Dynamic Femto Cell Deployment for Power Efficiency

1. Dynamic Femto Cell Deployment for Power Efficiency Future Network & Mobile Summit 2012 4th -6th July, 2012 Berlin, Germany

2. Overview of the Experimental System • The experimental scenario “Dynamic Femto Cell Deployment” is developed to validate and showcase the cooperative energy aware solutionsand self-growing mechanisms in cellular radio networks. • The power saving schemes and self-growing mechanisms are realized in the platform in means of autonomic and dynamical adding or removing Femto base stations in the network according to the current capacity and coverage demand.

3. Validation Use Cases Use case : Dense home/office environment • The experimental platform reproduces a dense home/office environment, in which • several Femto stations (AP) are set up within a close geographical area. • a certain number of wireless devices are distributed in the area and access the cellular network via Femto-cells. The number and the position of active devices may possibly vary during the demonstration and validation processes. • There are also other short-range access points and devices such as WLAN operate within the same geographical area. These devices provide wireless connections parallel to the Femto stations. They can but not necessarily cooperate with the Femto stations.

4. Experimental System Setup • Enhanced Pico-station ePico3801 for UMTS indoor coverage solutions • UMTS/GPRS terminals • Huawei S7 Android Tablet • HuaweiU8800,HSDPA/UMTS/GPRS/GSM Handset • Intel Mobile XMM6160 handset platforms

5. Structure ofFemto Network remote AP manager • The Femto Base stations (Femto APs) are connected to the remote AP manager and corn network via VPN. HSPA 3G smart fone S7 Tablet local control computer Huawei Femto station IFX handset plateform MiFI HSPA Internet Huawei Femto station HSPA

6. CONSERN enabled Femto/Pico cells • The CONSERN enabled Femto/Pico network consists of several Femto/Pico base stations and control computers in which CCE functionalities are implemented.

7. CONSERN architecture Mobile Devices Backbone Flow Knowledge Base Ontology Knowledge Base Ontology Communication services (incl. Translation) Communication services (incl. Translation) Learning Learning Monitoring Monitoring Data Flow Femto network, CONSERN enabled Signalling Flow Network Infrastructure Decision Making Femto BS Femto BS Knowledge Base Ontology Communication services (incl. Translation) Cooperation Learning Monitoring Execution .... AutonomicControl Self-Growing Administrative Control

8. Demonstration of Dynamic Switch On/Off Femto/Pico cells • It demonstrate the energy-efficiency and self-growing capability of a cellular (Femto) network in home and office environment. • Based on the power consumption and traffic load in the current network the CCE determines the optimal base station constellation applying diverse algorithms. • The self-growing concept is demonstrated when CCE gradually changes the policy between throughput optimized and energy optimized according to different service purposes. high traffic scence Low traffic scence

9. Algorithms for Optimal Base Station Constellation • Diverse running-time algorithms are developed to calculate the base station constellation optimized for particular scenarios. • Three of them are adapted to the experimental system • Time Triggered Power Saving Algorithm • Stability-based Preferential Selection Algorithm • Centralized Cooperative Power On-Off Algorithm

10. Time Triggered Power Saving Algorithm • In high-traffic hours all Femto base stations are turned on. • In low-traffic hours, e.g. non-business hours, Femto base stations are turned into sleep mode if currently no terminals are attached to the base station.

11. Stability-based Preferential Selection Algorithm • In a dense small cell environment, a UE has usually multiple choices to set up a link with one of its neighbouring base stations • The set of active base stations can be minimized by artful selection of the Terminal-to-Base-Station links. • Other base stations that have no links to UEs at the moment can be shut down or turn to power saving mode. • In order to avoid incessant ON/OFF switches due to the mobility of terminals, the stability of the network is taken into account. Constellation 1: Selection according to best channel state, 2 base stations are active Constellation 2: Selection minimizes the set of active base stations, 1 base stations is active

12. Centralized Cooperative Power On-Off Algorithm • The algorithm aims to optimize an utility function regarding both throughput and power consumption: • The tradeoff between throughput maximization and power minimization can be adjusted by changing the weight factors. s.t. T5%current : outage throughput of the current configuration T5%baseline: outage throughput of the baseline configuration α: weight factor that corresponds to the significance of the utility of the terms , I: is the set of all users and is the ith user, RSRPi,current: reference signal received power by the ith user, : threshold value of the received signal strength which is set to -120dBm in our simulations EERGEnergy Reduction Gain

13. Demonstration of Dynamic Femto Cell Deployment • The status of the Femto base station is observed by a control/monitor interface. Power On/Off Tx Power, UE status

14. Demonstration of Dynamic Femto Cell Deployment Running-time monitoring of power and throughput variation

15. Demonstration of Dynamic Femto Cell Deployment Cell reselection observed on the Terminal Reselection of serving cell

16. Performance comparison of three algorithms • Time Triggered Power Saving Algorithm • Stability-based Preferential Selection Algorithm • Centralized Cooperative Power On-Off Algorithm

17. Thank You