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Chapter 17: Green Broadband Access Networks

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Title: Chapter 17: Green Broadband Access Networks


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

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
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
    provisioning are taken care of by the remaining
    active devices.

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
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
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
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
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
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
Greening via Cooperative Networking Cooperation
between BSs and UEs
  • Cooperation network protocols
  • Channel measurement and data request
  • Transmission strategy calculation
  • Relay selection and cooperation negotiation
  • Relay assignment and relay negotiations
  • Relay assignment acknowledgement
  • Data transmission

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
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
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
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
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
Motivation
  • Power consumption of FTTx networks
  • Power consumption
  • On average, each FTTx user consumes 15w (gt30w)
  • 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
Background Passive Optical Network
  • Passive optical network (PON) the major FTTx
    technology
  • 1 OLT chassis
  • contains 8 OLT line cards
  • consumes 100w
  • 1 OLT line card connects with 32 ONUs
  • OLTs consume lt40 of FTTx energy (NTT)
  • 1 ONU consumes 10w
  • ONUs consumes gt60 FTTx energy

Question How to save energy at OLT and ONUs?
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!

upstream
  • When the upstream buffer is empty for some time,
  • ONU enters into sleep
  • 2. Upon the upstream traffic arrival, ONU wakes up

ONU
ONU
user
Control scheme is needed to put an ONU into sleep
when it doesnt have downstream packets!
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

ONU
OLT
Ref J. Mandin,10G-EPON task force meeting 2008,
R. Kubo et al., Globecom09, JOCN10 S. Wong, et
al. Greencom09, OFC10
Sleep notification
Sleep ack
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 doesnt have
    downstream traffic, and then go to sleep

Onu 1
onu2
onu2
OLT
ONU 1
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

Sleep control algorithm If no traffic is sent to
me for time t_silent, then, I will go to sleep
for time t_sleep
OLT
ONU
Sleep control algorithm If I havent sent
traffic to ONU i for time t_silent, then, I will
buffer its traffic which arrives in the next
t_sleep time
OLT
ONU
22
Energy-Efficient OLT
  • 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?

Typical daily traffic profile
Off-peak hour traffic rate is much less than peak
hour traffic
Peak hour
Off-Peak hour
Source Amsterdam Internet Exchange
23
Energy-efficient OLT
  • How to aggregate traffic of multiple PONs at OLT?
  • Assume one OLT chassis contains 4 line cards

OLT chassis
Green OLT chassis
ONUs
OLT line card
ONUs
OLT line card
44 optical switch
ONUs
OLT line card
ONUs
OLT line card
ONUs
OLT line card
ONUs
OLT line card
ONUs
OLT line card
ONUs
OLT line card
24
Energy-efficient OLT
  • Assume the switching speed is fast (lt1 DBA
    cycle),
  • i.e., the switch configuration can be rather
    dynamic

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

Case 3 Loadlt25
Case 1 Loadgt50
Case 2 Load 25 50
OLT line card
OLT line card
OLT line card
OLT line card
OLT line card
OLT line card
OLT line card
OLT line card
OLT line card
OLT line card
OLT line card
OLT line card
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
Thanks for your attention!
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