1. Chapter 17: Green Broadband Access Networks Tao Han, Jingjing Zhang, and Nirwan Ansari Advanced Networking Laboratory, New Jersey Institute of Technology, Newark, NJ, United States HANDBOOK ON GREEN INFORMATION AND COMMUNICATION SYSTEMS

2. 2 Green Broadband Wireless Access Networks  Techniques on greening cellular networks  Power saving communication protocols  Heterogeneous network deployment  Enabling off-grid BSs  Greening via cooperative networking  Cooperation among BSs  Cooperation between BSs and UEs

3. 3 Power saving communication protocols  Idea: Adjusting the transmit power of the transceivers according to the traffic intensity  Traffic volumes variation  Typical day-night behavior of users  Mobility of users Users tend to range over their office districts during working hours and stay home in their residential area after work. This results in the surge of traffic in both areas at peak usage hours, but in the drop of traffic during the off-peak hours.  Solutions Switching off the transceivers when the traffic load is below a certain threshold for a certain time period. When some base transceiver stations are switched off, radio coverage and service provisioningare taken care of by the remaining active devices.

4. 4 Heterogeneous Network Deployment  Disadvantages of Homogeneous Network Deployment  Optimization of the location of BSs is complicated  Limited ability to adapt to the traffic load.  Heterogeneous Network Deployment  Utilizing a diverse set of base stations can be deployed to improve spectral and energy efficiency per unit area.

5. 5 Enabling Off-Grid BSs (1)  Designing off-grid BSs and communication protocols to enable optimal utilization of renewable energy in cellular access networks  Off-grid BSs

6. 6 Enabling Off-Grid BSs (2)  Designing communication protocols to maximize the utilization of green energy  Energy Source Aware Target Cell Selection (Ref. [31]) The proposed algorithm is to ease the mobile users to handover into the green cell and also to make the UE more difficult to leave the green cell. As a result, the coverage of the green cell is actually enlarged, therefore reducing the on-grid power consumption.

7. 7 Greening via Cooperative Networking: Cooperation among BSs  Green opportunities  Cooperation umbrella cell and the underlying cells in multi-layer cellular network architecture  Cooperation among BSs in flat cellular network architecture  Cooperation among BSs from different mobile service providers

8. 8 Greening via Cooperative Networking: Cooperation among BSs  Green challenges  When to cooperate: determine the traffic threshold for cooperation If the threshold is too high, the coalition will break down in a short time period. In other words, some BSs that were turned into the sleep mode in the cooperation will restart soon. In this case, the energy consumed by restarting the BSs may be much higher than that of noncooperation. If the threshold is too low, the BSs may miss some cooperative opportunities.  Who to cooperate: determine the coalition among BSs Determine the size of the coalition Determine the members of the coalition

9. 9 Greening via Cooperative Networking: Cooperation between BSs and UEs  Green opportunities  Unified cellular and ad-hoc network architecture (ref. [33])  Cooperation with beamforming Transmit beamforming provides incentives to the relay users to stimulate the cooperation One hop relay to attain largest performance improvement while consuming minimal relay energy

10. 10 Greening via Cooperative Networking: Cooperation between BSs and UEs  Cooperation network protocols 1.Channel measurement and data request 2.Transmission strategy calculation 3.Relay selection and cooperation negotiation 4.Relay assignment and relay negotiations 5.Relay assignment acknowledgement 6.Data transmission

11. 11 Greening via Cooperative Networking: Cooperation between BSs and UEs  Green challenges  Channel state information New protocols to enable the measurements and updates of the channel state information among UEs How to efficiently feedback the channel state information to BSs  Incentive mechanism Design incentive mechanism to avoid tragedy of common  Hybrid handover scheme Design an efficient handoff scheme to address the handovers from BSs to BSs, from BSs to relay UEs, from relay UEs to relay UEs, and from relay UEs to BSs.

12. 12 Greening via Cooperative Networking: Cooperation between BSs and UEs  Case study: energy efficient wireless multicasting (ref. [34])  The energy efficient wireless multicasting integrates multicast beamforming and cooperative networking. It contains two phases: in phase 1, the base station (BS) transmits the signal to the subscribers using antenna arrays with multicast beamforming; in Phase 2, the users who successfully received the signal in phase 1 forward the signal to other users. The unsatisfied users combine the received signals in both phases to retrieve the infor -mation.

13. 13 Greening via Cooperative Networking: Cooperation between BSs and UEs  Case study: simulation results (1) The simulation compares the minimal transmit power of different multicasting strategies. With transmit beamforming, BS saves more than 3dBm transmit power. Lozano's algorithm is a multicast beamforming algorithm that does not consider cooperation. As the number of users increases, the performance of the proposed algorithm becomes better because there are more cooperative opportunities. When the number of users is larger than 40, the performance becomes steady, in which it uses about 3.5dBm, 2dBm, and 1dBm less transmit power than those of Lozano's algorithm, respectively. It becomes steady because when the number of users is large enough (40 in the simulation), the cooperation gain is not limited by the cooperative opportunities, and becomes steady.

14. 14 Greening via Cooperative Networking: Cooperation between BSs and UEs  Case study: simulation results (2) This simulation compare the BS power consumptions under different multicasting strategies.. The blue line indicates the power consumption of the standard LTE Macro BS, which can be considered as the power constraint of BS. Note that simply broadcasting without beamforming and cooperation cannot satisfy the users' requirement under the constraint. As compared to the Lozano's multicast beamforming algorithm, our proposed algorithm can save at least 100 Watts when the number of users is larger than 60. The power savings are benefited from the cooperation between BS and users.

