point-to-Multipoint Architecture: Spectrum
Peak: 17.85 Mbps
Mean: 6.67 Mbps
Point-to-Point Microwave Radio, Star Topology Point-to-Multipoint Microwave Radio
Cumulative Peak: 92.0 Mbps Cumulative Peak: 60.2 Mbps
Cumulative Mean: 31.2 Mbps Cumulative Mean: 31.2 Mbps
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16. Savings from Point-to-Multipoint Architecture: Spectrum
Peak: 15.98 Mbps
Mean: 2.93 Mbps
Point-to-Point Microwave Radio, Star Topology Point-to-Multipoint Microwave Radio
Cumulative Peak: 108.0 Mbps Cumulative Peak: 67.8 Mbps
Cumulative Mean: 34.2 Mbps Cumulative Mean: 34.2 Mbps
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17. Savings from Point-to-Multipoint Architecture: Spectrum
Peak: 15.18 Mbps
Mean: 5.49 Mbps
Point-to-Point Microwave Radio, Star Topology Point-to-Multipoint Microwave Radio
Cumulative Peak: 123.2 Mbps Cumulative Peak: 77.9 Mbps
Cumulative Mean: 39.7 Mbps Cumulative Mean: 39.7 Mbps
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18. Savings from Point-to-Multipoint Architecture: Spectrum
Point-to-Point Point-to-Multipoint
Cumulative Peak: 123.2 Mbps Cumulative Mean: 39.7 Mbps Cumulative Peak: 77.9 Mbps Cumulative Mean: 39.7 Mbps
• Spectrum required = 15.4 MHz • Spectrum required = 9.7 MHz
* 256-QAM assumed
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19. Savings from Point-to-Multipoint Architecture: Spectrum
Point-to-Point Point-to-Multipoint
Cumulative Peak: 123.2 Mbps Cumulative Mean: 39.7 Mbps Cumulative Peak: 77.9 Mbps Cumulative Mean: 39.7 Mbps
• Efficiency = 32.2% • Efficiency = 51.0%
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20. Savings from Point-to-Multipoint Architecture: Power
Point-to-Point
37W per radio,
2 radios per link
74W per link
40% power saving per link
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21. Conclusions
• Mobile broadband backhaul traffic • Dedicated backhaul links operate at
has specific properties we can exploit a very low efficiency: ~25% (!!)
to design more efficient backhaul something blah something different
networks something
• Point-to-multipoint architecture • Less equipment deployed means
dramatically improves spectral additional environmental, capex
efficiency and power efficiency and opex benefits
per link
VectaStar from Cambridge Broadband Networks is the market leader in point-to-multipoint
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