The document discusses energy conservation in wireless communication systems using relays. It provides an introduction to the growing energy consumption of wireless networks and the need for more efficient designs. The basics of relaying are described, including what relays are, why they are used, and common relaying protocols. A framework for modeling energy consumption is also presented, including equations for power at transmit and receive, energy per bit, and the impact of fading. Research challenges in optimizing the use of relays are noted.
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Energy conservation in wireless communication systems with relays
1. Energy Conservation in Wireless
Communication Systems with Relays
Aniruddha Chandra
Telecommunications, School of Engineering & Technology,
Asian Institute of Technology, Bangkok, Thailand.
aniruddha.chandra@ieee.org
Science City, 27th December, 2011
Kolkata
2. Outline
Introduction
Energy Conservation
Basics of Relaying
Modelling
Case Study
Summary
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3. Outline
Introduction
- Paradigm shift in wireless system design
- Energy consumption by telecomm industry
Energy Conservation
Basics of Relaying
Modelling
Case Study
Summary
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4. Introduction
Paradigm Shift in Wireless System Design
Meteoric growth in wireless usage:
- Demand for coverage extension.
- Demand for higher capacity.
- Demand for better QoS.
Traditional design:
- New infrastructure deployment, Complement old ones with Relay.
- Femtocell, SDMA, MIMO.
- Adaptive modulation, coding, equalization, diversity.
Increase in energy costs and greater awareness of impact on environment:
- New energy-efficiency oriented design perspective.
- Value power consumption as much as BW, delay, or throughput.
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5. Introduction
Energy Consumption by Telecomm Industry
Some statistics on environmental impact:
- A cellular network (medium sized) ~ Energy for 1,70,000 homes.
- About 3% of the energy consumption, 2% of CO2 emissions.
- The figures are going to double in next 5 years.
- Energy from electricity grid, runs on fossil-fuel.
- Backup diesel generators for unreliable electric supply.
Objects in
Mirror are
Close than
they Appear
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6. Introduction
Energy Consumption by Telecomm Industry
Some statistics on cost incurred for power:
- Powering the BSs accounts for half of the total OpEx.
- Diesel cost has doubled since 2008.
- Even the operators don’t care about environment, they care about ….
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7. Introduction
Energy Consumption by Telecomm Industry
Cost Components:
Energy Components:
- Top three energy consuming components,
feeder network, RF conversion, and climate
control (e.g., air conditioning).
Energy consumption at a typical
macro BS (normalized)
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8. Outline
Introduction
Energy Conservation
- Various means
Basics of Relaying
Modelling
Case Study
Summary
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9. Energy Conservation
Various Means
Power efficient wireless nodes:
- Low power architecture ~ Clock gating, Power saving modes.
- Improved display, Enhanced battery life.
Energy optimized software:
- Improved modem software and OS, application driven power management.
Efficient communication strategies:
- Energy efficient routing.
- Handling idle modes.
- Emerging techniques ~ Multi-antenna, Relay, Cognitive radio etc.
F. Shearer, Power Management in Mobile Devices, Elsevier, 2008.
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10. Outline
Introduction
Energy Conservation
Basics of Relaying
- What is a relay and Why use a relay?
- Modes of operation
- Relaying protocols
Modelling
Case Study
Summary
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11. Basics of Relaying
What is a Relay?
A simple repeater: receive, boost, and re-send a signal.
Cellular Network: different node, carrier owned infrastructure, tree topology.
IEEE 802.16j (mobile multihop relay).
Sensor Network: identical node, subscriber equipment, mesh topology.
IEEE 802.15.5 (WPAN mesh), IEEE 802.11s (WLAN mesh).
Relay #1
Relay Station
(RS) Source Relay #2 Destination
Base Station Mobile Terminal
(BS) (MT)
Cellular Network Sensor Network
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12. Basics of Relaying
Why Use a Relay? RS-MS
link
Network performance improvement Cooperative
BS-RS MT #1
transmission
- Radio range extension link
Coverage/ radio
range extension
- Service for coverage holes RS #1
- Improve QoS RS #2
Traditional direct
- Reduce Tx energy requirement MT #2
transmission
- Capacity enhancement BS
RS #3
- Load balancing between the MT #3
neighbouring cells
Capacity enhancement through
replacing low rate, unreliable links
with multiple high rate, reliable links
Cost benefit Traditional service
boundary
- Use relays to lower CapEx
- Temporary coverage
A. Chandra, C. Bose, and M. K. Bose, “Wireless relays for next generation broadband
networks,” IEEE Potentials, vol. 30, no. 2, pp. 39-43, Mar.-Apr. 2011.
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13. Modes of Operation
Direct Path vs. Relayed Path
1st time slot
× ×
Relay Relay 2nd time slot
Source Destination Source
× Destination
Co-operative Strategies
1st time slot
Relay Relay 2nd time slot
Source Destination Source Destination
K. J. Ray Liu, A. K. Sadek, W. Su, and A. Kwasinski, Cooperative Communications and
Networking, Cambridge University Press, 2009.
