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BLI Research on Small Cells Imran Ashraf April 2010 Davide CherubiniBell Labs Ireland Networks & Networking Group
Spectrally Efficient Cellular Networks ,[object Object],Femtocell overlay on the GSM macrocell network Localized coverage through femtocells – high data rates ,[object Object],Femtocells perform sensing for unused GSM spectrum by macrocells The vacant spectrum is opportunistically used by femtocells with tight interference constraints on the macrocell network Capacity increase for femtocells with minor impact on the macrocell network 2| July 2010  Mbps
Green Cellular Networks Total Consumption = 12 W Total Consumption = 7.3 W Power Amplifier(2 Watts) Power Amplifier(0 Watt) Power Source (85 % efficiency) Power Source (85 % efficiency) Microprocessor (RF On)(3.7 Watts) Microprocessor (RF Off)(2.7 Watts) FPGA/Other Circuitry(4.5 Watts) FPGA/Other Circuitry(3.5 Watts) SLEEP Mode ACTIVE Mode ,[object Object]
Network energy consumption increases in dependency of the scale of small cell  deployment
Energy-Efficient algorithms for small cellsCoverage-aware Switch-offs Detect existing spatial coverage and switch-off base stations Traffic-aware Sleep modes Detect UE activity via carrier sniffing and temporarily switch-off idle small cells Energy consumption follows the traffic 3| July 2010
Network Power Savings using Sleep Modes Network energy consumptionfor operator with 40% market share (Future improved Technologies) Network energy consumption for operator with 40% market share (Today) Higher macrocell efficiency 97% of energy costs paid by end user Higher picocell efficiency Picocell contribution increases linearly Picocell contribution does not increase linearly anymore 100% of energy costs paid by operator 75% reduction in network power consumption 4| July 2010
Future - Autonomous Networks UE UE UE Network Network Network Now Future Past Ongoing research is in here Objective Objective Model Objective Model Objective Model Automated Program Generation (offline) Algorithm Algorithm Network Planners Design stage measurements measurements measurements Model Automated Program Generation (online) Algorithm measurements drive testing BS BS BS BS The algorithm generation process is now distributed and performed locally and continuously by the network nodes themselves. Nodes now have ability to autonomously specialise their individual behaviour according to environment. Algorithms are generated using automated means, (Genetic Programming). Design process is done offline, and resulting algorithm is implemented in the network.  Algorithms for auto-configuration and self-optimisation are developed manually, and used to automate the network configuration and optimisation. Planning and optimisation is performed manually through network planning engineers and drive testing. 5| July 2010
Wilson Street Project Scope Development of a series of small cell demos http://www.wilson-street.com @Bell Labs Ireland First permanent small cells platform for research ,[object Object]

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Bell Labs Ireland research on small cells [Davide Cherubini]

  • 1. BLI Research on Small Cells Imran Ashraf April 2010 Davide CherubiniBell Labs Ireland Networks & Networking Group
  • 2.
  • 3.
  • 4. Network energy consumption increases in dependency of the scale of small cell deployment
  • 5. Energy-Efficient algorithms for small cellsCoverage-aware Switch-offs Detect existing spatial coverage and switch-off base stations Traffic-aware Sleep modes Detect UE activity via carrier sniffing and temporarily switch-off idle small cells Energy consumption follows the traffic 3| July 2010
  • 6. Network Power Savings using Sleep Modes Network energy consumptionfor operator with 40% market share (Future improved Technologies) Network energy consumption for operator with 40% market share (Today) Higher macrocell efficiency 97% of energy costs paid by end user Higher picocell efficiency Picocell contribution increases linearly Picocell contribution does not increase linearly anymore 100% of energy costs paid by operator 75% reduction in network power consumption 4| July 2010
  • 7. Future - Autonomous Networks UE UE UE Network Network Network Now Future Past Ongoing research is in here Objective Objective Model Objective Model Objective Model Automated Program Generation (offline) Algorithm Algorithm Network Planners Design stage measurements measurements measurements Model Automated Program Generation (online) Algorithm measurements drive testing BS BS BS BS The algorithm generation process is now distributed and performed locally and continuously by the network nodes themselves. Nodes now have ability to autonomously specialise their individual behaviour according to environment. Algorithms are generated using automated means, (Genetic Programming). Design process is done offline, and resulting algorithm is implemented in the network. Algorithms for auto-configuration and self-optimisation are developed manually, and used to automate the network configuration and optimisation. Planning and optimisation is performed manually through network planning engineers and drive testing. 5| July 2010
  • 8.
  • 9. indoor open service cells
  • 11. looking at the future!6| July 2010
  • 12. WirelessLab SIG Events Join WirelessLab’s Energy-Efficient Wireless Access NetworksSpecial Interest Group! For further information: www.wirelesslab.ie Interested in further discussions onenergy-efficient wireless communications? 7| July 2010