15. 15 Green Broadband Wireline Access Networks  Why saving energy consumption of optical access network is important?  Where and how much is the power consumed in Passive Optical Network?  Where is the power wasted?  Optical network unit (ONU) and optical line terminal (OLT)  How to save? - proposals  Vision and challenges  Proposals

16. 16 Motivation Fiber-To-The-x (FTTX) users are increasing year by year By 2011, there are over 80 million FTTx users  Global broadband subscriber forecast  Power consumption of FTTx networks Power consumption: On average, each FTTx user consumes ~15w (>30w) In 2011, the total FTTx energy consumption is ~11 TWhr, equal to 7M tons of CO2, 3 extra 500MW power stations Goals: Save FTTx energy consumption!

17. 17 Background: Passive Optical Network residential Business Central office Optical line terminal (OLT) …… Distribution 1 OLT chassis contains 8 OLT line cards; consumes ~100w 1 OLT line card connects with 32 ONUs OLTs consume <40% of FTTx energy (NTT) 1 ONU consumes ~10w ONUs consumes >60% FTTx energy … … … Optical network unit (ONU)  Passive optical network (PON): the major FTTx technology Question: How to save energy at OLT and ONUs?

18. 18 Upstream and downstream scenarios  Upstream scenario  Pros: the upstream traffic arrival triggers the wakeup of asleep ONUs  Challenges: physical layer implementation, fast wakeup and fast sleep  Downstream scenario  Owing to the broadcast nature, an ONU needs to be awake all the time to check the header of each packet! ONU user ONU upstream ONU2 ONU1 ONU3 223 2 2 3 223 2 2 3 OLT splitter ONU2 ONU1 ONU3 Control scheme is needed to put an ONU into sleep when it doesn’t have downstream packets! 1.When the upstream buffer is empty for some time, ONU enters into sleep 2. Upon the upstream traffic arrival, ONU wakes up

19. 19 How to put an ONU into sleep in the downstream scenario?  Existing proposal: two-way or three-way handshake  When the downstream queue of an ONU is empty for some time, OLT sends a message informing ONU to sleep  ONU sends an ACK to confirm the sleep  It addresses the problem, but  At least one round trip time needs to be taken for negotiation  EPON MPCP protocol needs to be extended to support the mechanism ONUOLT Sleep notification Sleep ack Ref: J. Mandin,10G-EPON task force meeting 2008, R. Kubo et al., Globecom’09, JOCN’10 S. Wong, et al. Greencom’09, OFC’10

20. 20 Our proposal – main idea  Main idea: let ONU infer its downstream queue status instead of being explicitly notified by OLT  Assume OLT schedule downstream traffic of ONUs with nonempty queues in order (e.g., 1, …, N)  If no traffic is destined to an ONU for some time, the ONU can infer that it doesn’t have downstream traffic, and then go to sleep Onu 1 OLTONU 1 onu2onu3onu4onuN … onu2 onu3onu4onuN … onu2 onu3onu4onuN … ONU 1 guess it doesn’t have traffic ONU 1 is more sure it doesn’t have traffic

21. 21 Our proposal  Implement a sleep control algorithm at ONU  How can an ONU avoid missing downstream packet when it is sleeping?  Solution: Implement a sleep control algorithm at OLT  Pros: easy implementable, compatible with current protocol OLTONU Sleep control algorithm: If I haven’t sent traffic to ONU i for time t_silent, then, I will buffer its traffic which arrives in the next t_sleep time OLTONU Sleep control algorithm: If no traffic is sent to me for time t_silent, then, I will go to sleep for time t_sleep

22. 22 Energy-Efficient OLT Peak hour Off-Peak hour Typical daily traffic profile Source: Amsterdam Internet Exchange Off-peak hour traffic rate is much less than peak hour traffic  Current status  One OLT chassis contains multiple line cards  All OLT line cards are power-on all the time  OLT traffic profile  Why not aggregate traffic of multiple line cards and power off some line cards in off-peak hour?

23. 23 OLT Energy-efficient OLT  How to aggregate traffic of multiple PONs at OLT?  Assume one OLT chassis contains 4 line cards OLT line card 4×4 optical switch OLT chassis Green OLT chassis ONUs

24. 24 Energy-efficient OLT  Assume the switching speed is fast (<1 DBA cycle),  i.e., the switch configuration can be rather dynamic OLT line card Case 1: Load>75%Case 2: Load [50%, 75%] Case 3: Load<[25%,50%] OLT line card Case 4: Load<25%

25. 25 Energy-efficient OLT  Assume the switch speed is slow,  i.e., the switch configuration is semi-static  Further assume the traffic is uniform among all PONs OLT line card Case 1: Load>50%Case 2: Load [25% 50%] Case 3: Load<25%

26. 26 Simulation results

27. Conclusions  Green broadband wireless networks  Techniques on greening cellular networks Power saving communication protocols Heterogeneous network deployment Enabling off-grid BSs  Greening via cooperative networking Cooperation among BSs Cooperation between BSs and Ues Case study: energy efficient wireless multicasting  Green broadband wireline networks  Energy consumption measurement in Passive Optical Networks Energy waste in ONU Energy wast in OLT  Energy efficient Passive Optical Networks Energy efficient ONU Energy efficient OLT

28. 28 Thanks for your attention!