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14. Relaying Protocols
Forwarding Strategy
Amplify and Forward (AF)
- Layer #1 relaying: Relays act as analog repeaters.
Decode and Forward (DF)
- Layer #2 relaying: Relays act as digital regenerative repeaters.
Compress and Forward (CF)
- Hybrid solution: Relays quantize and compress (source coding).
Relay Relay Relay
Source Destination Source Destination Source Destination
Amplify and Forward Decode and Forward Compress and Forward
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15. Relaying Protocols
Protocol Nature
Fixed protocol
- Relays always forward a processed version of their received signals.
Adaptive protocol
- Relays autonomously decide whether or not to forward.
Feedback protocol
- Relays provide redundancy only when explicitly requested by destination.
H. Katiyar, A. Rastogi, and R. Agarwal, “Cooperative communication: A review,” IETE
Tech. Review, vol. 28, no. 5, pp. 409-417, Sep.-Oct. 2011.
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16. Outline
Introduction
Energy Conservation
Basics of Relaying
Modelling
- Power consumption at Rx/ Tx
- Energy consumed per bit
- Effect of fading
Case Study
Summary
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17. Modelling
Assumptions
Receiver
- Heterodyne, Hartley & Weaver, Zero IF, Low IF.
Baseband Signal Processing
- Source Coding, Pulse Shaping, Digital Modulation blocks are omitted.
Uncoded System
- No Error Correction Code (ECC) blocks are included.
Multiple Antennas
- Multiple RF processing blocks.
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18. Modelling
Power Consumption at Receiver
Block Diagram
Band Image Channel
Antenna selection rejection selection ADC
filter LNA filter Mixer filter IFA
LO
Components
PRx = PLNA + Pmix + PIFA + PADC + Pfil + Psyn
P. -I. Mak, S. -P. U, and R. P. Martins, Analog-baseband Architectures and Circuits for
Multistandard and Low-voltage Wireless Transceivers, Springer, 2007.
B. Leung, VLSI for Wireless Communications, 2nd ed., Springer, 2011.
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19. Modelling
Power Consumption at Transmitter
Block Diagram
Channel Image
DAC selection rejection Antenna
filter Mixer filter PA
LO
Components
ξ
PTx = PDAC + Pmix + Pfil + Psyn PPA = PT
η
PTx ,total = PPA + PTx PT → RF transmit power.
ξ → Peak-to-average ratio.
η → Drain efficiency.
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20. Modelling
RF Transmit Power
Friis Free Space Formula
2
PR λ PR → Received power.
= GT GR
PT 4πd d → Distance between Tx and Rx.
2 λ → Signal wavelength.
4π d
2
⇒ PT = PR G → Combined antenna gain.
λ G where G = GT GR.
For Terrestrial Transmission
2
4π d
n
PT = PR n → Path loss exponent (2 ≤ n ≤ 4).
λ G
Considering Link Margin and Noise Figure
2
4π d
n
ML → Link margin.
PT = PR M L NF
λ G NF → Noise figure.
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21. Modelling
Energy Consumed per Bit
Total Circuit Power Consumption
PC = PTx ,total + PRx
= PPA + PTx + PRx
ξ
= PT + PTx + PRx
η
2
ξ 4π d n
= PR
η M L N F + ( PTx + PRx )
λ G
2
ξ 4π d
n
= Eb Rb
η M L N F + ( PTx + PRx )
λ G
where, Eb → Received energy per bit, Rb → Bit rate, and PR = Eb Rb.
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22. Modelling
Energy Consumed per Bit
Consumption per Bit
PC
E=
Rb
2
ξ 4π d n P + PRx
= Eb
η M L N F + Tx
λ G Rb
Bit Rate (Rb)
- When no pulse shaping is used, Rb = 2B, where B = System BW.
Received Energy per Bit (Eb)
- This parameter determine the BER floor and QoS.
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23. Modelling
Ensuring a Fixed BER
Consider the Modulation Scheme
- For BPSK modulation, the BER is
1 Eb
Pe = erfc
N
2 0
Consider the Target BER
- Target BER is application specific, e.g. for voice applications, Pe ≤ 10-3.
Calculate Required Eb
1 Eb
erfc
N
≤ 10 −3
2 0
[
⇒ Eb ≥ N 0 erfc 2 ×10
-1
( −3
)] 2
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24. Modelling
Effect of Fading
Statistics of Received SNR
- For Rayleigh fading
1 γ
f ( γ ) = exp −
γ
γ
Outage Probability
- For a target SNR (γo),
O = Pr[ γ < γ 0 ]
γ0
= ∫ f ( γ ) dγ
0
γ0
= 1 − exp −
γ
- Target SNR is determined by the required data rate.
