Mary Ann Ingram
School of Electrical and Computer Engineering
Georgia Institute of Technology
TR-50 Meeting
April 12, 2010

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Objective
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Cooperative Transmission

Energy Harvesting and Storage

RFID and Sensors

Wake-up Radios
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Conclusions
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How Georgia Tech can help

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Consider some emerging technologies that would impact the standard, because they impact the
Data Link Layer (DLL)

Identify some DLL issues for each technology

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Definition and SNR advantage
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Transmit time synchronization

Range extension
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Application to the energy hole in wireless sensor networks
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Application to broadcasts in dense networks

DLL issues

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A protocol where multiple, neighboring radio platforms cooperate in the physical layer to send a single message
I’ll help you if you will help me!
OK!
That way, if your channel is faded, maybe mine will be better!
Working together, our signals can go farther and we may save energy!
J. Laneman, D. Tse, and G. Wornell, “Cooperative diversity in wireless networks: Efficient protocols and outage behavior,” IEEE Trans. on Information Theory, vol. 50, no. 12, pp. 3062–3080, Dec. 2004.

SNR ADVANTAGE ( in dB)

Div ( N c
)

10 log
1 0
N c



Diversity gain
– >13 dB in Rayleigh-fading channels
Array gain (e.g. 6 dB with 4 nodes)
– When all nodes transmit with same power
Extra SNR can be used for range extension, TX power reduction, lower PER, higher data rate




Cooperating nodes transmit at the same time
– A commonly received packet provides reference for synchronization
The alternative is time-division CT
– Nodes transmit in non-overlapping time periods
CCT is better for range extension
– Receivers get the benefit of diversity gain for synchronization
– Less SNR loss from imperfect RX synchronization




Non-coherent
FSK
Median rms TX time spread for
-5 dBm TX pwr
– First hop
60 ns
– Other hops
~125 ns
Will see in the demo
Chang and Ingram, "Convergence Property of
Transmit Time Pre-Synchronization for Concurrent
Cooperative Communication," submitted to
Globecom 2010

CCT Range Extension – Dispersed Cluster


Light grey = 2-hop non-CT coverage
Light + dark grey = 2-hop CT coverage
– 80% increase
Jung, Chang and Ingram, "Comparison of Two Cluster Topologies for Cooperative Transmission Range Extension in the 2.4GHz Band," submitted to Globecom 2010



CT yields 280% area increase
But total 2-hop dispersed CT area is 55% larger than tight
Jung, Chang and Ingram, "Comparison of Two Cluster Topologies for Cooperative Transmission Range Extension in the 2.4GHz Band," submitted to Globecom 2010


The nodes near the sink have to relay the data from the rest of the network, and die early
A single sink
Sink


Non-uniform distribution [Wu08]
– Placing more nodes in the area close to the sink
– The extra sensors can significantly raise the cost

Using mobile sensors [Wang05]
– May not be possible depending on the environment and the hardware
[Wu08] X. Wu, G. Chen, and S. K. Das, “Avoiding energy holes in wireless sensor networks with nonuniform node distribution,” IEEE
Trans. Parallel Distrib. Syst., vol. 19, no. 5, pp. 710–720, 2008.
[Wang05] W. Wang, V. Srinivasan, and K.-C. Chua, “Using mobile relays to prolong the lifetime of wireless sensor networks,” in Proc.
IEEE MobiCom, 2005.



Extend range with CT to jump over heavily-loaded nodes
Simulation: Factor of 8X lifetime extension
Virtual MISO Link
Conventional (Non-CT) Routing Cooperative Routing
Jung and Ingram, "Residual-Energy-Activated Cooperative Transmission (REACT) to Avoid the Energy Hole," ICC CoCoNet Wkshp, 2010.

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
A group of nodes that, without coordinating with each other, transmit the same message at approximately the same time in response to a signal received from another transmitter or OLA
Uses:
– Fast, contention-free, reliable broadcasts
– Complexity is independent of density for highdensity networks
– Simple OLA-based unicasting is available
* A. Scaglione, and Y. W. Hong, IEEE Trans.Signal Processing, 2003.

Decoding Level 1
(DL 1 )
OLA 1
Decoding Level 2
(DL 2 )
OLA 2
Decoding Level 3 (DL 3 )
DL 2
DL 3
DL 1
In more energy efficient versions, only subsets transmit
Faster than multi-hop because no contention
* A. Scaglione, and Y. W. Hong, IEEE Trans.Signal Processing, 2003.





