Transcript Design Issues for Wireless Networks Across Diverse and Fragmented Spectrum Collaborators: Bell Labs India: Supratim Deb, Kanthi Nagaraj Bell Labs USA: Piyush Gupta All Rights Reserved.

Design Issues for Wireless
Networks Across Diverse and
Fragmented Spectrum
Collaborators:
Bell Labs India: Supratim Deb, Kanthi Nagaraj
Bell Labs USA: Piyush Gupta
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Mobile Data Explosion Will Result in Diverse & Fragmented Spectrum
Examples:
 AT&T Spectrum in New York – 700MHz band, 800MHz, 1.7GHz and 2.1GHz
 Unlicensed Spectrum in US – DTV Whitespaces (500-700MHz), 2.4GHz and 5.1GHz
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Research Goal
Design a network stack that operates across
1) Fragmented and spatially varying spectrum with diverse propagation
2) Devices with different tunable center freq. and b/w range
Routing + Flow
Control
MAC + Spectrum
New Design
Perspective
Selection
PHY + Sensing
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Lot of research
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No fixed interference graph
 Frequency dependent propagation
 Complicates spectrum allocation and MAC design
 No fixed communication graph
 Next-hop (hence, routing) depends on frequency
 Leakage power at a distance depends on
frequency
 Adjacent channel interference (hence, guard
band) varies with frequency
 Cross layer optimization is highly complex
slope = －20
log fc 
Power Spectral Density 
 Devices can tune frequency and bandwidth
 Non-channelized system  complex MAC
Received Power at
fixed distance, power (dB) 
Designing MAC and above: Unique Challenges
All traditional network stack design issues require a
fresh look.
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Interference Management
 Standard Approach:
 Measurement based interference map
 But, if the spectrum is diverse …
 Two devices may interfere only in certain frequency bands
Design Principle:
 Generate different interference maps for different bands
 Ideally a single/small number of control channels
 Can use measurements over a single control channel
 Pr(f1) － Pr(f2) ＝ 20 log(f2/f1)
Interference maps in a higher freq. band can be
deduced from interference map in a lower band (and
knowledge of ambient interference)
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Agile and Efficient MAC for
Unlicensed Access in TV
Whitespaces and ISM Bands
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Gist of FCC Mandate
 Usable Free Spectrum: Unused TV channels between 500-698 MHz for
unlicensed portable access
 Varies from city to city
 Limit Interference to DTV receiver:
 Tx power: 16 dBm in adjacent band, 20 dBm elsewhere
 Out of Band Emission: Has to fall by 55 dB in the adjacent 6 MHz band
 Spectrum Mask
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Single Link Capacity With ACI Constraints
 Fundamental Question: What’s the optimal transmit power anyway?
 High power-> lower bandwidth
 Guard band required to prevent interference to the TV channel
16 dBm
Freq •
DTV Channel
Freq  •
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Optimal capacity is independent on center frequency
For FCC’s spectrum mask, the power cap is not too
sub-optimal
Design Implications:
•
DTV Channel
•
Observations:
Choose fixed power (marginal loss in capacity)
DTV Channel
20 dBm
DTV Channel
 Low power -> reduced system capacity
Ensure a minimum bandwidth (leakage depends on PSD)
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MAC Design Considerations
 Fragmented spectrum + limitations on
maximum tunable bandwidth of a radio
implies
 Multi radio AP, single radio client (for
cost considerations)
 Need to account for frequency
dependent propagation
Resilient to disruptions
 E.g. wireless microphones
 Evolution over WiFi
 Easy adoption path, quick time to
market, can interoperate with ISM
bands
 IEEE 802.11af standard already in
progress
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Joint Spectrum Selection and Client Allocation
4
3
2
1
5
6
(1,2,3,4,5,6,7)
(1,2,3,4,5,6,7)
(1,2,3,4,5,6,7)
(1,2,3,4,5,6,7)
Joint Spectrum Selection and Client Assignment is a non-trivial problem
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7
Capturing the Utility of a Band
Important Observation:
 For most technologies, data rate/Hz
Client-1
depends on SNR as
Data Rate / Hz = a × (SNR in dB) - b
Client-2
ASE = Data rate averaged over all clients / Hz
= a × (SNR averaged over all clients in dB) – b
SNR(f1) － SNR(f2) ＝ 20 log(f2/f1)
ASE in f1 can be generated for ASE in f2
Design Implication:
 Two step ASE generation:
 Each AP generates ASE in control channel band.
 Use frequency dependence and ambient interference measurements to
compute ASE in all bands.
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Proportional Fairness is Key for Whitespaces
More likely that
far away client
will bring down
performance of
system
6Mbps
600MHz
6Mbps
2.4GHz
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Very simple
design with
minimal
information
overhead on
top of 802.11
ensures
proportional
fairness
Simulation Results
Comparison scheme
 White space selection algorithm is
optimal
 Number of clients assigned per band is
proportional to number of clients
 60-90% improvement in total throughput
 Proportionally fair
 Frequency agnostic schemes do not work
well!
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Making it Work in Practice
 Designed frequency translator with < 2
microsecond switching delay
 Dynamic range of 100- 900 MHz
 Integrates with a WiFi card on Sokeris
box
 Extensive indoor trials done
 Waiting for experimental license for
outdoor trials
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