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25. Modelling
Target SNR Calculation
Ergodic Capacity: Shannon’s Formula
- For reliable communication
Rb ≤ B log 2 (1 + γ o )
⇒ γ o ≥ 2 Rb B
−1
Outage Probability
γ0
O = 1 − exp −
γ
2 Rb B − 1
= 1 − exp −
γ
3
−
= 1 − exp
Eb N 0
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26. Modelling
Energy Consumed per Successful Bit
Effective Data Rate
Rb ,eff = Rb (1 − O )
Energy Consumption per Bit
PC
Esuc =
Rb ,eff
PC
=
Rb (1 − O )
E
=
1− O
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27. Modelling
One More Equation …
… and you’ll lose rest of your audience!
A. Chandra - Energy Conservation with Relays 27/41
28. Modelling
Research Challenges
Relay: To Use or Not to Use
- Always cooperate, or use relay only when the direct link fails?
Relay Placement
- If relay node is not collinear, is there any boundary region to place it?
Relay Selection
- If there are many relay nodes, how many and which ones to select?
Other Issues
- Multiple antennas at relay, distributed STC etc.
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29. Outline
Introduction
Energy Conservation
Basics of Relaying
Modelling
Case Study
- Relay placement: Collinear model
- Relay placement: Non-linear model
Summary
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30. Modelling for Relay
Statistics of S-R-D Link
Outage Probability
γ0
OS − R − D = OS − R + (1 − OS − R ) OR − D OS − R = OR − D = 1 − exp −
γ
Energy Consumption per Bit in S-R Link
2
PC , S − R ξ 4π d S − R
n
P + PRx
ES − R = = Eb
η M L N F + Tx
Rb λ G Rb
Energy Consumption per Bit in R-D Link
2
PC , R − D ξ 4π d R − D
n
PTx + PRx
ER − D = = Eb
η M L NF +
Rb λ G Rb
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31. Modelling for Relay
Statistics of S-R-D Link
Energy Consumption per Bit in S-R-D Link
- Outage in S-R path, ES − R − D = ES − R , probability OS − R .
- No outage in S-R path, ES − R − D = ES − R + E R − D , probability 1 − OS − R .
- Average energy consumption
ES − R − D = OS − R ES − R + (1 − OS − R )( ES − R + E R − D )
Effective Data Rate
Rb ,eff = Rb (1 − OS − R − D )
Energy Consumption per Successful Bit
ES − R − D
Esuc =
1 − OS − R − D
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32. Relay Placement
Collinear Model
Direct Path vs. Relayed Path
Relayed
Path
Direct Path
(Reference level)
42.2 m (Optimum location)
Source Relay Destination
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33. Relay Placement
Non-linear Model
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34. Relay Placement
Non-linear Model
?
Source Relay Destination
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35. Relay Placement
Non-linear Model
Relay
Source Destination
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36. Outline
Introduction
Energy Conservation
Basics of Relaying
Modelling
Case Study
Summary
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37. Summary
Energy efficient perspective for wireless systems.
Various means to reduce energy consumption.
Use of wireless relays is one of them.
A single collinear relay may save upto 35% energy.
For non-linear setup, an energy efficient region may
be found to place the relay.
Many open problems, we need you!
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38. Read More About It
Green Communication
• G. Y. Li et al., “Energy efficient wireless communications: Tutorial, survey,
and open issues,” to appear in IEEE Wireless Commun. Magz.
Modelling Energy Consumption
• S. Cui, A. Goldsmith, and A. Bahai, “Energy-efficiency of MIMO and
cooperative MIMO techniques in sensor networks,” IEEE J. Sel. Areas
Commun., vol. 22, no. 6, pp. 1089-1098, Aug. 2004.
• G. G. de Oliveira Brante, M. T. Kakitani, and R. D. Souza, “On the energy
efficiency of some cooperative and non-cooperative transmission schemes
in WSNs,” Proc. IEEE CISS, Baltimore, MD, Mar. 2011, pp. 1-6.
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39. Thank You All
Presenting talks in conferences ensure …
Hua Hin
Bangkok
Science City
… travelling around the Globe!
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40. Acknowledgements
This talk won’t be possible without …
The support of Conference Organizers
Encouragements
Prof. Richard D. Souza Prof. Joyanta Kr. Roy Dr. P. Venkateswaran
UTFPR - Parana, Principal, NIT Assoc. Prof., ETCE Deptt.,
Curitiba, Brazil. & Program Chair, ICCIA. & Secretary, IEEE ComSoc.
Permissions
My research group Mr. Biswajit Ghosh Mr. Anirban Ghosh
Lecturer, IT, Master’s student,
FIEM, Kolkata NIT Durgapur.
& Ph.D. student.
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41. Thank You!
Questions?
aniruddha.chandra@ieee.org
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