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CT is not supported by current protocols
Cooperators have to be selected
– Can be done autonomously in sufficiently dense networks
CCT requires a commonly received packet to provide a synchronization reference
– Need a field in the header to command the CCT
CCT node transmissions must not include their addresses
– Received signal must appear to have come from a single node through a multi-path channel
Distributed ARQ required for OLA transmissions
(OLA has no cluster heads)
For energy balancing, the set of all potential cooperators must be informed of Sink Nav


Objective

Cooperative Transmission

Energy Harvesting and Storage

RFID and Sensors

Wake-up Radios

Conclusions

How Georgia Tech can help

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

Success of embedded/pervasive devices depends on success of energy harvesting
Device technologies are developing fast
– Harvester prototypes for almost every kind of energy
– Amounts of energy harvested differ by orders of magnitude (solar highest; RF lowest)
– Storage technologies are also developing fast
MAC/routing research is slowed because of inadequate system-level models for harvester and storage
M.A. Ingram et al., “Energy Harvesting Wireless Sensor Networks,” in Globalisation of Mobile and Wireless Communications: Today and in 2020, R. Prasad, ed., Springer, to appear Spring 2009.


Rechargeable battery (RB)
– High energy density
– Low peak power
– Low leakage
– Few hundred recharge cycles
– Constant voltage
– Sensitive to depth of discharge

Supercapacitor
(SC)
– Low energy density
– High peak power
– High leakage
– Million recharge cycles
– Variable voltage
– Not sensitive to depth of discharge
19


Harvester has low efficiency if storage device is not impedance matched to source

Source impedance varies

Optimal matching circuits have to track the source, but can consume too much energy themselves


Harvesting takes time-
– Devices can be unavailable for minutes to hours while harvesting

Duty cycling becomes problematic because of random node availability
– Adaptive control theory proposed for aperiodic energy sources


Objective

Cooperative Transmission

Energy Harvesting and Storage

RFID and Sensors

Wake-up Radios

Conclusions

How Georgia Tech can help

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


Mature technology
Optical bar code replacement
Passive RF Tag
– No battery on board
– Processor activated by a reader’s RF signal
– Reader has to be close (few meters) – limited by activation
– Modulated backscatter for transmission

Eliminates power amplifier
Semi-passive RF Tag
– Battery on board, runs the processor
– Modulated backscatter for transmission
– Read range longer- limited by mod backscatter

New: RF Tag + Sensor + Energy Harvesting


Two-tier network
– Top tier: mesh network of readers

Access power mains
– Bottom tier: low-power semi-passive sensors


Powered by harvested ambient energy
Communicate with top tier by modulated backscatter
Dedicated source can provide RF for energy harvesting (PowerCast)
– This source need not be a communicating node
– Powers nodes where there is no ambient energy

Behind walls, low-light areas, above the ceiling
Clark et al., "Towards Autonomously-Powered CRFIDs," Workshop on Power Aware Computing and Systems (Hot-Power ’09),
October 2009
A. Sample and J. R. Smith, "Experimental Results with two Wireless Power Transfer Systems," 2009.


MAC needed for reader transmissions

Multiple readers can collide trying to read the same tag

Reader TX power for modulated backscatter is higher than traditional radio- larger interference range

Must provide time for power-up delay
Waldrop et al, “Colorwave: A MAC for RFID Reader Networks,” 2003
G. P. Joshi, S.W. Kim, “Survey, Nomenclature and Comparison of Reader Anti-collision Protocols in RFID,” IETE Tech Review [serial online’ 2008.


Objective

Cooperative Transmission

Energy Harvesting and Storage

RFID and Sensors

Wake-up Radios

Conclusions

How Georgia Tech can help

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


A well known significant source of energy drainage is radio idle listening
Traditional power management uses duty cycling
– Nodes periodically wake up to check if they are needed. Most of the time they are not needed.
An ultra low-power radio can be used to trigger a remote interrupt at the sleeping device when communication with the device is required
Enables more efficient utilization for event-based and on-demand applications
Van der Doorn et al, “A prototype low-cost wakeup radio for the 868 MHz band,” Int. J. Sensor Networks, Vol. 5, No. 1, 2009


~20 m W to 170 m W consumption

-75 dBm sensitivity @ 915 MHz

0.5 m to 2 m range from 0 dBm transmitter
Le-Huy and Roy, “Low-Power Wake-Up Radio for Wireless Sensor Networks,” Mobile Networks and Applications, April 2010.
Van der Doorn et al, “A prototype low-cost wakeup radio for the 868 MHz band,” Int. J. Sensor Networks, Vol. 5, No. 1, 2009


Wake-up radio operates like passive
RFID

Wake-up radio is less complex than
RFID and requires less power to be energized


In wake-on radio, the radio wakes up periodically to listen for incoming packets without microcontroller interaction

Wake-up radio does not wake up periodically
Lu et al, “A Wake-On Sensor Network,” Sensys, 2009


How often should wake up signals be sent?

Wake up signal wakes all nodes in the neighborhood

Collisions can happen between nodes sending wake up signals






CT offers many advantages for networks of highly energy-constrained radios; CT is not supported by current protocols
Energy harvesting and storage makes dutycycling difficult – good models lacking
Wake-up radios can make duty cycling much easier; current technology is short-range
RFID with energy harvesting is sustainable, but needs reader
All these technologies would significantly impact the standard


Objective technology assessment

Determine protocol changes to support specific technologies

Prototype development and prototype testing

Channel and device modeling

Certification test design